ASQ Six Sigma

Workshop on Structured Problem Solving Using DMAIC Methodology

Agenda 

Day 1:



TQM



Introduction to Six Sigma



Define Phase



Project Charter



Day 2:



Seven QC Tools



Process Mapping

Day 3: FMEA Process Capability Control Charts Day 4: Lean Enterprise Day 5: VSM Exercise NTPC Case Study Exam & Wrap Up

The Evolution of Quality • Provides a framework for understanding the history of the quality movement. • Expands the definition of quality. • •

Juran’s Definition of Quality Defined as “fitness for use” based on: • Customer’s perceptions of product design. • Degree to which a product conforms to design. • Product’s availability, reliability, and maintainability. • Available customer service. 

ISO Definition of Quality • Degree to which a set of characteristics fulfills requirements Requiremen ts: Convenienc e and speed

Crosby’s Definition of Quality

• Quality is conformance to requirements. • Requirements are answers to key organizational questions: –How quickly will orders ship? –What is our return policy? –What forms of payment are acceptable?

Quality Evolution: Medieval Guilds

Guilds: uDeveloped strict rules for products and services. uUsed stamps to identify flawless goods.

1 2 0 0

Quality Evolution: Product Orientation

uMaster

craftsmen trained apprentices. uIndustrial Revolution divided trades into specialized tasks; inspectors guaranteed quality. uTaylor system increased productivity; inspection departments found defects.

1

2

0

0

Quality Evolution: Process Orientation

uProcesses became uShewhart identified

critical. statistical

quality control. uDeveloped strict rules for products and services. uQuality became relevant for process, not just product.

1

2

0

0

Quality Evolution: Wartime

uQuality

became a safety

issue. uThe military developed a sampling inspection system and trained suppliers.

1

2

0

0

Quality Evolution: Total Quality Movement

uDeveloped

in response to Japanese quality movement. uFocused on improving all processes through people who used them.

1

2

0

0

W. Edwards Deming Quality keys: • Understanding customer needs • Process improvement • Statistical analysis • Expertise of workers • PDCA cycle • 

Joseph M. Juran Quality keys: • Features that satisfy customers • Freedom from deficiencies • Juran Trilogy® 

– Quality planning – Quality control – Quality improvement

Kaoru Ishikawa Quality keys: • Company-wide participation • Quality control circles • Advanced statistical methods and tools • Nationwide quality control promotion 

Armand V. Feigenbaum Quality keys: • Total quality control • Integration of quality development, maintenance, and improvement • Focus on internal and external customers • 

Genichi Taguchi Quality keys: • Quality should be designed in. • Quality should minimize deviations from a target. • DOE optimizes performance. 

Philip Crosby Quality keys: • Conformance to requirements • Prevention • Zero Defects • Price of nonconformance • 

Total Quality Management 

Total quality management (TQM):

• A management approach • Centered on quality • Based on company-wide participation • Aimed at long-term success • Through customer satisfaction 

3 Cs of TQM

1

Customer relationships

2

Continuous improvement

3

Company-wide participation

Customer Definitions 1

Levels of Customer Satisfaction 1

Noriaki Kano identified three levels: • Expected quality • Desired quality • Excited quality 

Customer Feedback 1

Has two parts: ◆ Efforts to capture what customers say about company’s products/services ◆Efforts to drive feedback back into organization

Partnering with customer: ◆ Extension of listening to customer feedback ◆ Most direct route to customer satisfaction

PDCA 2 • A well-known model for continuous process improveme nt is the Plan-DoCheck-Act cycle.

A

Company-Wide Participation 3

• Leadership must come from management. • All employees must be involved. • Employee involvement usually requires employees to work in cross-functional teams.

Employee Involvement 3

Benefits • Improved productivity and cost reduction • Increased participation and job satisfaction • Opportunities for professional development 

Barriers “It Won’t Work Here” Perception of loss of management authority Employees feeling “used” “Flavor of the month” 

• •

• •

Quality Benefits

• Tangible – Increase in earnings – Decrease in waste – Increase in productivity

• Intangible – Customer goodwill – Alignment between business activities

W. Edwards Deming on Quality • Meeting customer needs + wants = quality. • Quality improves products/services and processes. • Improved products/services and processes = profitability.

A Quality Approach Benefits . . . Organizations

Employees

Customers

Suppliers

Society

Benefits to Employees Pride in products and services Job satisfaction Improved communications Streamlined work processes Happier customers Strong customer relationships Greater job security/benefits

Benefits to Organizations

Quality Studies and Standards Released the Profit Impact of Market Strategy (PIMS) study. Partnered with the Baldrige recognition program. Both organizations support the link between quality and profitability.

External and Internal Customers

Publication Department

Sales Department

Customer

Benefits to Customers Quality results in: • Increased choices. • Improved goods and services. • Expectations met or exceeded. 

Benefits to Suppliers • Achievement of performance requirements • Streamlined processes • Efficient communication • Increased customer satisfaction

Benefits to Society

Economic growth and stability



Increased employment opportunities

Product safety

Process Management Quality improvements are applied to single processes within manufacturing. Quality improvements are applied to all organizational activities through process management.

Organizational Process

Introduction to Six Sigma

What is Lean Six Sigma? Introduction • Six Sigma goal is process perfection through defect reduction. • Lean goal is cycle time reduction through elimination of waste. “Only those companies that eliminate their defects will have what it takes to win.” “Breakthrough companies strive for 100 percent DEFECT-FREE products and services.” Larry Bossidy CEO of AlliedSignal

What is Six Sigma? Methodology and Improvement Strategy • •

Six Sigma is an overall strategy to accelerate improvements in processes, products, and services–create breakthrough. Six Sigma measures how effective strategies are in eliminating defects and variations from processes, products, and services.

+

= Y

f(x1,

+ ...

+ x2,

x3

Process output (Y) is a function of (f) the inputs (Xs). Understanding and controlling this relationship is a major aspect of Six Sigma projects.

…)

Focus on Variation • Sigma (σ) refers to standard deviation, a measure of process variation (smaller is better). • Process Sigma is the number of units of standard deviations between the process center and the closest specification limit (larger is better). • A Six Sigma process has six standard deviations (short term) between the target and the closest specification limit. Lower Spec

Target

Lower Process Control Center

Upper Spec

Upper Control

6 Standard Deviations

6 Sigma

Sources of Variation Desig n Materi al

$

Process Capabil ity

Measurem ent System

Harvesting the Fruit of Six Sigma Sweet Fruit

Design for Manufacturability

5 σ Wall - Must Address Designs 5 σ Wall - Must Address Designs

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -4 σ Wall - Must Improve Internally

4 σ Wall - Must Improve Internally

Low Hanging Fruit Seven Basic Tools

----------------------------------

3 σ Wall - Demand improvement 3 σ Wall - Demand improvement

Ground Fruit

Logic and Intuition

The walls crumble faster when working WITH suppliers and CONCURRENTLY addressing design and process issues

da nu ou s Co nti

Process Characterization and Optimization

ta

Bulk of Fruit

D is c r e t e d a ta

The Focus of Six Sigma

• • • • • •

f (X)

Y

Y Dependent Output Effect Symptom Monitor

•X1

. . . XN •Independent •Input-Process •Cause •Problem •Control

Would you control shooter or target to get the Gold Medal at Olympics

Six Sigma Defines Problems Statistically

Y= f (X) The product is used to evaluate the process.

Y - Outputs uDependent uOutput uEffect uSymptom uAble to Monitor

Should we focus on the process outputs (Y) or inputs (X)?

X1 . . . X N Inputs uIndependent uInputs, process uCause uProblem uControllable

The process is used to control the product.

99% Good (3.8 Sigma)

99.99966% Good (6 Sigma)

20,000 lost articles of mail per hour

Seven articles lost per hour

Unsafe drinking water for almost 15 minutes each day

One unsafe minute every seven months

5,000 incorrect surgical operations per week

1.7 incorrect operations per week

Two short or long landings at most major airports each day 200,000 wrong drug prescriptions each year No electricity for almost seven hours each month

One short or long landing every five years 68 wrong prescriptions per year One hour without electricity every 34 years

Define Phase

The Define Phase The define phase module provides an overview of the following tools: 

1.Project selection 2.Project charter 3.Supplier, Input, Output, Customer (SIPOC) diagram 4.Collecting Voice of the Customer (VOC) 

Projects Must be … Meaningful And Manageable!

Sorting Projects from Messes • A mess is a morass of unsettling symptoms, causes, data, pressures, shortfalls, opportunities, etc. • A problem is a well-defined situation that is capable of resolution • Identifying a problem from within the mess is frequently the first step in the process of project definition •

Project Qualifications • There is a gap between current and desired performance. • The cause of the problem is not clearly understood. • The solution is not predetermined. •

Project Selection is Critical • High leverage projects lead to largest $$ Savings • Large returns justify the investment in time and effort • Developing a Lean Six Sigma culture depends upon successful projects having significant business impact • Black Belt training depends on completion of a meaningful project within ~ 6 months • Future Projects are frequently identified through initial projects •

Lean Six Sigma Project Criteria • Aligned with business objectives and plans – Voice of Customer/ Critical to Satisfaction (CTS) – Quality (CTQ) / Cost (CTC) / Delivery (CTD) • Consistent with principles of Six Sigma – Elimination of process defects – Reduction of variation • Concentrates on significant issues/opportunities ..... not “problem of the day” • Justify the investment •

Project Selection “The best Six Sigma projects begin not inside the business but outside it, focused on the question — how can we make the customer more competitive? What is critical to the customer’s success? … One thing we have discovered is that anything we do to make the customer more successful inevitably results in a financial return to us.” Jack Welch Address to the General Electric annual meeting April 23, 1997

What is Customer Satisfaction? • A comparison of expectation to experience • A matter of degree • A result of a good match between supply and demand • A predictor of repeat business •

Customer Needs Translated into “Critical To” (CT) Characteristics Customer needs are translated into product, service or deliverable requirements in terms of quality, delivery and cost. The “Y” of Y=f(X). Typical Critical to Characteristics

Y

CTQ

Critical to Quality

CTD

Critical to Delivery

CTC

Critical to Cost

Breakdown of • Projects are identified by the relationship between the processes product, service, or deliverable requirements and processes. required to produce the • The process parameters that affect the requirements are later identified (X , X , … X ) product, 1 2 n service, or deliverable. • Leverage processes are identified.

Project Selection Criteria Pain area Faster Deployment

Aligned with core objectives

Stakeholder Satisfaction

Repeatable

High probability of success

Higher returns

Process Improvement Data Availability

S. No. 1 2 3 4

Criteria

Weight

Aligned with core objectives High probability of success Data Availability Pain area

10 10 8 8

5

Process Improvement

7

6

Higher returns

8

7

Repeatable

6

Faster Deployment

5

Stakeholder Satisfaction

7

Ease of implementation

6

8 Ease of implementation 9 10

Project Selection Matrix Diagram Project 1 S. No. Criteria

Project 2

APC Reduction in Boiler (Stage II) stage I Optimization

1

Aligned with core objectives

2

High probability of success

3

Data Availability

4

Pain area

5

Process Improvement

6

Higher returns

7

Repeatable

8

Faster Deployment

9

Stakeholder Satisfaction

10

Ease of implementation

Strong Relationship

Project 3

DM (Stage I) Make up ESP (Stage I) Inlet Optimization Duct Replacement

Moderate Relationship

1 0

Selected Project

Project 4

Project 5 Soot Blowing Sy.Optimization

Weak Relationship

6

3

Factors that Improve Project Success • Dedicated Black Belt • Champion phase reviews • Black Belt has knowledge of process/product to be improved • Historic data • Clearly defined deliverables • Committed process owners (skin in the game) with the authority to modify the process •

Project Metrics – Success Criteria Primary Metric • Used to measure project success • Consistent with the problem description and objective • Plotted on a time series graph and shows the goal and actual performance lines 

Secondary Metric(s) • Control unintended negative consequence (assures the Primary Metric is not achieved artificially) • May be used to measure project progress when the Primary Metric responds slowly • More than one may be required • Plotted on a time series graph and shows the goal and actual performance lines 

8

Project Charter Traditionally created by LSS Champion Specifies details of a project including: 

1.Scope 2.Responsibilities 3.Benefits 4.Schedule 5.Success criteria A project charter template that may be adopted to fit your organization is: Project Charter Template.

SIPOC Supplier, Input, Process, Output, Customer diagrams are used to: 1.Define the scope of the project 2.Identify key stakeholders 3.Gain a “30,000 foot” view of the process targeted by the project Tips: 1.The SIPOC is the first of several ways the process will be documented. Therefore, it should be at a relatively high level of abstraction. 2.It is a good way to assure agreement on the scope of the project. 



SIPOC Diagram – Questions to Answer • Who are the customers of this process? • What are their requirements? • How are those requirements reflected in the process parameters (output measures)? • What are the process outputs? • What are the process inputs that cause the outputs? • What controls are in place for the inputs? • Who are the suppliers of the material for this process? • What are their requirements?

Purpose of Various Diagrams / Maps • SIPOC diagrams provide a “forest view” of the process – maintains focus on the customer’s requirements. • Value stream “trees level” describes the time, effort, resources, and information used in the process – a frequent source of early wins. • Lay-out diagram (spaghetti diagram) documents the distance an item travels during its production – illustrates unnecessary movement. • Process map “ground level” documents the inputs and outputs of each step in the process – provides the raw material for building a model of the process. •

The SIPOC Diagram – The Forest Level • • • • • • • • •

Start with the end in mind. Who are the customers of this process? What are their requirements? How are those requirements reflected in the process parameters (output measures)? What are the process outputs? What are the process inputs that cause the outputs? What controls are in place for the inputs? Who are the suppliers of the material for this process? What are their requirements?

Sample SIPOC Supplier(s)

Inputs/Req'ts

Process

Output(s)/Req'ts

Grocery store Utility Company Appliance store

Coffee machine Measuring cup Electricity Qualified operator Water Filters Cream/milk Sweetener Ground coffee

Install filter Measure coffee Add coffee Add Water Turn on machine

1800 Specified number of cups No grounds < one hour old Dark Hot Aromatic Fresh Strong

Customer(s)

Husband Wife Guest

SIPOC Validation Review the SIPOC with your: team, Champion and process owner(s) to assure agreement on the SIPOC content as well as the project scope and success criteria among all stakeholders.

S

I Inputs

Suppliers Coal Field Rihand Dam Suppliers

P

O

C

Process

Outputs

Customers

Coal Water

Power Effluent Process Ash

Air Power

Steam CO2

Manpower Lubricants

Internal -Plant Mgmt -Corp Mgmt -Employee External -Cent.Gov. -Ministry

Maintenance Services Spares and

-State Gov. -Shareholders

Consumables

-Contractors -Suppliers -PAPs -Labour Environment

Boiler Turbine COAL AIR WATER

STEAM

CTQs Plant Availability UI Earned Plant Load factor Heat Rate

AUXILLIARY POWER CONSUMPTION Preferred Employer R&R Man : MW Ratio Lead Time Manpower Utilization Quality System Social Responsibility Maintenance Cost Overhead Expenses

ENERGY EFFICIENCY DM Water Used Safety aspect

Generator

GRID

Training of manpower Cycle Time In process idle stock Air Emission quality Noise level

Collecting VoC • Who is a customer? • What does the customer need? – Gathering the Voice of the Customer – Define customer requirements

• How do the customers prioritize their needs? • How are customer needs translated into CTQs? uGenerally

a less intense exercise for DMAIC projects than for DFSS projects

uMore

likely to be based on information that is already available internally for DMAIC projects than for DFSS projects

Who Is a Customer? Process Voice of Customer

Step

Step

Step

Product/ Service Customer

A customer sets/affects requirements for your product or service. External Buying customers End-users Regulatory agencies A customer is one who receives your output. Internal

Customer Segmentation •Generally, external customer needs are more important than internal customer needs. •Are all customers equally important? –External vs. internal –Customer segments •Regions •Type of business •Volumes •Profitability •Strategic market •Future potential •

Voice of the Customer • The Voice of the Customer (VOC) is the starting point of any project and data collection plan. • The Voice of the Customer includes: – Expectations – Requirements – Opinions

–

Questions to Find Voice of the Customer • What are the elements of your business that are the most critical, from the perspective of your top or best customers? What are their relevant needs? • What data has been collected to understand the customer requirements? • How do you operationally define the defect from the perspective of the customer? Under what conditions does it occur?

Voice of the Customer Concerns • Real vs. stated needs • Perceived needs • Intended vs. actual usage • Internal customers vs. external customers • Effectiveness vs. efficiency needs • Change over time

Determining Customer Requirements • Use verbatim comments from customers to help determine the key customer requirements – We often receive many verbal comments from our customers. – We need to look for ways to probe for deeper meaning behind the comments in order to translate these comments into what the customer actually requires.

•

Tools for Gathering Voice of the Customer 

Unsolicited data from customers – Complaints – Field reports – Trade journals – Benchmarking – Internal research • • • •

•

Requirements documents Contracts Customer observation Be a customer

Tools for Gathering VOC Solicited data from customers



– Interviews – Focus groups – Surveys – Informal customer discussions – Market research

•

Determining Customer Requirements • Review customer verbatim comments and comparative data • If possible, probe for deeper understanding • Convert into terms of process performance • Describe the actual customer requirement – Write the requirement, not the solution – Use measurable terms – Identify performance targets – Be concise

Define Phase Review • The purpose of the define phase is to identify and launch a project. • VOC should be reflected in the project charter especially in the project success criteria. • The Black Belt and Champion should review and agree on the details of the project charter and SIPOC. • A common cause of project failure is poorly defined or projects with excessive scope. This review is an opportunity to mitigate that risk.

D M A I C

VOC ( Voice of Customer )

Generation & Dispatch

Environmental Pollution Conservation of Coal

RATING

5 5 4 4

5 5 4 4 4 5 4 2 4 5 4 4 5 5 2 5

81 90 64 66

Better

Same

Competitor Worse

Replace with eff. pro

Systems Better

Arrest Pro.Deviation

Aux Power Consumption

Improve Processes

WHAT ?

CustomerNeed Needs Customer

Ranking ( 1-5 )

HOW ?

D M A I C Project Charter

D M A I C Resource Plan Champion: Process Owner: Process Owner: Quality Leader Coach (BB): Green Belt:

S. Sinha TMD V. Agarwal EEMG

Mr. P.K.Mohapatra Mr. N.N.Mishra Mr. N.K.Sinha Mr. S. Mathew Mr. S. Banerjee Mohit Yadav Iswar BMD Ashish Jain EMD

Green Belt Contact Information :

General Information

Project Review Dates Tollgate

Date

Define

Big Y:

Measure Analyze

Reduction in APC of Stage-I units

Improve Control

Mohit Yadav 9425823299 1550

05/02/ 07 05/04/ 07 15/04/ 07 31/05/ 07 31/08/ 07

Project Team Rhythm and Review Meeting Frequency: Mandatory Attendees: Optional Attendees:

Signoff

(xx/xx/xx)

Yes Yes Yes Yes Yes

Rhythm and Review: On-Track Off-Track Need Attention

15 Days Mohit Yadav

V. Agarwal

Mr. P.K.Mohapatra

Mr. N.N.Mishra

Iswar

S. Sinha

Mr. N.K.Sinha

A. Jain

Mr. S. Banerjee

VOC ( Voice of Customer )

The Seven QC Tools

➨ ➨ ➨ ➨ ➨ ➨ ➨

Check sheet Stratification Pareto diagram C &E Diagram Histogram Scatter diagram Graphs and Charts

v Problem Solving v Continuous Improvement-- Kaizen v Dispersion Control-- Six Sigma v Waste Elimination--Lean v QMS, EMS, TS 16949, OHSAS-Process control, C&P v Supplier Development v Project Management--Team working

What is their role ?

In problem solving

Tool

Role they Play









Data gathering

 



Check sheet





Stratification

 

Quantify current status or magnitude of the Problem Facilitate data gathering 



Identify and segregate different sources of the problem 

•



Tool



• Pareto diagram •

• Brain storming 

• Cause & effect diagram



Role they Play



• Prioritize the problem •

• Generate many ideas for solving a specific problem • Identify possible causes of a problem in a structured way •



Tool





Role they Play





• Histogram

• • Scatter diagram

• Study pattern of variation in a set of data. • Study relationship between 2 types of variable



• Visual display of data

• Graph & chart



•

DATA GATHERING

Data Collection

What is Data ? Data is a numerical expression of an activity

Conclusions based on facts and data are necessary for any improvement. K. Ishikawa If you are not able to express a phenomenon in numbers, you do not know about it adequately Lord Kelvin

Types of Data

Quantitative •Measurable  e.g. :Length, Temperature •Countable  e.g. :Number of defects

Qualitative •Subjective assessment e.g. :Score in a beauty contest

Population, Sample and Data

Action

Population

Random Sampling

Sampl e Action

X

Measurement / Observation

Data

A Saying q When you see the data, doubt it q When you see the measuring instrument, doubt it. q When you see the chemical analysis, doubt it. q Three Categories q

  

1 False Data 2 Mistaken Data 3 No Data available

How to Collect Data? qDefine the purpose (Follow 5W 1H approach). qDefine the period for data collection. qDefine the Stratification. qDesign the check sheet and assess Measurement System Capability.

Purpos e

Be Clear on What, Where, When, Why, Who and How the data should be generated

STRATIFICATION



Stratification





vMethod of grouping data by Common  points or characteristics

v

vA Filtration Process for isolating the  cause of a problem. 

vPrevent mix up and helps in easy &  faster identification-

Basis for Stratification Workers



Machines



Defect



  

Product Folder 

Material Time Environment

Region Files 



Machine Machine A A

Machine BB Machine

N = 450 N = 450 D = 12D = 12 P% =P% 2.7= 2.7

N 450 = 450 N= = 118 D =D 1118 P%== 26.2 26.2 P%

COMBINED N = 900 D = 130 P% = 14.4

Blister Defect UCL CL Pinhole Defect UCL C L All Defects

UC L CL

CHECKSHEET



Check sheet

 

v 

A convenient and compact format for data collection



v A Simple rule– Maximum 

information with minimum writing



efforts and easy to fill

v

Check Sheet For Machining Operation Location M/C No.

Comp.

DRG. No

Date

Group Token No.

Op.

Qt. Prod. Material Defect No. Insp. 1 2 3 4 5 6

M/c Defects

Total

Remark

A B C D………P Q R

Machining Defect

Material Defect 1: Blow holes 2: Cracks 3: Hard Metal 4: Eccentric 5: Others 6: Total

Shift

A: Dia.+ B: Dia.C: Ch+ D: ChE: CDV+ F: CDV-

G: Length+ H: Length I: Sp+ J: SpK: D& T Size+ L: D & T Size-

M: Oblong N: Taper O: Hole Shifted P: PCDV Q: Poor Finish R: Others

Graphs & Charts Graphs represent data pictorially. A picture can see what 1000 words can not tell. v Line chart v Bar chart v Multiple bar Chart v Component bar Chart v Radar chart

v Pie chart v Gantt chart v Pareto diagram v Scatter diagram v Control chart

v

•

v

v

Bar Chart Bar graphs are parallel bars of identical width but differing length to compare size of different quantities / things.

Line Chart

Line graphs manifest the overall trend in time series data by direction of their lines.

Pie Chart Pie charts makes it easy to grasp the breakdown of the components of a quantity over a certain period.

Comparison of Machines A & B for weekly Rejection

% Rejection

25 21

20

20

15

14

15 11 10

15

13 10

Multiple bar chart

20

11

13 11

10 8 6

5

5

4

3

2

3

0 1

2

3

4

5

6

7

8

9

10

Week Number

Comparison of Machines A & B for Units Produced 900 800

Component bar chart

Units Produced

700 600

400

358 281

317

29 9

375

321

307

29 4

6

7

8

9

336 2 44 221

300

435

200 100

422

257

500

2 63

285

201

2 75 348

1 33

0 1

2

3

4

5

W eek N umb er

10

Pie Chart for Customer returned watches

E 4%

•A – Glass Broken

F 3%

D 6%

•B - Stop •C - Mvt. Trouble

A 43% C 12%

•D - Defective Dial •E - Regulation •F - Stem Loose •G - Others

G 5%

B 27%

Control Chart

X- Bar and R Chart Xbar/R Chart for C1

Sample Mean

2854

UCL=2853

2849

Mean=2849

LCL=2844

2844

Sample Range

Subgroup

15

0

5

10

15

20

25

UCL=16.41

10 R=7.76 5 0

LCL=0

Radar Chart on ISO 9001-1994 Implementation 1 20

80

2

70

19

3

60 50

18

4

40 30

17

5

20 10

16

6

0

15

7

14

8 13

9 12

10 11

Series 1

Gantt Chart for Construction Activity

Weeks

Type of work

1

2

3

4

5

6

7

8

9

10

11

Foundation work Frame work Dry-walling Exterior touch up Sheetrock work Plumbing Electrical wiring Fit Fixtures Paint interior wall Interior touch up Inspection delivery

Gantt Charts makes it easy to understand the details of a plan and progress in its implementation schedule.

12

Pareto Diagram

Vital few from Trivial many 94.6

100

87.5

50

90

76.8

80 70

60.7

60 30

50

41.7

40

20

30 20

10

10 0

0

Fish not Vegetable fresh wilted

Bread Stale

Cashier Rude

Meat not Eggs rotten Fresh

Cum Percentage

Pareto Analysis of Customer Complaints

No. of complaints

40

100

Pareto Principle

v80% of problems are caused by less than 20% of probable causes vEstablishes proof of the need vIdentifies vital few

PARETO ANALYSIS: Outstanding branch wise BRANCH

BRANCH

Rs . DUE

RATIO TO TOTAL

CUM . %

A= 5.0 B= 2.5 C = 10 . 0 D = 20 . 0 E = 45 . 0 F=1.5 G=1.0 H=1.5 87 Oth. 0.= 0 . 5

E D

45.0 20.0 10.0 5.0 2.5 1.5 1.5 1.0 87 0.5.0

51.7 23.0 11.5 5.7 2.9 1.7 1.7 1.2 100 0.6 .0

51.7 74.7 86.2 91.9 94.8 96.5 98.2 99.4 100.0

C A B F H TOTAL G OTHERS

Pareto Analysis on Outstanding

91.9

94.8

96.5

98.2

99.4

100

86.2

50

90

74.7

80 70 60

51.7

50 40

20

30 20

10

10 0

0

E

D

C

A

B

F

H

Branches

G

O

Cum Percentage

Outstanding Value

40

30

100

Pareto Diagram for Production Stoppage 45

90

B.Intermediate conveyor

40

80

C.Power failure

35

70

D.Hopper/duct line jamming

30

60

25

50

20

40

15

30

10

20

5

10

0

0

E.Dryer drum coupling pin F.B P full press problem G.Dryer preventive H.Nip roller I.Rotary comb tripped J.Comber jamming K.Al conveyor idle roller L.Fire M.Accumulation N.Drum seal changing O.Fan tripping P.Chain problem

No. of stoppages

A.M/C quality change

A B C D E F G H I J K L MN O P Q R S

Cumulative %

100

Pareto Analysis of Complaints at a Laundry 93

200

100

85

180

140

80 70

60

120

60

100 80

100 90

75

160 No. of complaints

98

50

35

40

60

30

40

20

20

10

0

0

Late Missing or Fading delivery wrong colours items

Stains

Creased

Buttons Stretched Missing or torn

Brain Storming

generating large number of ideas by a group of people

Basic Rules vDefer evaluation vFantasize freely vGenerate quantity vBuild on ideas •

Defer Evaluation vPut critical faculties in cold storage - even constructive criticism. v vEnsure a proper climate for acceptance of all sorts of ideas. v vNo idea should be treated as stupid. 

Fantasize Freely vDon’t operate with your brakes on. v

vParticipants are encouraged to generate ideas, no matter how fanciful they are.

Generate Quantity vGenerate as many ideas as possible. v

vA pearl diver will be more successful in finding pearls, when he brings up 200 oysters than when he surfaces only 1520 oysters. 

Build on ideas Idea of one participant is more effectively built up by another participant.

Steps in Brainstorming v Select the topic v v Each member, in rotation gives ideas v v Member offers only one idea per turn, regardless of how many he or she has v v Continue till all ideas are exhausted v v Ideas are recorded and displayed

Benefits v Individual is limited in generating ideas and group produces more ideas v v Ideas are improved upon by members v v Presence of others increases creativity v v Pooling of ideas and resources is made possible by coming together as a group

CAUSE AND EFFECT DIAGRAM

qGraphic tool to represent relationship between an effect and influencing causes qThere can not be an effect without a cause. qReduce incidence of subjective decision making. qIdentify main causes X’s influencing Y

Construction of C & E Diagram v Define problem v Gather members for discussion v Conduct Brainstorming v Group causes into 4M’s v Man, Material, Machine, Method v For each cause, ask, “What goes wrong that produces the effect”. v Identify major causes

Cause and Effect Diagram for high petrol consumption Procedure

Driver

Impatience

Poor anticipation

Craze

Always late Lack of awareness Riding on clutch

Wrong gears

Vehicle

Bad attitude Poor skill

Spark plugs Contacts Life

Heavy Body Shape Inexperience

Wrong culture

High H.P

One way

No turn

Circuitous Road

Road

Fuel mix Carburetor

Engine Cylinders

Restrictions

Technical details

Crossings Traffic

Spares

Spurious

High Petrol

Consumptio n

Impurities Incorrect Octane no.

Tyres Inferior Frequent Petrol Faulty stops Negligence pressure Speed Breakers Additives Ignorance Potholes Irregular Incorrect viscosity Low pressure servicing Poor Clogged Oil condition filters False Steep Not changed economy Low level Maintenanc

e

Materials

Cause & Effect Diagram

PROCESS COOKING TIME

TRAINED

MATERIALS

QTY OF WOOD QLTY COOKING WATER (OLD/FRESH) TEMP. IN PENTOSANS IN FINAL PULP INSTRUMENT UNTRAINED ACCURACY

PERSONNEL

EQUIPMENTS

VARIATION

Uses of C & E Diagram vTrace out real root cause vHelp evolve countermeasures vMaking C & E an education in itself vEveryone participating, learn more about their work. vIs a focus for discussion. vShows level of expertise available. vCan be used for any problem v

v

v

v

v

30 24

25 19

Frequency

20

17

15

12

11

9

10

6 5

3

2

0 1 .7 7 6

1 .8 6 8

1 .9 6

2 .0 5 2

2 .1 4 4

2 .2 3 6

2 .3 2 8

2 .4 2

2 .5 1 2

C o n s u m p ti o n ( K W h )

HISTOGRAM

Histogram vMethod of analyzing data v v

vData is condensed in a table v v

vTabulation is known as frequency distribution. v

vPresented by a Graph displaying distribution of data v

Histogram 

Graph is Characterized by 3 constituents



• centre ( mean) • width (spread-variation) • over all shape v

30 24

25 19

Frequency

20

17

15

12

11

9

10

6 5

3

2

0 1 .7 7 6

1 .8 6 8

1 .9 6

2 .0 5 2

2 .1 4 4

2.23 6

2 .3 2 8

C o n s u m p ti o n ( K W h )

2 .4 2

2 .5 1 2

Histogram Construction vSelect a sample of min. 50 vRecord the measurements. vDetermine the range. vDecide the no. of classes. vDivide range into no. of classes vDetermine boundary or class limits. vPrepare frequency distribution. vConstruct histogram (GRAPH).

Data on Metal Block thickness (in mm) 3.56 3.46 3.48 3.50 3.42 3.43 3.52 3.49 3.44 3.50 3.48 3.56 3.50 3.52 3.47 3.48 3.46 3.50 3.56 3.38 3.41 3.37 3.47 3.49 3.45 3.44 3.50 3.49 3.46 3.46 3.55 3.52 3.44 3.50 3.45 3.44 3.48 3.46 3.52 3.46 3.48 3.48 3.32 3.40 3.52 3.34 3.46 3.43 3.30 3.46 3.59 3.63 3.59 3.47 3.38 3.52 3.45 3.48 3.31 3.46 3.40 3.54 3.46 3.51 3.48 3.50 3.68 3.60 3.46 3.52 3.48 3.50 3.56 3.50 3.52 3.46 3.48 3.46 3.52 3.56 3.52 3.48 3.46 3.45 3.46 3.54 3.54 3.48 3.49 3.41 3.41 3.45 3.34 3.44 3.473.47 3.41 3.38 3.54 3.47

Range= Max. – Min.=3.68-3.30=0.38 N=10 0

No. of classes= 9 Class width= 0.5

Frequency Table

Class no.

Histogram for Metal Block Thickness 45 40

37 33

35

Frequency

30 25 20 15

5

10

9

10 3

3

3.3

3.35

3

1

1

3.65

3.7

0 3.4

3.45

3.5 Thickness (in mm)

3.55

3.6

Histogram for Bearing Thickness

45

41

40 35

Frequency

31

29

30 25

22 18

20 15

17

12 9

10 5

5

3

0 5.24

5.28

5.32

5.36

5.4

5.44

Thickness (in mm)

5.48

5.52

5.56

5.6

Histogram for Energy Consumption

30 24

25 19

Frequency

20

17

15

12

11

9

10

6 5

3

2

0 1.776

1.868

1.96

2.052

2.144

Consumption(KWh)

2.236

2.328

2.42

2.512

Types of Histograms Bell shaped Symmetrical shape with a peak in middle representing a normal histogram

–

30

24

25 19

Frequency

20

17

15

12

11

9

10

6 5

3

2

0 1 . 7 7 6 1 .8 6 8

1 .9 6

2 .0 5 2 2 . 1 4 4 2 . 2 3 6 2 . 3 2 8 C o n s u m p tio n( K W h)

2 .4 2

2 .5 1 2

Skewed to Left & Right

Skewed to Left Caused by centering the process toward high end of the tolerance Skewed to Right Caused by centering the process toward low end of the tolerance..

Bimodal & Truncated

Bimodal : Two combined populations-- two shifts, operators, inspectors, suppliers, machine settings, gages, tools, machines, measurement locations, etc. Truncated: This can happen when a process is not capable of meeting the specifications, parts are sorted from both ends, or too few classes are chosen.

Missing Centre Spike's at Tail (s)

Missing Centre : Centre of the distribution has been sorted from the rest. Portion may have been delivered to a customer with tighter specifications. Spike's) at the Tail (s) : Parts in outer ends of distribution are probably being reworked to bring characteristic just within specifications.

The Need for Transformations--Prediction from a ND is possible … Skew distribution Transformation Before

After

XTrans = 1/XRaw

Histogram Uses vTo know--whether variation in data is due to chance or assignable causes. vTo tell about Process Behavior v --about its capability to produce defect free output v v

Sources Of Variation

vCommon Causes ---Chance Causes Of Variation vSpecial Causes --- Assignable Cause Of Variation

Common Cause vConsists of combined effect of several sources of uncontrollable variation inherent to a process. vCollective influence of common cause variation defines natural process fluctuation and is known as Chance causes of variation. vProcess output is predictable vProcess is said to be in Statistical Control v v

Special Cause vVariation has a large impact on performance. vDetermination of source of impact makes cause "assignable." and is termed as assignable cause of variation. vIf they exist, process or key characteristic is said to be "out-of-control". vOut-of-control process is not predictable

Process Behavior vIt tells whether process is under control? vIs it producing defect free output? v ----process under control or

LS L

Process out Of control US L

LSL

USL

30 24

25 19

Frequency

20

17

15

12

11

9

10

6 5

3

2

0 1 .7 7 6 1 .8 6 8 1 .9 6

2 .0 5 2 2 . 1 4 4 2 . 2 3 6 2 . 3 2 8

2 .4 2

2 .5 1 2

C o n s u m p ti o n ( K W h )

process variability

process variability

Good Process Behavior vShape close to normal curve vMean at target value vSpread within Specification limits v

v

v v

vCp is greater than 1.67 and Cpk is greater than 1.33 v

SCATTER DIAGRAM

What: To study the possible relationship between two variables.

Why:

Diagram make it clear whether a

relationship exists, and shows the strength of relationship.

When:To test a theory that the 2 variables are related.

Examples:



vCutting speed and tool life vBreakdown and equipment age vTemperature & lipstick hardness vTemperature and percent foam in soft drinks vHardness and tensile strength

Different Scatter diagram Patterns

Scatter Diagram on Conveyor Speed vs. Severed Length

1050

Severed Length (mm)

1045 1040 1035 1030 1025 1020 1015 1010 1005 1000 5

5.5

6

6.5

7

7.5

Conveyor Speed (cm/sec)

8

8.5

9

Uses: vControl Purpose vReplacing a destructive test by a non-destructive test vStudy of Cause & Effect relationship vProcess Optimization v •

Process Mapping

About This Module… Process Mapping is a tool used to: ◆Clearly define processes ◆ ◆Identify areas where data

collection should take

place ◆ ◆Visualize

activities involved in a process at the early stages of project development

Six Sigma, A Quest for Process Perfection Attack Variation and Meet Goals

\DataFile\ProcessT.ppt

What We Will Learn … 1.The importance of process maps and the character of the product and process parameters. 2.The when, why and where to use process maps. 3. 4.The x’s & y’s and X’s & Y’s and Y=f(x,X). 5. 6.What to measure and control. 7. 8.The need for process maps prior to FMEA’s, Gage Studies, DOE’s and SPC. 9. 10.When the process map is completed. 11. 12.How to use the tool for your process.

Extending Extending Flow FlowCharts Chartsto to Process ProcessMapping Mapping

Process Management Basic Process Model

Resources • • • • •

System

Input Input

People Equipment Material Money Time

A

Process Process C

Output Output P

D

Feedback

Cycle Time • Time it takes to complete a process from beginning to end

Question “How does a reduction in cycle time benefit an organization?” 

Fundamentals of Process Mapping AAprocess processmap mapshould shoulddescribe: describe: ◆◆Major Majoractivities/tasks activities/tasks ◆◆Sub Subprocesses processes ◆◆Process Processboundaries boundaries ◆◆Inputs Inputs ◆◆Outputs Outputs ◆◆Process Process&&Product ProductParameters Parameters ◆◆Customers Customers&&Suppliers Suppliers ◆◆Process Processowners owners

AAprocess processmap mapshould shouldbe be reviewed reviewedfrequently frequentlyand andisis never neverdone. done. AAprocess processmap mapshould should document documenthow howthe theprocess process actually actuallyoperates, operates,nothow nothowitit isissupposed supposedto tooperate. operate. (“As (“Asis,” is,”not not“To “ToBe”) Be”) AAprocess processmap mapwill willidentify identify opportunities opportunitiesfor forquality quality improvements. improvements.

Principles of Process Management • Establish ownership. • Verify and describe the purpose of the process. • Define the process, boundaries, and interfaces. • Organize and train the process improvement team.

Principles of Process Management • • • •

Define and document the process. Define points of control. Establish process measurements. Improve process.

Process Mapping Steps 1.IDENTIFY INPUTS AND OUTPUTS –Identify Inputs (raw material, equipment, energy, 6M’s, etc.) –Identify Outputs (measurable/assessable end product parameters) 3.SHOW ALL STEPS –Value adding steps have the following characteristics: uSomething

the customer would be willing to pay for

uTransforms uDone

the product or service

right the first time

–Non value-added steps in the process are presented graphically: uEvaluation uRework uScrap

points

points

points

uInventory

Steps (cont.) 3.SHOW OUTPUTS OF EACH STEP –Show after each process step the characteristics that can impact the following step(s). u

4.SHOW ALL PROCESS PARAMETERS AT EACH STEP –List under each step the parameters that can change a product characteristic at that step (i.e., parameters that can be controlled at that step). u

More Steps 5.CLASSIFY THE PARAMETERS –Classify the process parameters identified (in #4 above) into the following categories: u

N = Noise Factors - Uncontrollable - May be controllable, but are not controlled by decision. C = Controllable factors - Process factors that can be changed to see the effect on product characteristics. S = Standard Operating Procedures - A procedure is used to define and run those factors. Tooling, Fixtures. ✔ CR = Critical Factors - Determined through FMEA, DOE, etc.

Inputs & Outputs High Level Process Map X’s

Y’s

INPUT S

OUTP UTS

PROCESS

Processes Come in Hierarchies Process - Level #1 Step #1

Step #2

Step #3

Process - Level #2 Step #1

Step #2

Step #3

Process - Level #3 Step #1

Step #2

Step #3

Select Selectthe theappropriate appropriateprocess processlevel. level.

Product and Process Parameters STEP OF PROCESS

Inputs

Process Parameters, x’s

Outputs

y = f(x)

Remember the 6 M’s ◆Man

(People)

◆Machine ◆Method

(Equipment)

Product Parameters, y’s

(Procedures) KEY for (x’s) Process Parameters

◆Material ◆Measurement ◆Mother

Nature (Environment)

N C

Noise Parameters Controllable Process Parameters S SOP Parameters CR Critical Parameters

Why List the Parameters? TO REDUCE DEFECTS! ◆The

Defects

x’s and X’s are the sources of variation in your process.

◆Variation

causes defects.

◆The

x’s must be under control to prevent defects.

◆The

root cause of a defect is variation of the x’s!

◆The

y’s and Y’s are the measured results of the process and include the failure modes of the process.

◆Defects

are also outputs of a process step.

What Are We Measuring? Measure the x’s, not the Y’s !

X’s

Inputs _________ ?

x’s

Process Parameters _________ ?

y’s Y’s

Process Step Outputs

_________ ? Process Outputs

_________ ?

We Wecannot cannot control controlwhat what we wedon’t don’t measure! measure!

Is Workmanship an x? Y’s

X’s INPUT S

OUTP UTS

PROCESS Process Parameters, x’s

y = f(x)

WORKMANSHIP ?? OPERATOR ?? ✚ 6 M’s reminders: ◆Man

(People)

◆Machine ◆Method

(Equipment)

(Procedures)

◆Material ◆Measurement ◆Mother

Nature (Environment)

Product Parameters, y’s ◆DEFECT

FREE OUTPUT

◆DEFECTS

◆

IN PROCESS OUTPUT

What Are the x’s and y’s? Y’s

X’s Inputs 6 M’s reminders: ◆Man

(People)

◆Machine ◆Method

(Equipment)

(Procedures)

◆Material ◆Measurement ◆Mother

Nature (Environment)

Outputs Process Parameters, x’s N N N N C C

KEY for (x’s) Process Parameters N C

Noise Parameters Controllable Process Parameters S SOP Parameters CR Critical Parameters

y = f(x)

C C S S

Product Parameters, y’s

Identifying Product & Process Parameters The following may be helpful to identify process parameters that have a potential effect on the product parameters and process output: ◆Brainstorming ◆Literature

review

◆Operators ◆Work

manuals

Instructions

◆Operator

experience

◆Customer

/ supplier input

◆Engineering ◆Scientific

knowledge

theory

Remember the 6 M’s ◆Man

(People)

◆Machine ◆Method

(Equipment)

(Procedures)

◆Material ◆Measurement ◆Mother

Nature (Environment)

Completeness Checks Inputs

Step of the Process

Outputs

y = f(x)

Process Parameters, x’s Are there y’s for every x in this step? Is there a “good” type of y for every x ? Is there a “bad” type of y for every x ? Are x’s here that impact downstream y’s? Does the map have input of extended team?

Remember the 6 M’s ◆Man KEY for (x’s) Process Parameters N C

Noise Parameters Controllable Process Parameters S SOP Parameters CR Critical Parameters

(People)

◆Machine ◆Method

(Equipment)

(Procedures)

◆Material ◆Measurement ◆Mother

Nature (Environment)

Product Parameters , y’s ◆Good ◆Bad

= Defects ◆Good Rejected = Defect ◆Bad Accepted = Defect ◆Horror Stories: What has happened in the past that caused disasters? ◆Success Stories: What outputs of this step thrilled the customer(s)? ◆Are there x’s for each y in this step? ◆Are upstream x’s changing y’s of this step? How?

Wave Solder Process LOAD IN FIXTURE

INPUT X’s £Boards with components £Solder £Flux £Electricity £Machine Setup

LOAD ON CONVEYOR

❑Masking ✖Operator ✔Board thickness ✔4-Corner support ✔Bd. Spacing in Fixture ✔Bd quantity in fixture ✔Bd. position within fixture Front or rear Side ✔Fixtures/conveyor width ✔Bd Orientation ✚Frame size/Board size ✚Fixture mass. ✚Fixture dimensions ✚Vert. location bd.in fix. ✚Component Orientation ✚Component Density

❑Conveyor speed ✖Rail position over pot ✖Conveyor angle ✔Time req’d in Solder ✚4-Corner Fixture support ✚Conveyor drive smoothness ✚Finger condition ✚Rail Straightness

Bd Orientation Bd Spacing Bd Alignment Bd to Rail Position Critical areas masked

Current Setup: Specifications Flux: Kester 2% Solid FACTOR S.G.: NA RANGE NOMINAL

Pre Heat #1 Temperature 400

FLUX AIR KNIFE

FLUX ✖Pressure ✔Flux Brand ✔Flux Type ✔Thinner ✔Cleanliness of flux ✔Tritration level ✔Stone Type ✔Cleanliness of Stone ✔Height over Stone ✚Temperature ✚Humidity ✚Ambient Temp

Immersion depth Raised Carrier Frame corner Poor wetting ⇒Partial filled holes ⇒Skip Soldering ⇒Bridging ⇒Excessive solder speed ⇒Insufficient solder ⇒Bridging ⇒Cycle Time

TO PREHEAT

❑Pressure of air knife ✖Orientation ✖Distance to board ✖Air Knife used ✔Angle of air knife ✚Temperature

Solder in all holes Solder Bridging Solder Insufficients Fire Qty of Excess Flux

Lead Solderability Amount on Bd. Flux through holes to top side Distribution on Bd. KEY for (x’s) ⇒ Excessive Solder Process Parameters ⇒ Bridging ✚Noise Parameters ⇒ Icicles ✖Controllable Process Parameters ✔SOP Parameters ⇒ Partially filled Holes qCritical Parameters Cleanliness of Board

Pre Heat #2 Pre Heat #3 Solder Emmersion Conveyer Temperature Temperature Temperature Depth Speed 2.75-4.25 445 470 490 1/4" 3.75

Angle N/A

Hot Air Knife Angle 45-65 60

Pressure 12-20 17PSI

Wave Solder Process (cont.) PREHEA T #1

PREHEA T #2

❑Temp - Zone 2 ❑Temp -Zone 1 ✖Temp - Zone 1 ✖Temp - Zone 2 ✖Temp -Zone 3 ✖Temp - Zone 3 ✖Time in Preheat 2 ✖Time in Preheat 1 ✖Resp time of heater ✖Resp time of heater ✚Stability of temp ✚Stability of temp ✚Dist to board ✚Distance to board ✚Temp distribution ✚Temp distribution ✚Fixture warp ✚Fixture warp ✚Rail warp ✚Rail warp

Board Temp Flux Condition Flux Activated Flux Solvent drive off Thermal Shock ⇒ Board Warping Excess Heat ⇒ Excess Solder ⇒ Poor Fillets ⇒ Excess flow thru Inadequate Heat ⇒ Solder splatter ⇒ Trapped Gas ⇒ Solder Bridges ⇒ Poor flow thru (plated thru holes)

PREHEA T #3 ❑Temp - Zone 3 ✖Temp - Zone 1 ✖Temp - Zone 2 ✖Time in Preheat 3 ✖Response time of heater ✚Stability of temp ✚Distance to board ✚Temp. Distribution ✚Fixture warp ✚Rail warp

Board Temp Flux Condition Flux Activated Flux Solvent drive off Thermal Shock ⇒ Board Warping Excess Heat ⇒ Excess Solder ⇒ Poor Fillets ⇒ Excess flow thru Inadequate Heat ⇒ Solder splatter ⇒ Trapped Gas ⇒ Solder Bridges ⇒ Poor flow thru (plated thru holes)

HOT AIR KNIFE

SOLDER POT ❑Solder Temp ✖Ht of Pot/Position ✖Solder Pot Angle ✖Exit Point ✖Amount of dross ✔Solder Pump Speed ✔Solder Height ✔Solder Pump Pressure ✔Choke bar setting/adj ✔Solder contact ✔Solder type ✔Solder tin content ✔Solder Contam ✔Baffle qual, hole wear, bent condition, clean ✔Board Deflection

Board Temp Flux Condition Flux Activated Flux Solvent drive off Thermal Shock ⇒ Board Warping Excess Heat ⇒ Excess Solder ⇒ Poor Fillets ⇒ Excess flow thru Inadequate Heat ⇒ Solder splatter ⇒ Trapped Gas ⇒ Solder Bridges ⇒ Poor flow thru (plated thru holes)

✖Position ✖Dist to board ✔Temp ✔Angle ✔Air Pressure ✚Temp Dist .

Solder Distribution Coverage on board Solder Appearance Solder joint Quality

KEY for (x’s) Process Parameters ✚Noise Parameters ✖Controllable Process Parameters ✔SOP Parameters qCritical Parameters

EXIT WAVE SOLDER ✖Workmanship Stds ✖Samples ✖Lighting ✖Magnification ✖Prod/Dmnd/Sch ✖Census/Inspection Staffing ✖Inspection Sample . (%) ✚Eyesight ✚Inspector Variation

I N S P E C T I R O NE W O R K

OUTP UT Y’s Boards: •Accepted •Rejected •Scrap

y’s Product Paramenters

Excess Pressure ⇒Solder Bridging ⇒Insufficient solder/Opens Insufficient Pressure ⇒Solder Bridging Temp Too Low ⇒Solder Bridging Temp Too High ⇒Insufficient Solder/Opens ⇒Damage Board Angle Too Steep ⇒Insufficient Solder/Opens Angle Too Shallow ⇒Solder Bridging

Solder Appearance Solder Joint Quality/Defects Open Solder Joints Good Boards Dirty Boards Scrap Boards Hot Boards Damaged Components Lifted Components

The Importance of Questions Noise Parameters: ◆What

are they? ◆Are they impossible or impractical to control? ◆How robust is the system to the noise? ◆

Controllable Parameters: ◆How

are they monitored? ◆How often are they verified? ◆Are optimum target values known? ◆How much variation is there around the target values? ◆How consistent are they? ◆

Standard Operating Procedures: ◆Do

they exist? ◆Are they understood? ◆Are they being followed? ◆Are they current? ◆Is operator certification performed? ◆Is there an audit schedule?

Process Parameter Questions Process Parameters: ◆What

causes variation of the process parameter? ◆How is the process parameter controlled? ◆How often is the parameter out of control? ◆Is there data on the parameter? ◆Which of your process parameters should have control charts on them? ◆When should you place a control chart on a process parameter? ◆Which of your process parameters have control charts on them? ◆How are the control charts used? ◆How do you know which process parameters to monitor? ◆Should we focus on parameters of non value-added steps?

Product Parameter Questions Product Parameters: uWhat uIs

is the goal of the improvement effort?

the product parameter qualitative or quantitative? –An attribute or a variable?

uFor

the product parameters: –Is larger better? –Is nominal best? –Is smaller better? –Is it dynamic in nature?

uIs

the concern for... –Process centering? –Process variation? –Both?

uWhat

is the process baseline for the product parameter? –What is the mean and sigma?

More Product Parameter Questions Product Parameters: ◆Is

the product parameter currently in statistical control? ◆Is the product parameter affected by time? ◆How much of a change in the product parameter do you need/wish to detect? ◆Do you know the expected distribution of the product parameter? ◆Is the measurement system adequate? ◆Are there multiple responses of concern? What are the priorities for optimization? ◆What measurements are taken on product parameters? ◆How do you know which product parameters to monitor? ◆Which product parameters need control charts on them? ◆Which product parameters have control charts on them? ◆How are the control charts used?

Process Map-Flow Charting (Step-by-Step) Identify the inputs and outputs of the process

Document entire flow of the process selected

Identify all value and Non value-added operations

Identify/classify the scope of the process

Identify/classify measurements taken on product & process parameters

Continue to update & classify process map!

Classify/ characterize process parameters into 3 main factors

rNoise factors rStandard operating procedures rControllable process parameters

Develop initial list of process parameters along with current operating conditions

Identify/classify upstream in-process product parameters

Consider Every Process Step 1. What Process work is a process ◆All processes have owners ◆All processes can be described as a verb and noun ◆All processes can be analyzed and improved

feedback

◆All

Requirements

2. What Output 3. What Input

4. Who are Customers 6. Who are Suppliers

feedback

8. Process Controls/Dependencies Procedures/Policies Any written document that controls/impacts a process

5. What Customer

◆Process

owner’s requirements on the supplier ◆Specifications ◆Cost ◆Schedule

◆Specifications

–Function –Reliability –Format ◆Cost ◆Schedule

7. What Supplier Requirements

Training/Education

Equipment/Facilities

Quality Attitudes

◆Performance

◆Space

Personal attitude which is less than the requirement

skills ◆Certifications

required

◆Processing

equipment

Causes of Process Map Failure CONCERN

RESPONSE

Requires extra effort - “We know the process - lets just move forward”

Initial payoff is team understands process -- team members are not working on different set of assumptions. Use experts to help you through the mapping process

The process appears straight forward - then becomes difficult as you realize you do not understand process as well as you thought

If necessary, adjust process boundaries -- initiate another improvement team

The process map just seems to grow and grow and grow

Think about approaching the problem hierarchically

Process Mapping Summary What Whatisisthe thetool? tool? ◆◆Graphical method to illustrate Graphical method to illustrate the thedetails detailsofofaaprocess process ◆◆

What Whatwill willthe thetool toolidentify/show? identify/show? ◆◆All process steps, value-added All process steps, value-added &&non nonvalue-added value-added ) ◆◆Input Inputparameters parameters(X (Xi,in i,in ) ◆◆End Endproduct productparameters parameters(Y (Yi)) i

◆◆In-process parameters (x’s & In-process parameters (x’s &

y’s) y’s) ◆◆Characterization of all Characterization of all parameters parameters ◆◆Defect/data collection points Defect/data collection points ◆◆Steps needing FMEA’s Steps needing FMEA’s ◆◆Sources of variation identified Sources of variation identified

When Whendo doyou youapply applythis thistool? tool? ◆◆Always: to fully understand Always: to fully understand process process&&process processflow flow ◆◆Find where/when/how defects Find where/when/how defects are arebeing beingcreated created ◆◆Define elements of cycle time Define elements of cycle time ◆ ◆

What Whatresults resultscan canyou youexpect? expect? ◆◆Systems needing MSE’s Systems needing MSE’s ◆◆List of Factors for DOE’s List of Factors for DOE’s ◆◆Find the hidden factory Find the hidden factory ◆◆Opportunities for process Opportunities for process step stepelimination elimination(i.e. (i.e.flow flow improvement) improvement) ◆◆Ways to re-layout the process Ways to re-layout the process ◆◆Sources of variation reduced Sources of variation reduced

Map Your Process For the next session: • Map and characterize a critical part of your process. • Identify: – The Inputs (X’s) – The Outputs (Y’s) – The Process Parameters (x’s) – The Product Parameters (y’s) – The process owner, supplier, & customer – Classify the parameters at each step – The next step to reduce defects in your process 

What We Have Learned … 1.The importance of process maps and the character of the product and process parameters. 2.The when, why and where to use process maps. 3. 4.The x’s & y’s and X’s & Y’s and Y=f(x,X). 5. 6.What to measure and control. 7. 8.The need for process maps prior to FMEA’s, Gage Studies, DOE’s and SPC. 9. 10.When the process map is completed. 11. 12.How to use the tool for your process.

Extending Extending Flow FlowCharts Chartsto to Process ProcessMapping Mapping

Failure Modes and Effects Analysis FMEA

About This Module… Failure Modes and Effects Analysis

An FMEA is a systematic method for identifying, analyzing, prioritizing and documenting potential failure modes, their effects on system, product, process performance and the possible causes of failure. Six Sigma, A Quest for Process Perfection Meet Goals and Attack Variation

\DataFile\FMEAform.xls \DataFile\CopyFMEA.xls |Datafile|causeeffecte.igx \Datafile\catapultflow.igx \Datafile\catapultC&E.igx

What We Will Learn… Failure Modes and Effects Analysis 1. As a Team, how to construct an FMEA and associated Action Plan 2. How the FMEA process ties to process mapping 3. The relationship between Failure Mode, Cause and Effect 4. The different types of FMEAs Ü

Sample FMEA S Failure E Effects V Causes Must redo copy 6 Paper Jam Must redo copy Must redo copy

Must redo copy Must redo copy Must redo copy Must redo copy Must redo copy

O D R C E P C Controls T N

Action Recommended

Periodic Maint. 7 294 Periodic preventive maintence Place sign over copier outlining Existing standard size enlarge/reduce or User notes on reliable mach to clearly indicate 6 misset size 6 copier 5 180 standard reduce/enlarge User Existing misset notes on Place sign to encourage user to 6 control 5 copier 4 120 utilize auto settings Used landscape instead of portrait or Tray Place note on ruler re tray 6 vice versa 7 Selection 2 84 selection

6

6

align marking not clear Doc moved when lid closed

7

Resp. Schedule Person Date

Key Opr

3/1

Action Taken PM Schedule created and implemented

Key Opr

2/20

Key Opr

Actual Compl. p p p Date S O D

p r p n

R i Risk s X k prpn

2/15

6 3 7 126 3 378

Place sign over mach

2/15

6 3 2

36 1

36

2/20

Place sign over mach

2/15

6 2 2

24 1

24

Key Opr

1/20

Placed Note

1/15

6 2 1

12 1

12

Use Auto Feeder / Enlarge marks for 8.5 " paper on 4 align ruler 3 72 ruler Key Opr

1/15

Enlarged marks

1/14

6 2 1

12 1

12

Use Auto Place sign over copier re Feeder / "Ensure align prior to copying or 5 align ruler 2 60 use auto Feeder" Key Opr

1/15

Displayed Sign

1/14

6 1 1

User selected wrong tray 3

Auto select 6 function 3 54 Periodic Cleaning 6 Dirty Glass 6 SOP 1 36

Place sign over copier to encourage user to use auto tray select

Key Opr

2/25

Place sign over mach

2/20

6 2 3

Place cleaning material near copier

Maint.

1/15

Placed Cleaning Matl

1/15

6 1 1

Datafile/CopyFMEA.xls

6

1

6

36 1

36

6

1

6

Why Use FMEAs? What is an FMEA? Identify critical product characteristics and process variables Prioritize product and process deficiencies in support of downstream improvement actions Help focus on prevention of product and process problems

Benefits of FMEA’s What is an FMEA?

F u Helps increase customer satisfaction. M u Reduces product development timing and cost. E u Reduces the amount of rework, repair and scrap. u Documents and tracks actions taken. A u

Improves the quality, reliability and safety of products.

u

Prioritizes deficiencies to focus improvement efforts.

Process and FMEA Hierarchies What is an FMEA? Process - Level #1 Step #1

Step #2

Step #3

FMEA - Level #1

Step #3

FMEA - Level #2

Process - Level #2 Step #1

Step #2

Process - Level #3 Step #1

Step #2

Step #3

FMEA - Level #3

Process FMEA Steps What is an FMEA? uSteps

Completed Prior to FMEA:

–Charter Team –Develop and Characterize Process Map

uFMEA Steps:

1.Identify “Heavy Hitter” Process Step

1. 2.

3. 4. 5. 6. 7. 8. 9. 10.

1.Identify Associated y’s (Product Parameters) 1.Identify Failure Mode 1.Identify Failure Effects/Rate Severity 1.Identify Causes/Rate Occurrence 1.Identify Controls (if any)/Rate Detection 1.Calculate RPN 1.Prioritize by RPN Order 1.Determine Actions/Plan 1.Recalculate RPN Based on Plan 1.Take Action

FMEA Form What is an FMEA?

Header Accessible from View Header/Footer in Excel

Workbook in Excel

\DataFile\FMEAForm.xls

Cause -Failure Mode -Effect Continuum What is an FMEA?

Effect (y’s) Cause (x’s)

Failure Mode

The Cause and Effect Diagram Example What is an FMEA? Admin/Service Example Measurements

Materials

First produced in 1950 by Professor Kaoru Ishikawa Also called the: uIshikawa Diagram uFish Bone Diagram

Manpower

Failure Mode (Defect)

Mother Nature

Methods

Machines

Failur e Effec t

Developed to represent the relationship between some “effect and all possible “causes” influencing it. Create using Igrafx:

The Cause and Effect Diagram Example Cause and Effects Diagram Measurement Manpower Inadequate training

Material

Reproducibility

Repeatability

Late

Linearity

Wrong quantity Lack of experience

Stability Calibration

Defective

Distractions

Defects Too hot

Vague

Too humid Not maintained Too cold

Inadequate capability

Out of date Complex

Mother nature Machines

Methods

Datafile/Causeeffecte.igx

Copy Machine Example What is an FMEA?

• Our process is copying documents on a Xerox model XC1045 copy machine. • First we will construct a process map • Then we will construct a cause and effect diagram • Finally we will complete an FMEA

Process: Making A Copy What is an FMEA?

Make Copies

Place Document in Copier

Set number of copies

N Hinges N Glass clean

C Copies required Cr Number button

Document set correctly Glass clean

Legend C Controllable Cr Critical N Noise P Procedure x Input

Enter size required C Size desired Cr Size button

Number of copies selected correctly

Set light/dark settings

Select paper source

C Darkness desired

Size selected correctly

Press button

C Size desired x Paper

Darkness set directly

Retrieve copies

Cr Button

Correct paper tray selected

Copies

Copies Right number Right contrast Right orientation Right size Right paper

Step 1: Identify “Heavy Hitter” Process Step The FMEA Process uFrom

the Process Map, identify the process step with the most likelihood of having failure modes with significant effects

defect data and/or team knowledge about failure F modes when selecting process steps impact to the business? (COPQ, cycle time, fill M uSignificant rate, ...) E uUse a Cause and Effect Diagram to capture brainstorming results. A uAfter completing FMEA Steps #2-7 for all failure modes uUse

associated with this process step, return to this step and select the next most likely “Heavy Hitter” process step

uNot

all process steps will need to be analyzed by the FMEA

Step 2: Identify Associated y’s The FMEA Process uFrom

the Process Map, identify the y’s that are associated with the process step being investigated

uAs

the y’s are the indications of a successful completion of the process step, they are crucial as a basis for determining failure modes

Step 3: Identify Failure Mode The FMEA Process • Brainstorm failure modes for the selected process step : – Identify the ways in which the process could fail to generate each of the expected “y’s” • Eliminate “duplicates” from brainstorm list • Are the failure modes from the same level of the process? • Are the failure modes specific? • Are the failure modes the most likely? • Do the failure modes provide good coverage of the process step? • Have all y’s been considered?

Step 4: Identify Failure Effect/Rate Severity The FMEA Process uPick

the most likely failure mode and brainstorm the most important Effects: –FAILURE EFFECTS are the outcome of the occurrence of the failure modeon the process. The impact on the customer --- What does the customer experience as a result of the Failure Mode?

uIdentify

each effect as being “Attribute” or “Variable”

uSeverity

doesn’t change unless the design changes.

Step 5: Identify Causes/Rate Occurrence The FMEA Process uIdentify the most likely causes for each failure mode using a Cause and Effect Diagram: –CAUSES are the conditions that bring about the Failure Mode uTransfer

the resulting information to the FMEA form

uAssign

an occurrence value (1-10) to the likelihood that each particular cause will happen and result in the failure mode

uThe

occurrence score for each cause should be related to the likelihood of that cause resulting in the failure mode and producing the specific associated effect

Organize Brainstorming Ideas The FMEA Process Measurement Wrong Size Selected

Materials

Manpower Selected wrong orientation

Wrong Paper Size

Copy Misaligned Too Humid

Mother Nature

Document Moved When Lid was Closed

Method

Alignment Marking Unclear

Machine

What would you add?

Step 6: Identify Controls/Rate Detection The FMEA Process uIdentify

the current mechanisms in place which prevent the causefrom occurring, or detect it before the product reaches the customer. Some examples of controls are SPC, training, maintenance, inspection, SOP etc.

uAssign

a detection value (1-10) based on an assessment of the likelihood that the current control mechanisms will detect the cause of the failure mode before it reaches the customer.

uDon’t

agonize over detectability.

Step 7: Calculate Risk Priority Number The FMEA Process The product of the estimates of severity occurrence and detection. The RPN provides a relative priority for taking action the bigger the RPN, the more important to address.

RPN = SEVERITY x OCCURRENCE x DETECTION

Steps 8 and 9 The FMEA Process 8: Prioritize by RPN Order Use the “Sort” command in Excel to order the spreadsheet in descending order of Risk Priority Number (RPN). 9: Determine Actions/Plan Based on the causes found, determine actions that will minimize the effect of each cause, in priority order.

Steps 10 and 11 The FMEA Process 10: Recalculate RPN Based on Plan uAssuming the actions are carried out successfully, reassign severity, occurrence and detectability. u

uPlace

these new ratings in the “predicted” columns (ps, po & pd).

u

uAssign

a rating from 1 to 5 for each action that will show the “risk” associated with each action (5 being the greatest risk). Place the rating in the “risk” column.

11: Take Action uBased on the risk mitigation column (Risk * prpn), take the actions indicated or reassign actions. Then…. u

uComplete

the actions indicated by the times stated!

The FMEA Process Steps 1-11:

Step 2 ID y’s

Step 1 ID Process Steps S Failure E Effects V Causes Must redo copy 6 Paper Jam Must redo copy Must redo copy

Must redo copy Must redo copy

Step 6

Step 4 O D R C E P C Controls T N

7

Step 9

FMEA Action Recommended

Periodic Maint. 7 294

Periodic preventive maintence Place sign over copier outlining Existing standard size enlarge/reduce or User notes on reliable mach to clearly indicate 6 misset size 6 copier 5 180 standard reduce/enlarge User Existing misset notes on Place sign to encourage user to 6 control 5 copier 4 120 utilize auto settings Used landscape instead of portrait or Tray Place note on ruler re tray 6 vice versa 7 Selection 2 84 selection

align marking 6 not clear 4 Doc Must moved Step redo 3 when lid copy 6 closed ID Failure Modes 5

\DataFile\CopyFMEA.xls Step 11

Resp. Person

Schedule Date

Key Opr

3/1

Action Taken PM Schedule created and implemented

Key Opr

2/20

Key Opr

Actual Compl. p p p Date S O D

p r p n

R i Risk s X k prpn

2/15

6 3 7 126 3 378

Place sign over mach

2/15

6 3 2

36 1

36

2/20

Place sign over mach

2/15

6 2 2

24 1

24

Key Opr

1/20

Placed Note

1/15

6 2 1

12 1

12

Use Auto Feeder / Enlarge marks for 8.5 " paper on align ruler 3 72 ruler Key Opr

1/15

Enlarged marks

1/14

6 2 1

12 1

12

Use Auto Place sign over copier re Step Feeder / "EnsureStep align prior 7 to©ing or align use auto Feeder" 5 ruler 2 60

8

Step 10 Key Opr

1/15

Displayed Sign

1/14

6 1 1

6

1

6

Process FMEA Types of FMEA • Helps analyze manufacturing and assembly processes to reduce the occurrence and F improve detection of defects. • Assists in the development of process control M plans. E • Establishes a priority for improvement activities. • Documents the rationale behind process A changes and helps guide future process improvement plans. • IS PROACTIVE! Should be started when new processes are designed or when old processes are changed.

Process FMEA Scoring Definition Types of FMEA Score 10 9 8 7 6 5 4 3 2 1

SEVERITY CRITERIA Hazardous Without Warning Hazardous With Warning Very High High Moderate Low Very Low Minor Very Minor None

OCCURRENCE 1 in 2 Very High 1 in 3 Very High 1 in 8 High 1 in 20 High 1 in 80 Moderate 1 1 in in 400 Moderate 2,000 Moderate 1 in 15,000 Low 1 in 150,000 Low £1 in 1,500,00 Remote

DETECTION Absolute Uncertainty Very Remote Remote Very Low Low Moderate Moderately High High Very High Almost Certain

Note: When completing a Process FMEA, first assume the material is good and the process is bad. Then assume that the process is good and the material is bad. Lastly, review the process for safety considerations.

Design/Product FMEA Types of FMEA

F M E A

• Helps to identify potential product failure modes early in the product development cycle. • Increases the likelihood that all potential failure modes and their effects on assemblies will be considered. • Assists in evaluating product design requirements and test methods. • Establishes a priority for design improvement. • Documents the rationale behind design changes and helps guide future development projects. • IS PROACTIVE! Should be done when new products are designed or existing products are changed.

Defect FMEA Types of FMEA

• F • M• •

E A

Helps identify the root causes of defects. Establishes a priority for improvement activities. Documents plan of action. Provides methodology to battle initial ground swell of defects. • Focuses effort on defects with highest $ impact. • IS NOT PROACTIVE!

Scoring Criteria Types of FMEA Score 10 9 8 7 6

SEVERITY CRITERIA

Use actual defect quantities

OCCURRENCE

DETECTION

Hazardous Without Warning Hazardous With Warning Very High High Moderate

Very High Very High High High Moderate

Absolute Uncertainty Very Remote Remote Very Low Low

5

Low

Moderate

Moderate

4 3 2 1

Very Low Minor Very Minor None

Moderate Low Low Remote

Moderately High High Very High Almost Certain

Note: To change header information, click on "View" then "Header". RISK: Optional field used to reflect the probability of completing actions.

The Catapult FMEA Exercise Analyze the Catapult process using the FMEA tool. (Remember we want to get the “most bang for the buck”.)

• • • • • •

Break into the Catapult teams We have already constructed a process map First, we will construct a cause and effect diagram Then we will complete at least two failure modes for the most critical step(s) of our process Appoint a spokesman for your team to debrief the class on your progress, questions, etc. Complete the FMEA (FMEAform.xls) for the Catapult process before the third session (We will use this information for our DOE competition)

25 minutes!

Catapult Process Map FMEA Exercise Start

Assemble Catapult Pins (2) Arm Rubber Band Ball

Clamp Tape Measure Tape

Arm moves smoothly

Pull Arm to Proper Angle

Positions Designated

Feasible settings

Measure distance

Tape Measure Observers positioned properly

Operator Lateral movement Correct angle

Set Catapult Pins

Plan or Prediction equation Computer

Aligned with tape ± 3 inches

Shoot

Operator Consistency No Parallax

Select Catapult Settings

Secure to table

Ball flys straight

Correct settings

Record distance

Stop

Recorder Computer

Accurate measurement ± 2 inches

Correct distance recorded

Datafile/Catapultflow.igx

Complete the Diagram Below FMEA Exercise Men Method Calculation procedure

Material Release consistency Rubber Band Ball

Angle measurement

Distance Air Conditioner

Arm moves freely

Repeatability Reproducibility

Mother nature Machine

Measure

Datafile/CatapultC&E.IGX

When To Update an FMEA? FMEA Summary An FMEA should be updated whenever a change is being considered to a product’s: u

design

u

application

u

environment

u

material

u

product’s manufacturing or assembly process

Summary of Product/Process FMEA’s FMEA Summary u What is the tool?

uWhen

–Spreadsheet –

–When evaluating product for robustness (functionality, produceability, reliability) –During early stages of defect reduction efforts to identify causes –When identifying key process/product parameters and evaluating methods for controlling them –

uWhat

will the tool identify/show? –All product/process failure modes, related effects, causes, & methods of controlling them –Risk Priority Number (RPN) for action based on failure severity, probability of occurrence and detection capability –Actions/plans to reduce elements of RPN

do you apply this tool?

uWhat

results can you expect? –Learn to identify critical product/ process parameters –Achieve consensus on solutions and methods of implementation –Detailed product/process understanding

Keys to Success FMEA Summary uIdentify purpose...BE SPECIFIC! u uUnderstand effects...INVOLVE CUSTOMERS & SUPPLIERS! u uLink to the process map. u uUse to prioritize efforts, allocate resources. u uUse as a risk assessment/prioritization tool based on predicted u uUse to build consensus on prioritization. u uEncourage creativity...TEAMWORK! u uPLAN! u uASK QUESTIONS!

impact.

Process FMEA Steps What is an FMEA? uSteps

Completed Prior to FMEA:

–Charter Team –Develop and Characterize Process Map

uFMEA Steps:

1.Identify “Heavy Hitter” Process Step

1. 2.

3. 4. 5. 6. 7. 8. 9. 10.

1.Identify Associated y’s (Product Parameters) 1.Identify Failure Mode 1.Identify Failure Effects/Rate Severity 1.Identify Causes/Rate Occurrence 1.Identify Controls (if any)/Rate Detection 1.Calculate RPN 1.Prioritize by RPN Order 1.Determine Actions/Plan 1.Recalculate RPN Based on Plan 1.Take Action

FMEA Appendix Key Definitions for FMEA Severity is an assessment of how serious the effect of the potential failure mode is on the customer. The customer in this case could be the next operation, subsequent operations, or the end user.

Occurrence is an assessment of the likelihood that a particular cause will happen and result in the failure mode.

Detection is an assessment of the likelihood that the current controls (design and process) will detect the cause of the failure mode, should it occur, thus preventing it from reaching your customer. The customer in this case could be the next operation, subsequent operations, or the end user.

Current Controls (for both design and process) are the mechanisms which prevent the cause of the failure mode from occurring, or detect the failure mode, should it occur, before the product reaches your “customer.” For example, current controls include SPC, inspections, written procedures, training, preventive maintenance and all other activities that ensure a smooth running process.

Critical Characteristics are those items which affect customer safety and/or could result in non-

compliance to regulations and thus require controls to ensure 100% compliance. These are usually process“settings” such as temperature, time, speed, etc.

Significant Characteristics are those items which require SPC and quality planning to ensure acceptable levels of capability.

FMEA Appendix Terminology A. B. C. D. E. F. G. H. I. J. K. L. M. N. O. P. Q. R. S. T.

Process or Product Name – Description of Process or Product being analyzed. Responsible – Name of Process Owner. Prepared By - Name of Agent coordinating FMEA study. FMEA Date – Dates of Initial and subsequent FMEA Revisions. Process Step/Part Number – Description of individual item being analyzed. Potential Failure Mode – Description of how the process could potentially fail to meet the process requirements and/or design intent, i.e. a description of a non-conformance at that Potential Failure Effects – Description of the effects of the Failure Mode upon the customer, i.e. what the next user of the process or product would experience or notice. SEV (Severity) – An assessment of the seriousness of the effect of the potential failure mode Potential Causes – Description of how the failure could occur, described in terms of something OCC (Occurrence) – Description of how frequently the specific failure cause is expected to Current Controls – Description of process controls that either prevent, to the extent possible, DET (Detection) – An assessment of the probability that the current controls will detect the potential cause, or the subsequent failure mode. RPN (Risk Priority Number) – The product of the Severity, Occurrence, and Detection Rankings i.e., RPN = SEV * OCC * DET. Actions Recommended – Actions to reduce any or all of the Occurrence, Severity or Detection rankings. Responsibility – Person or group responsible for the Recommended Action. Actions Taken – Brief description of actual action and effective date. New SEVERITY Rating after corrective action. New OCCURENCE Rating after corrective action. New DETECTION Rating after corrective action. Resulting new RPN after corrective action.

Introduction to Process Capability

About this Module • Process capability enables the prediction of the ability of any process to produce products and services that meet their desired specifications. • This module focuses on typical manufacturing processes. Transactional and other manufacturing processes are not discussed here. • The principles of process capability will be introduced and Minitab will be used to calculate process capabilities. 

Learning Objectives At the conclusion of this module participants will be able to: 

1.Recognize the value of and uses for process capability. 2.Calculate and explain the capability of processes whose output is normally distributed. 3.Predict the probability that the output of a process will be within its specification limits.

We Live in a Statistical World Basic Statistics

• Statistics have a pervasive influence on our lives – Every day there is another poll – Sampling is being used to perform many aspects of the census – All major economic indicators are based on samples – TV ratings are based on samples – Statistics determine insurance rates

• Quantum physics has demonstrated that probability determines the structure and

Types of Statistics Definitions Descriptive statistics is the process of describing the information we have. We summarize information from a sample or population give a clear understanding, or description, of the data. Inferential statistics is the process of using information from a smaller set of data (sample) to reach conclusions or inferences about a larger group (population). Usually, we have only sample information, not the entire population, and must infer understanding of the population based on our sample. We want these conclusions to be mathematically correct.

Data Types Definitions Attribute Yes - no Good - bad Accept - reject Discrete Multiples of whole units Can not be meaningfully divided Count or classification Continuous Can be meaningfully divided into finer and finer increments of precision weight, length, voltage, time

Measures of Central Tendency - Location Definitions Mean - the sum of all members divided by the population size (average) j

µ = Population mean= X = Sample mean

∑ X , X , X ... X 1

1

2

3

j

N

Mode - the most frequently occurring or most likely value Median - the fiftieth percentile (half the values are above and half below the median)

Population Versus Sample Definitions Population Size N n Location Average (Mean) µ Dispersion: Variation Variance σ Std dev σ Range

2

Samples x

s2 s R = XHi -XLo

Statistics infer information about the parameters of the population.

Quantifying Dispersion - Spread Definitions x1

X

xn x2

We could add the differences between each value x and the average of the values x however that would always yield zero. Therefore we square the difference between each x and x, to eliminate the negatives and emphasize the2 outliers, then take the average of the results. σThis is defined as the variance or σ 2. Obviously, σ =

Attributes of the Histogram - Location & Spread Definitions

n

Number of Cases = 50 Mean & Median = 75 Standard Deviation = 8.3299 Range = 40 Variance = 69.388 Minimum = 55 Maximum = 95

14 12

F r 10 e q 8 u e 6 n c 4 y

i=1

n− 1

n

X i X=µ ˆ=∑ i=1 n Variable X measurements:

2

0 50

s=σ ˆ=

2 ( X − X ) ∑ i

60

70

80

90

Values of X

100

110

75 85 60 80 70 80 65 75 70 75

80 70 80 75 75 55 70 85 75 95

75 70 80 75 75 70 80 90 75 90

65 85 80 70 75 70 75 80 80 60

70 70 65 85 85 85 65 65 80 65

Measures of Variability - Variance = Sigma Squared Definitions uSigma

Squared is a measure of dispersion of the population about the mean uVariances are not in the units of interest; standard deviations are in the units of interest uVariances are additive; standard deviations are not additive...

…so σ

2

1

but, σ

+σ

1

+σ

2

+ σ

3

2

+ σ

3

2

2

is OK,

is NOT OK

Measures of Variability – S. D. = Sigma Definitions Standard Deviation is a measure of dispersion of the population about the mean σ = the units of interest and is population standard deviation µ = population mean N = total population s = estimate of standard deviation 2 2 2 µ − + − + − µ n = sample size X1 µ X2 X3 ... X N −µ σ (X )= N

(

σˆ = s =

(X

) (

1

−X

) + (X

) (

2

2

−X

) + (X

) (

2

n-1

3

−X

) ...(X 2

n

−X

)

2

)

2

Normal Distribution Each curve shown here has: u An area of one u A mean of zero u A standard deviation of σ

Therefore, the same % of the population is under each of the curves for n σ about the mean.

Quantifying the Normal Distribution Definitions

µ −3σ µ +3σ

µ −2σ

µ −1σ 68.26% 95.46% 99.73%

µ

µ +1σ

µ +2σ

Probability Density Function – Standard Normal Distribution Definitions Area under the curve = 1 σ =1 µ =0 Any normal distribution can be converted to a standard normal distribution

The formula for the probability density function is − z2

1 f ( z) = e 2π

2

The Standard Normal Transform Definitions

X −µ Z= σ Permits conversion of any data point (X) into a Z value. This value allows us to look up the percentage of the population that is above and below the data point.

Sample Questions……… 

Q.

A new iron ore mine is discovered. 10 Kg ore is collected from each of 20 spots.

1.

b. This procedure is called as __________ . c. Average is calculated from iron content of each of 20

spots. This value is called as ________________ d. If we calculate average, range and standard deviation from the iron content values of each lot, this data is called as ________________ . e. Predictions are made regarding average iron content of the mine, total iron that can be extracted, impurities present etc. the analysis is called as ___________ . f. The above calculations will give answers which will be100% correct. True / False

Answers a.The procedure is called as SAMPLING. b. c.The value is called as STATISTIC. d. e.The values are called as STATISTICS. f. g.The analysis is called as STATISTICAL ANALYSIS. h. i.The Statement is FALSE.

Basic Principle • All measures of process capability are based on the concept of calculating the number of standard deviations between the process center and the specification limits. • A Six Sigma process has six units of standard deviation between the process center and both specification limits.

LSL

USL

Visualizing Process Capability

Process width Specification width

Quantifying Process Capability If we assume the process is centered on the target and does not shift or drift the yields would be.

Yield of a one sigma process 0.683

LS L

US L

Process Sigma

Yield

1 2 3 4 5 6

0.6826895 0.9544997 0.9973002 0.9999367 0.9999994 1

The Standard Deviation 1 Sigma - 68% 2 Sigma - 95% 3 Sigma - 99.73 %

µ

σ =

1σ Upper Specification Limit (USL) Target Specification (T) Lower Specification Limit (LSL) Mean of the distribution (µ ) Standard Deviation of the distribution (σ )

Σ (X – X)2 n

p(d)

T

USL

3σ

Calculating Yield We know that Z is the number of units of standard deviation on a standard normal curve which has a mean of zero and a standard deviation of one. We also know any normal distribution can be converted to the standard normal using the Z equation.

x −µ Z = σ

X −X Z = σˆ

If the specification limits are substituted for x we can determine the number of units of standard deviation between the process center and the specification limits on the standard normal curve. Then we can use the tables to look up the probability a value will be less than that number.

In most cases we do not know µ or σ so we substitute the sample statistics for the population parameters as shown.

Calculating Yield The mean time taken for completing an operation is 500 hrs.



and this is normally distributed with a standard deviation of 100 hrs. 1. What is the probability that an operator taken at random will take between 500 to 650 hrs to complete the operation? 2. What is the probability that he will take > 700 hrs? 

Express in graphical form also.

Calculating Yield – Example 1. What is the probability that an operator taken at random will take between 500 to 650 hrs to complete the operation? 

Z = 

x −µ σ

= (650 – 500) / 100 = 1.5

Looking up z table, the corresponding value under the



Standard Normal Distribution is 0.4332. i.e. 43%.





Calculating Yield – Example 2. What is the probability that he will take > 700 hrs? 3.

x − µ= (700 – 500) / 100 = 2 σ Looking up z table, the corresponding value under the 

Z =

Standard Normal Distribution is 0.4772.



Thus the probability of an operator taking more than 700 hrs



is (0.5 – 0.4772) = 0.0228, i.e. slightly over 2%.







Calculating Yield Example Consider a process that has the following specification limits: Lower Specification Limit (LSL) of -1 and a Upper Specification Limit of 1. Data indicates the process is centered on 0 with a standard deviation of 1. What is the yield? Using tables or software to look up the area under the curve when Z=1 we USL-X ZUSL= find .8413. This means that 84.13% of ˆ σ the product has a value less than the 1-0 upper specification limit. ZUSL= =1 1 Again using tables or software to look LSL-X ZLSL= ˆ σ -1-0 ZLSL= = −1 1

up the area under the curve when Z=-1 we find .1586. This means that 15.86% of the product has a value less than the lower specification limit.

What if the Process Shifts? Generally speaking, processes have been observed to shift and/or drift 1.5 standard deviations over time. How would that effect the yield of a one sigma process? 

LSL

-4

-3

-2

-1

USL

0

1

Calculating Shifted Process Yield Using tables or software to look up the USL-X ZUSL= area under the curve when Z=-.5 we ˆ σ find .3085 1-0-1.5 ZUSL= = −.5 1 LSL-X Again using tables or software to look ZLSL = ˆ σ up the area under the curve when Z=2.5 we find .0062. -1-0-1.5 ZLSL = = −2.5 1 Subtracting the two we obtain .3023

Using These Principles • Process capability and process capability indices are unambiguous and will be addressed first. • Process sigma is somewhat ambiguous and will be addressed second.

Process Capability Terms Measures of the ability of a process to produce compliant products/services: Cp - Short-term process capability uFor

a limited period of time (not including shifts and drifts)

uDoes uAlso

not consider process centering

known as process entitlement

Cpk - Short-term process capability index uFor

a limited period of time (not including shifts and drifts)

uDoes

consider process centering

Pp - Long-term process capability uFor

an extended period of time (including shifts and drifts)

uDoes

not consider process centering

Ppk - Long-term process capability index uFor

an extended period of time (including shifts and drifts) See formulae on next page. uDoes consider process centering

Capability Formulae USL-LSL Specification Width (s) Cp = Short-Term Process Width = µ ST 6σ

Pp = Cpk = Ppk =

Specification Width (s) = Long-Term Process Width Lesser of: Lesser of:

USL-X µ ST 3σ

or

USL-X µ LT 3σ

or

USL-LSL µ LT 6σ X-LSL µ 3σ ST

X-LSL µ 3σ LT

Using Minitab The data is continuous so test for normality Stat>Basic Statistics>Normality Test

The Normality Test Probability Plot of Caps Normal 99.99 99

Percent

95

Mean 1.000 StDev 0.001986 N 750 AD 0.619 P-Value 0.107

80 50 20 5 1 0.01 0.992 0.994 0.996 0.998 1.000 1.002 1.004 1.006 1.008 Caps

Worksheet: Bottle Caps.MTW

The P value is > .05 therefore do not reject the assumption of normality.

Using Minitab to Calculate Process Capability

Minitab Results Process Capability of Caps LSL

Target

USL

Process Data LSL 0.995 Target 1 USL 1.005 Sample Mean 1.00006 Sample N 750 StDev(Within) 0.00198431 StDev(Overall) 0.00198636

Within Overall Potential (Within) Capability Z.Bench 2.26 Z.LSL 2.55 Z.USL 2.49 Cpk 0.83 Overall Capability Z.Bench Z.LSL Z.USL Ppk Cpm

2.26 2.55 2.48 0.83 0.84

5 0 5 0 5 0 5 0 94 996 997 999 000 002 003 005 9 0. 0. 0. 0. 1. 1. 1. 1. Observed Performance % < LSL 0.40 % > USL 0.67 % Total 1.07

Exp. Within Performance % < LSL 0.54 % > USL 0.64 % Total 1.18

Exp. Overall Performance % < LSL 0.54 % > USL 0.65 % Total 1.19

Worksheet: Bottle Caps.MTW

Let’s examine this in detail

Process Data Process Capability of Caps LSL

Target

USL

Process Data LSL 0.995 Target 1 USL 1.005 Sample Mean 1.00006 Sample N 750 StDev(Within) 0.00198431 StDev(Overall) 0.00198636

Within

ly from the data. The within standard deviation Overall is the pooled standard Potential (Within) Capability Z.Bench 2.26 Z.LSL 2.55 Z.USL 2.49 Cpk 0.83 Overall Capability Z.Bench Z.LSL Z.USL Ppk Cpm

45 60 75 90 05 20 35 50 99 .99 .99 .99 .00 .00 .00 .00 . 0 0 0 0 1 1 1 1 Observed Performance % < LSL 0.40 % > USL 0.67 % Total 1.07

Exp. Within Performance % < LSL 0.54 % > USL 0.64 % Total 1.18

Worksheet: Bottle Caps.MTW

Exp. Overall Performance % < LSL 0.54 % > USL 0.65 % Total 1.19

2.26 2.55 2.48 0.83 0.84

Observed Performance Process Capability of Caps

ent of product that was outside of the upper and lower specification lim Within LSL

Target

USL

Process Data LSL 0.995 Target 1 USL 1.005 Sample Mean 1.00006 Sample N 750 StDev(Within) 0.00198431 StDev(Overall) 0.00198636

Overall Potential (Within) Capability Z.Bench 2.26 Z.LSL 2.55 Z.USL 2.49 Cpk 0.83 Overall Capability Z.Bench Z.LSL Z.USL Ppk Cpm

45 60 75 90 05 20 35 50 99 .99 .99 .99 .00 .00 .00 .00 . 0 0 0 0 1 1 1 1 Observed Performance % < LSL 0.40 % > USL 0.67 % Total 1.07

Exp. Within Performance % < LSL 0.54 % > USL 0.64 % Total 1.18

Worksheet: Bottle Caps.MTW

Exp. Overall Performance % < LSL 0.54 % > USL 0.65 % Total 1.19

2.26 2.55 2.48 0.83 0.84

Expected Within Performance Process Capability of Caps

utside of the upper and lower specification limits on an short term basis. Thi LSL

Target

USL

Process Data LSL 0.995 Target 1 USL 1.005 Sample Mean 1.00006 Sample N 750 StDev(Within) 0.00198431 StDev(Overall) 0.00198636

Within Overall Potential (Within) Capability Z.Bench 2.26 Z.LSL 2.55 Z.USL 2.49 Cpk 0.83 Overall Capability Z.Bench Z.LSL Z.USL Ppk Cpm

45 60 75 90 05 20 35 50 99 .99 .99 .99 .00 .00 .00 .00 . 0 0 0 0 1 1 1 1 Observed Performance % < LSL 0.40 % > USL 0.67 % Total 1.07

Exp. Within Performance % < LSL 0.54 % > USL 0.64 % Total 1.18

Worksheet: Bottle Caps.MTW

Exp. Overall Performance % < LSL 0.54 % > USL 0.65 % Total 1.19

2.26 2.55 2.48 0.83 0.84

Expected Overall Performance

ower specification limits on an long term basis. This projection is based on t Process Capability of Caps

LSL

Target

USL

Process Data LSL 0.995 Target 1 USL 1.005 Sample Mean 1.00006 Sample N 750 StDev(Within) 0.00198431 StDev(Overall) 0.00198636

Within Overall Potential (Within) Capability Z.Bench 2.26 Z.LSL 2.55 Z.USL 2.49 Cpk 0.83 Overall Capability Z.Bench Z.LSL Z.USL Ppk Cpm

45 60 75 90 05 20 35 50 99 .99 .99 .99 .00 .00 .00 .00 . 0 0 0 0 1 1 1 1 Observed Performance % < LSL 0.40 % > USL 0.67 % Total 1.07

Exp. Within Performance % < LSL 0.54 % > USL 0.64 % Total 1.18

Worksheet: Bottle Caps.MTW

Exp. Overall Performance % < LSL 0.54 % > USL 0.65 % Total 1.19

2.26 2.55 2.48 0.83 0.84

Potential Within Capability Process Capability of Caps

rocess mean, the respective specification limits and the within standa ted within yield (.982) left hand tail of a standard normal then looking Within LSL

Target

USL

Process Data LSL 0.995 Target 1 USL 1.005 Sample Mean 1.00006 Sample N 750 StDev(Within) 0.00198431 StDev(Overall) 0.00198636

Overall Potential (Within) Capability Z.Bench 2.26 Z.LSL 2.55 Z.USL 2.49 Cpk 0.83

or Z LSL .

Overall Capability Z.Bench Z.LSL Z.USL Ppk Cpm

2.26 2.55 2.48 0.83 0.84

45 60 75 90 05 20 35 50 99 .99 .99 .99 .00 .00 .00 .00 . 0 0 0 0 1 1 1 1 Observed Performance % < LSL 0.40 % > USL 0.67 % Total 1.07

Exp. Within Performance % < LSL 0.54 % > USL 0.64 % Total 1.18

Worksheet: Bottle Caps.MTW

Exp. Overall Performance % < LSL 0.54 % > USL 0.65 % Total 1.19

Note: Minitab uses within to describe short term variation and overall to describe long term variation.

Overall Capability

Process Capability of Caps process mean, the respective specification limits and the overall stand cted within yield (.981) left hand tail of a standard normal then looking Within LSL

USL

Target

USL

Process Data LSL 0.995 Target 1 USL 1.005 Sample Mean 1.00006 Sample N 750 StDev(Within) 0.00198431 StDev(Overall) 0.00198636

Overall

or Z LSL .

Potential (Within) Capability Z.Bench 2.26 Z.LSL 2.55 Z.USL 2.49 Cpk 0.83 Overall Capability Z.Bench Z.LSL Z.USL Ppk Cpm

5 0 5 0 5 0 5 0 94 996 997 999 000 002 003 005 9 0. 0. 0. 0. 1. 1. 1. 1. Observed Performance % < LSL 0.40 % > USL 0.67 % Total 1.07

Exp. Within Performance % < LSL 0.54 % > USL 0.64 % Total 1.18

Worksheet: Bottle Caps.MTW

Exp. Overall Performance % < LSL 0.54 % > USL 0.65 % Total 1.19

2.26 2.55 2.48 0.83 0.84

Within - Between Process Capability of Caps LSL

Target

USL

Process Data LSL 0.995 Target 1 USL 1.005 Sample Mean 1.00006 Sample N 750 StDev(Within) 0.00198431 StDev(Overall) 0.00198636

Within Overall

e as indicated by the Within and Between lines being very close Potential (Within) Capability Z.Bench 2.26 Z.LSL 2.55 Z.USL 2.49 Cpk 0.83 Overall Capability Z.Bench Z.LSL Z.USL Ppk Cpm

5 0 5 0 5 0 5 0 94 996 997 999 000 002 003 005 9 0. 0. 0. 0. 1. 1. 1. 1. Observed Performance % < LSL 0.40 % > USL 0.67 % Total 1.07

Exp. Within Performance % < LSL 0.54 % > USL 0.64 % Total 1.18

Worksheet: Bottle Caps.MTW

Exp. Overall Performance % < LSL 0.54 % > USL 0.65 % Total 1.19

2.26 2.55 2.48 0.83 0.84

Calculating Cpk and Ppk

Calculating Cpk and Ppk

e process mean, the respective specification limits and the within standard d Process Capability of Caps cted within yield (.982) left hand tail of a standard normal then looking up the LSL

Target

USL

Process Data LSL 0.995 Target 1 USL 1.005 Sample Mean 1.00006 Sample N 750 StDev(Within) 0.00198431 StDev(Overall) 0.00198636

Within Overall

of CPL or CPU.

Potential (Within) Capability Cp 0.84 CPL 0.85 CPU 0.83 Cpk 0.83 Overall Capability Pp PPL PPU Ppk Cpm

45 60 75 90 05 20 35 50 99 .99 .99 .99 .00 .00 .00 .00 . 0 0 0 0 1 1 1 1 Observed Performance PPM < LSL 4000.00 PPM > USL 6666.67 PPM Total 10666.67

Exp. Within Performance PPM < LSL 5355.08 PPM > USL 6432.04 PPM Total 11787.12

Worksheet: Bottle Caps.MTW

Exp. Overall Performance PPM < LSL 5395.59 PPM > USL 6478.48 PPM Total 11874.07

0.84 0.85 0.83 0.83 0.84

Calculating Cpk and Ppk Process Capability of Caps

e process mean, the respective specification limits and the overall standard d cted within yield (.9813) left hand tail of a standard normal then looking up the LSL

Target

USL

Process Data LSL 0.995 Target 1 USL 1.005 Sample Mean 1.00006 Sample N 750 StDev(Within) 0.00198431 StDev(Overall) 0.00198636

Within Overall

of PPL or PPU.

Potential (Within) Capability Cp 0.84 CPL 0.85 CPU 0.83 Cpk 0.83 Overall Capability Pp PPL PPU Ppk Cpm

45 60 75 90 05 20 35 50 99 .99 .99 .99 .00 .00 .00 .00 . 0 0 0 0 1 1 1 1 Observed Performance PPM < LSL 4000.00 PPM > USL 6666.67 PPM Total 10666.67

Exp. Within Performance PPM < LSL 5355.08 PPM > USL 6432.04 PPM Total 11787.12

Worksheet: Bottle Caps.MTW

Exp. Overall Performance PPM < LSL 5395.59 PPM > USL 6478.48 PPM Total 11874.07

0.84 0.85 0.83 0.83 0.84

A Process that Drifts Consider a similar process that does change over time. The data is in Caps Drift.MTW. First test for normality

Normality Test Probability Plot of Caps Drift Normal 99.99

Mean 1.000 StDev 0.001291 N 720 AD 0.326 P-Value 0.520

99

Percent

95 80 50 20 5 1 0.01 0.9950

0.9975

Worksheet: Caps Drift.MTW

1.0000 Caps Drift

1.0025

1.0050

Do not reject the assumption of normality.

Capability Analysis

Capability Analysis Process Capability of Caps Drift

time as indicated by the difference between the WithinWithin and

hart.

LSL

Target

USL

Process Data LSL 0.995 Target 1 USL 1.005 Sample Mean 0.999998 Sample N 720 StDev(Within) 0.00102066 StDev(Overall) 0.00129055

Overall Potential (Within) Z.Bench Z.LSL Z.USL Cpk

Capability 4.76 4.90 4.90 1.63

Overall Capability Z.Bench Z.LSL Z.USL Ppk Cpm

0.9960 0.9975 0.9990 1.0005 1.0020 1.0035 1.0050 Observed Performance % < LSL 0.00 % > USL 0.00 % Total 0.00

Exp. Within Performance % < LSL 0.00 % > USL 0.00 % Total 0.00

Worksheet: Caps Drift.MTW

Exp. Overall Performance % < LSL 0.01 % > USL 0.01 % Total 0.01

3.70 3.87 3.88 1.29 1.29

Process Capability Exercise 1

1 ± .06 Inches

Data indicate the process is centered with a standard deviation of .02. Calculate the yield.

Exercise 1 Visualizing the Answer -.06

-.04

-.02

+.02

+.04

+.06

Process average

Design width (.12 Inches)

There are 3 units of standard deviation between the process average and the specification limits therefore this is a 3 sigma process (short term).

Exercise 1 Calculating the Yield Using tables or software to look up the USL-X ZUSL= area under the curve when Z=3 we ˆ σ find .9986 1.06-1 ZUSL= =3 .02 Again using tables or software to look LSL-X ZLSL = up the area under the curve when Z=-3 ˆ σ we find .00135. .94-1 ZLSL = = −3 Subtracting the two we find a yield of . .02 9973

Exercise 2 Assume a process owner has asked you to analyze the data in Process Capability Exercise 1.MTW. Parts A and B are made on different machines in lots (subgroups) of 5. The customer has established specification limits of 10 ± .1 and requires a Ppk of 1.33. Prepare a brief presentation to describe your analysis and recommendations? Remember to present data practically, graphically and analytically.

Exercise 2 Normality Tests Probability Plot of Part A Normal 99.99

Mean 10.00 StDev 0.05049 N 750 AD 0.420 P-Value 0.324

99

Percent

95 80 50 20 5 1 0.01

9.8

9.9

10.0 Part A

10.1

10.2

Worksheet: Process Capability Exercise 1.MTW

Probability Plot of Part B Normal 99.99

Mean 10.00 StDev 0.05647 N 750 AD 0.248 P-Value 0.752

99

No reason to reject the assumption of normality for either part.

Percent

95 80 50 20 5 1 0.01

9.8

9.9

10.0 Part B

10.1

Worksheet: Process Capability Exercise 1.MTW

10.2

Exercise 2 Process Capabilities

Exercise 2 Part A Process Capability Process Capability of Part A LSL

Target

USL

Process Data LSL 9.9 Target 10 USL 10.1 Sample Mean 10.0009 Sample N 750 StDev(Within) 0.0496334 StDev(Overall) 0.0504922

Within Overall Potential (Within) Capability Cp 0.67 CPL 0.68 CPU 0.67 Cpk 0.67 Overall Capability Pp PPL PPU Ppk Cpm

9.88 9.92 Observed Performance % < LSL 1.87 % > USL 2.80 % Total 4.67

Exp. Within Performance % < LSL 2.10 % > USL 2.30 % Total 4.40

9.96 10.00 10.04 10.08 10.12 Exp. Overall Performance % < LSL 2.28 % > USL 2.49 % Total 4.77

Worksheet: Process Capability Exercise 1.MTW

0.66 0.67 0.65 0.65 0.66

Exercise 2 Prepare the Control Charts

Control Chart Shows Process Stability Xbar-R Chart of Part A UCL=10.0675 Sample Mean

10.05

__ X=10.0009

10.00

9.95 LCL=9.9343 1

16

31

46

61

76 Sample

91

106

121

136

Sample Range

UCL=0.2441 0.2

4 0.1

_ R=0.1154

44 4

0.0

LCL=0 1

16

31

46

61

76 Sample

91

Worksheet: Process Capability Exercise 1.MTW

106

121

136

Process Capability Part B Process Capability of Part B LSL

Target

USL

Process Data LSL 9.9 Target 10 USL 10.1 Sample Mean 9.99961 Sample N 750 StDev(Within) 0.0496334 StDev(Overall) 0.0564727

Within Overall Potential (Within) Capability Z.Bench 1.71 Z.LSL 2.01 Z.USL 2.02 Cpk 0.67 Overall Capability Z.Bench Z.LSL Z.USL Ppk Cpm

9.84 Observed Performance % < LSL 4.13 % > USL 4.00 % Total 8.13

9.90

Exp. Within Performance % < LSL 2.24 % > USL 2.16 % Total 4.39

9.96

10.02 10.08 10.14

Exp. Overall Performance % < LSL 3.89 % > USL 3.77 % Total 7.66

Worksheet: Process Capability Exercise 1.MTW

1.43 1.76 1.78 0.59 0.59

Control Chart Shows Time Based Variation Xbar-R Chart of Part B 1 1

11

1

1

1 5

Sample Mean

10.05

UCL=10.0662

__ X=9.9996

10.00 9.95

1

9.90 1

5 1

5 1

1 16

31

46

61

76 Sample

91

106

LCL=9.9330

1 121

136

Sample Range

UCL=0.2441 0.2

4 0.1

_ R=0.1154

44 4

0.0

LCL=0 1

16

31

46

61

76 Sample

91

Worksheet: Process Capability Exercise 1.MTW

106

121

136

Confidence Intervals

About This Module… Confidence Intervals (CI) permit us to state that we are X% confident that the population parameter of interest is at most a specified interval from the sample statistic.

Six Sigma, A Quest for Process Perfection Meet Goals and Attack Variation

\DataFile\PurchOrd.mtw \DataFile\PwrSuply.mtw \DataFile\Conf-Int.mtw \DataFile\OEack.mtw

What We Will Learn...

1.Significance of confidence intervals 2. 3.How to calculate confidence intervals for: –Means –Standard deviations or Variation

Confidence in the Midst of Uncertainty? and Standard Deviation statistics are: –estimates of the population Mu’s (µ ) and Sigma’s (σ ) –based on one sample

Ninety-five Percent Certain

uMean

Ø uVariability exists from sample to sample u uBy

using statistically based confidence intervals, uncertainty can be quantified

u u Usually, 95%are confidence intervals The chances approximately 95

are out of 100 calculated that the calculated confidence interval contains the population parameter, or… With 95% certainty, the population parameter is inside the confidence interval.

Population vs. Sample Population is the entire area of interest. Sample is a subset of the population. What is the relationship between the population and the sample?

Population

Sample

How representative is this sample?

Confidence Interval Symbols and Definitions Measure Mean

Population Sample Parameter Statistic

µ

X

Use Z  n ≥ 30 σ is known t  n < 30 



Variance

σ2

s2

χ

2

Standard Deviation

σ

s

χ

2

Process Capability

Cp

Cp

^

χ

2

p

^ p

Proportion Alpha Risk

α

F or Z (approx) Typically .05

Confidence Intervals (CI) CI take the general form : C.I.=Statistic +/- K * (Standard Deviation) Statistic= Mean, Variance, CP, etc. K = Constant based on a statistical distribution CI reflect the sample to sample variation of our point estimates We will look at CI for: µ , σ

X

, and C P

What is the Student t-distribution? The Student t distribution is a family of bell shaped (Normal like) distributions that vary by degrees of freedom (sample size) - the fewer degrees of freedom, the wider and flatter the distribution. 0.45 0.4 0.35 0.3 0.25 0.2 0.15 0.1 0.05

DF2

DF10

DF30

4

5 3.

3

5 2.

2

5 1.

1

5 0.

0

5 -0 .

-1

5 -1 .

-2

5 -2 .

-3

5 -3 .

-4

0

t-Distributions, Normal Approximation, Risk To give an idea of the values of t compared to Z for 95% (α = 0.05), look at the table below: Sample 5 10 20 30 100 1000

t-value 2.78 2.26 2.09 2.05 1.98 1.96

Z-value 1.96 1.96 1.96 1.96 1.96 1.96

α = risk α /2=0.025

We can use Z to estimate t if n ≥ 30 and σ is known STATISTICS FOR EXPERIMENTERS-- BHH

t

α /2= 0.025

Hypothesis Testing

About This Module… Hypothesis Testing helps: uDetermine if there is a statistically significant difference between two relatively small samples uQuantify the risks of making an incorrect decision

Six Sigma, A Quest for Process Perfection Meet Goals and Attack Variation

What We Will Learn 1.How to test variable data a.Use a t-test to compare two means b.Alpha (α ) and Beta (β ) Risks c.Use a paired t-test to compare paired treatments d.Use test for equal variances 2.How to test discrete data a.Compare proportions b.Compare discrete data Ø

Real World Scenario Design: Determine if two alternate design changes are significantly different. Manufacturing: Determine if two different types of material wear differently. Administrative/Transactional / Service: Determine if the change to a process affected the cycle time.

Purposes of Hypothesis Testing uDetermine

if there is a real difference between ? and ? .

uUse

relatively small samples to answer questions about the population.

uQuantify

the associated risks.

Example Old Design uHard disk transfer speed 89.7 (megabytes per second) is 81.4 marginal. A new design is 84.8 proposed. 87.3 79.7 uAn Engineering Change 85.1 Notice (ECN) is incorporated 81.7 83.7 uIs the new design better? 84.5

New Design 84.7 86.1 91.9 86.3 79.3 86.2 89.1 83.7 88.5

To answer this, we need some fundamentals of significance testing first!

Steps in Hypothesis Testing 1.Define the problem 2.Determine the objectives 3.Establish the Hypothesis –Write the Null Hypothesis (H0) –Write the Alternative Hypothesis (Ha) 4.Determine the appropriate statistical test (assume distribution Z, t, F) 5.State the alpha risk (usually 5 %) 6.State the beta risk (usually 10-20 %) 7.Establish the effect size (delta) 8.Compute the sample size 9.Develop a sampling plan

10.Select the samples 11.Conduct the test and collect data 12.Calculate the test statistic (Z, t, or F) from the data 13.Determine the probability that the calculated test statistic has occurred by chance 14.If that probability is less than alpha, reject H0 15.If that probability is greater than alpha, do not reject H0 16.Translate the statistical conclusion into a practical solution

Significance Tests uUsed

to assess evidence provided by sample data to reject, or fail to reject a claim about a population parameter.

uNull

hypothesis (Ho) is the statement we assess.

uHo

is usually stated as, “there is no difference”.

uAlternate

hypothesis (Ha) is usually stated as “there is a difference”.

uWe

fail to reject Ho unless there is convincing evidence to reject it.

Typical Examples

Ho :µ a = µ b Ha :µ a ≠ µ b Ho :σ a = σ b Ha :σ a ≠ σ b Ho : pa = pb Ha : pa ≠ pb

What does 5% Level of Significance Mean? This means that we will reject the null hypothesis if the difference between the sample statistic and the hypothesized population parameter is so large that it would occur, on an average, only 5 or fewer times in every 100 samples when the hypothesized population parameter is correct.

Type I and II Errors: Associated Risks Type I errors are made when we reject the null hypothesis when in fact it is true. Alpha (α ) risk is the probability of making a type I error.

This risk is typically set at 5%.

Type II errors are made when we fail to reject the null hypothesis when in fact it is false. Beta (β ) risk is the probability of making a type II error.

This risk is typically set at 10%

Risks are set before the test or experiment is conducted

The Risk Truth Table α is the risk of finding a difference when there really isn’t one. β is the risk of not finding a difference when there really is one. Action State of Nature Ho should not be rejected (Ho is true) Ho should be rejected (Ho is false)

Ho not rejected

Ho rejected

Correct Decision

Type I or producer’s risk α = P(Type I)

Type II or consumer’s risk β = P(Type II)

Correct Decision

Another Look at Risks Remember: α is the risk of finding a difference when there really isn’t one. β is the risk of not finding a difference when there really is one. Ho Ha

β α Now we can determine if the ECN improved performance

Normal Distribution and t Distribution When Population When Population SD is Known SD is Not Known Sample size n is > Normal Normal 30 distribution, z table tdistribution, Sample size < 30, Normal distribution,z ttable and we can assume distribution, z table table population is approx normal

P Value P value is the smallest level of significance that would lead to rejection of the null hypothesis Ho. eg. supposing Ho were true, what is the probability of getting a value of x-bar this far from the population mean? This probability is called a prob value or p-value.

Manual Test Null Hypothesis µ

1

†µ

2

 s12 s22 Difference Upper bound = X1 − X 2 +  tα ,df * +  n1 n2  Difference Upper bound = -1.99 + ( 1.7459* 1.57) Difference Upper bound = .756 The upper bound for the difference in the means indicates the difference between the means of these populations could be as great as .756 (at the 95% confidence level). Therefore, the evidence is not statistically significant to conclude that the difference between the new design and the old design is less than 0. Fail to reject Ho.

   

Manual Test Null Hypothesis µ

t(α ,df ) =

X1 − X 2 2 1

2 2

s s + n1 n2

1

†µ

= -1.26

P = .112 P> .05 therefore fail to reject Ho.

2

Hypothesis Testing Decision Tree Ho: P1=P2 Ha: P1 P2 Minitab: Stat-Basic Stat-1or 2 proportions

Hypothesis Testing

Proportions Testing (2 factors only) Continuous Data (One factor only)

Non-normal

Attribute Data

Normal

Normality test Ho: Data is Normal Ha: Data is NOT Normal Minitab: Stat-Basic Stat-Normality Test Use Anderson-Darling

2 or more samples Ho:σ 1=σ 2=σ 3… Ha: At least 1 is different Levene’s Testfor Equal Variances Minitab: Stat-ANOVA-Test For only 2 s, this is similar to an F-test: F=(S1)2/(S2)2 If Fcalc>Fcrit , reject null (Use Chi-Squared for 1 sample)

Ho: M1 = Target Ha: M1 Target Minitab: Stat-Nonparametric-1 Sample - sign (or) 1 Sample Stat-Nonparametric-1 Sample Wilcoxon (Also used for paired comparisons Ho: M1-M2=0) M1=Median or sample 1 M target = Target Median

Ho: M1=M2=M3… Ha: At least2 2or are different More Samples Minitab: Stat-Nonparametric-Mann-Whitney (or) Stat-Nonparametric-Kruskal-Wallis (or) Stat-Nonparametric-Freidmans M1=Median sample 1, etc.

Ho: 2 factors are independent Ha: 2 factors are dependent Minitab: Stat-tables-Chi square test

Contingency Table

1 Sample

2 or More Samples

Bartlett’s Test/F-Test

Chi-Square Ho: σ 1=σ Target Ha: σ 1 σ Target Minitab: Stat-Basic Stat-Graphical Summary If σ target falls within C1: then fail to reject Ho

1 Sample T Test Ho: µ 1=µ Target Ha: µ 1 µ Target Minitab: Stat-Basic Stat-1 Sample-T (Also used for paired comparisons:Ho: µ 1=µ 2=0)

Ho:σ 1=σ 2=σ 3… Ha: σ 1 At least 2 are different Minitab: Stat-ANOVA-Test for Equal Variances For only 2 σ s, this is same as F-test: Stat>BasicStat>2 Variances F=(S1)2/(S2)2 If Fcalc>Fcrit , reject Ho

1 Sample Z Test Ho: µ 1=µ Target Ha: µ 1  µ Target Minitab: Stat-Basic Stat-1 Sample-Z (Also used for paired comparisons: Ho:µ 1=µ 2=0) Sample Size >=30 σ is known

2 Sample T Test Ho: µ 1=µ 2 Ha: µ 1 µ 2 Minitab: Stat-Basic Stat-2 Sample-T (Compares Means using pooled Std Dev) Check box to assume equal variances or Check box to assume unequal variances

One Way ANOVA

Ho: µ 1=µ 2=µ 3=… Ha: µ 1 at least 2 are different Minitab: Stat-ANOVA-One Way (Caution Bartlett’s pbasic stat>correlation Correlation of Station 1 and Station 2 = 0.959, P-Value = 0.000 The two are highly correlated (.959)

?

Is this reasonable? Are you comfortable with .959? What does it mean to you? How does the data actually look? How would you find out?

Plot the Data Graph>ScatterPlots

The Data Scatterplot of Station 1 vs Station 2 9.4 9.3 9.2 Station 1

If all of the 9.1 data points were on the9.0diagonal line, would8.9we have perfect correlation? 8.8 8.7 8.6 8.5 8.6

8.8

Worksheet: Correlat.MTW

Let’s try regression

9.0

9.2 Station 2

9.4

9.6

Regression

Fitted line plot is used when there is only one predictor.

Example 1 (cont.) Fitted Line Plot Station 1 = 1.020 + 0.8729 Station 2 9.5

S R-Sq R-Sq(adj)

9.4

0.0557288 92.0% 91.5%

9.3 Station 1

9.2

In what ways is this graph different from the preceding one?

9.1 9.0 8.9

What are the implications?

8.8 8.7 8.6 8.6

8.8

9.0 9.2 Station 2

9.4

9.6

Worksheet: Correlat.MTW

Slide 225 was actual line – this is a fitted line. Can be used for prediction.

What action would you take?

Best Fit Line Fitted Line Plot Cases = 22.47 + 0.7546 Test Piece 100

S R-Sq R-Sq(adj)

90

Cases

80 70 60

11.5131 49.4% 47.7%

By minimizing the residual sum of squares, we get a best fit line of the form:

50 40 40

50

60

70 Test Piece

80

90

100

Yi = a + bX i

Worksheet: cases.MTW

a = coefficient of the constant term or intercept b = coefficient of the predictor, X

Statistical Process Control

About This Module… Control charts portray process performance and separate causes of variation: •Random •Assignable • Control Chart Systems are: •A proven technique for improving productivity •Effective in defect prevention •Prevent unnecessary process adjustments •Provide diagnostic information •Provide information about process capability

Six Sigma, A Quest for Process Perfection Meet Goals and Attack Variation \DataFile\Attribut mtw \DataFile\Variable.mtw

What We Will Learn.

1. Control charts are a powerful tool to hold the gains. 2. How control charts discriminate between common cause and assignable cause variation. 3. Why control charts must be designed to fit the data type and the control purpose.

Process Variation Process variation is the result of: • Common causes. • Special (assignable) causes. 

Common Causes • Result in normal process variation. • Are specific to each process. • Can be reduced by changing the process.

Special (Assignable) Causes • Are attributed to something outside of the process. • Result in abnormal process variation. • Do not result in process improvement  if eliminated.

Uses of Control Charts 1) Attain a state of statistical control: •All subgroup averages and ranges within control limits - no assignable causes of variation present 2) Monitor a process 3) Determine process capability • Juran’s Quality Control Handbook, 4th edition, page 24.7

What happens after an out-of-control situation occurs at the core of a successful SPC program?

General Concepts w = some characteristic of interest

XW

= mean of each sample

Sw = standard deviation of w Upper Control Limit UCL = X + 3S w Centerline =

X

Lower Control Limit

LCL = X − 3Sw

Therefore 99.73% of points will be within the control limits unless there is an assignable cause

Control Chart Selection Tree Type of data

Variable

Discrete

Count

Fixed

C Chart

Fixed or variable opportunity?

Count or Classification

Variable

U Chart

Attribute

Fixed

NP Chart

No

Fixed or variable opportunity?

Variable

P Chart

IMR Chart

Subgroup >1?

Yes

X Bar and R or X Bar and S

Supplement with EWMA if CTQ is sensitive to small process shifts

X and R Control Chart Formulae & Constants X Control Limits =X ± A 2R R Upper Control Limit = D R 4 R Lower Control Limit = D R 3 Sample Size 2 3 4 5 6 7 8 9 10

A2

D3

D4

d2

1.880 1.023 .729 .577 .483 .419 .373 .337 .308

.076 .136 .184 .223

3.267 2.574 2.282 2.114 2.004 1.924 1.864 1.816 1.777

1.128 1.693 2.059 2.326 2.534 2.704 2.847 2.970 3.078

Creating Control Charts for Variables \DataFile\Variable.mtw

Creating an X-bar and R Chart

An X-Bar and R Chart Xbar-R Chart of measure1, ..., measure5 1 1

1

5

Sample Mean

41

__ X=40.000

40 6

39 1

6 1

1

38

LCL=38.706

1

5

10

15

20

25 Sample

30

35

40

45

UCL=4.743

4.5 Sample Range

UCL=41.294

3.0

_ R=2.243

1.5

0.0

LCL=0 5

10

15

20

25 Sample

30

35

40

45

Worksheet: Variable.MTW

The numbers show violations of the assumption of control. The nature of the violation is given in the session window.

X-Bar and R Chart Session Window Test Results for Xbar Chart of measure1, ..., measure5 TEST 1. One point more than 3.00 standard deviations from center line. Test Failed at points:

7, 10, 13, 16, 17, 29, 46

TEST 5. 2 out of 3 points more than 2 standard deviations from center line (on one side of CL). Test Failed at points:

10, 17, 47

TEST 6. 4 out of 5 points more than 1 standard deviation from center line (on one side of CL). Test Failed at points:

7, 32, 34

* WARNING * If graph is updated with new data, the results above may no * longer be correct.

StatGuide Interprets the Tests

Comparing the Suppliers __ X=39.894

40 39 1

4

LCL=38.580 6

8

10

12 14 Sample

16

18

20

22

_ R=2.278

2 0

LCL=0 6

8

10

12

14

16

18

20

22

24

1

1

1 5

5

6

38 4

6

1

8

10

12 14 Sample

1

16

18

20

22

UCL=41.384 _ X=40.106 LCL=38.829

5

1

24

UCL=4.683 4 _ R=2.214

2 0

LCL=0 2

4

6

8

Sample Worksheet: Variable.MTW(Supplier = 1)

5

40

2

UCL=4.816

4

42

24

4

2

Sample Mean

UCL=41.207

41

2

Sample Range

Xbar-R Chart of measure1, ..., measure5

Sample Range

Sample Mean

Xbar-R Chart of measure1, ..., measure5

10

12

14

16

18

20

Sample Worksheet: Variable.MTW(Supplier = 2)

Supplier 2’s process is less stable than Supplier 1’s process.

22

24

Add Dates to Control Charts

Adding dates to the control charts may help identify potential sources of shifts.

Adding Dates Indicates When the Shift Occurred Xbar-R Chart of Stacked Data 1s 12

5

Sample Mean

6 11

2

10

6 6

6

9 7/31/2006 8/4/2006 8/10/2006 8/16/2006 8/22/2006 8/28/2006 9/1/2006 Date

Sample Range

4.5

3.0

1.5

2

9/7/2006 9/13/2006 9/19

Detecting Gradual Process Drift Xbar-R Chart of Stacked Data 1s 12

UCL=11.850

5

Sample Mean

6 2

11

2

10

2

2 2

2

_ _ X=10.568

6 6

6

LCL=9.286 9 4

8

12

16

20 Sample

24

28

32

36

40

UCL=4.699

Sample Range

4.5

3.0

_ R=2.222

1.5

0.0

LCL=0 4

8

12

16

20 Sample

24

28

32

36

40

Worksheet: Variable.MTW

The tests detect the process shift but it would have been detected earlier if the control limits had been based on the first 20 data points.

Detecting Gradual Process Drift Minitab calculates control limits based on the entire data set be default. Freezing control limits detects shifts earlier than using the entire data set to calculate limits. Xbar-R Chart of Stacked Data 1s

Sample Mean

12

1

1 5

11

6

6

2

2

2 2

2 2

6

2

2

2 2

__ X=10.112

10

9

LCL=8.864 4

8

12

16

20 Sample

24

28

32

36

40

UCL=4.575

4.5 Sample Range

UCL=11.360

2

3.0 _ R=2.164 1.5

0.0

LCL=0 4

8

Worksheet: Variable.MTW

12

16

20 Sample

24

28

32

36

40

Rational Subgrouping •Usually consecutive units •Must come from a single distinct population •Within subgroup, variation should be white noise only •Between subgroups should capture variation due to black noise 1) 2) 3) 4)

Subgroup needs to represent the distinct population Establish minimum subgroup size to reflect the within variation Establish sample frequency to capture the between variation Collect data maintaining the sequential information •Never knowingly subgroup unlike things together •Minimize variation within each subgroup •Maximize opportunity for variation between subgroups •Average across noise not across signals •Treat charts in accordance with the use of the data •Establish standard sampling procedures Donald J. Wheeler has six guiding principles for subgrouping in a rational manner.

When to Increase Sample Size If the sample size is too small, assignable causes may produce real effects that are relatively small and unimportant. In this case, it may not be economical to take action. To minimize the number of these “nuisance” causes, the sample size should be increased using the following techniques: •Identify characteristics •Determine logical nature of subgroups •Identify sampling sequence •Measurement methods proven to be accurate

What We Have Learned. 1. Control charts are a powerful tool to hold the gains 2. How control charts discriminate between common cause and assignable cause variation 3. Why control charts must be designed to fit the data type and the control purpose

Lean Enterprise A Formula for Organizational Success

Agenda 

1. Introduction to Lean, Wastes 2. 5S WPO & Visual Management 3. Standard Work 4. Value Stream Mapping 5. Quick changeover 6. Poka-yoke 7. Continuous Improvement 8. Kaizen Blitz 9. Starting Lean

Introduction to Lean and 7 Wastes

• Identify and Eliminate  the 7 Wastes

Brief History of Lean • Craftsman to mass production • Mass production to lean production • Lean production: Ford to Toyota – Frederick Taylor – Taiichi Ohno – Shigeo Shingo – James Womack

• From shop floor to office and support functions then to service industry •

Craft Manufacturing 

Late 1800’s

• ●

Car built on blocks as workers walked around

●

Built by craftsmen with pride

●

Components hand-crafted, hand-fitted

●

Excellent quality

●

Very expensive

●

Few produced

Mass Manufacturing • Assembly line - Henry Ford 1920s • ● ● ● ● ● 

Low skilled labor, simplistic jobs, no pride in work Interchangeable parts Lower quality Affordably priced for the average family Billions produced – identical Model ‘T’

Lean History – Japan • Sakichi Toyoda at his textile mills (20’s–30’s) • Toyota Motor Company’s Kiichiro Toyoda and Taiichi Ohno made innovations (40’s) in assembly lines that provided efficient, customer-focused, streamlined processes with flow, variety, and short lead time— Toyota Production System (TPS); to face competition of GM and Ford after WWII when key need was flexibility. • Taiichi Ohno and Shigeo Shingo developed Lean based on TPS

Lean Manufacturing ●

Cells or flexible assembly lines

●

Broader jobs, highly skilled workers, proud of



product

●

Interchangeable parts, even more variety

●

Excellent quality mandatory

●

Costs being decreased through process



improvement

●

Global markets and competition.

What is Lean? “A business system for organizing and managing product development, operations, suppliers, and customer relations that requires less human effort, less space, less capital and less time to make products with fewer defects to precise customer desires compared with the previous system of mass production.”



Lean Lexicon, Lean Enterprise Institute, 2003

Definition Lean manufactuirng is aimed at the elimination of waste in every area of production including customer relations, product design, supplier networks and factory management. The goal of Lean Manufacturing is to incorporate less human effort, less inventory, less time to develop products, and less space to become highly responsive to customer demand, while at the same time producing top quality products in the most efficient and economical manner.

Why Call it “Lean”? • The term “lean” is used because lean  uses “less”… •

üLabor üSpace üCapital investment üMaterials üTime between the customer order and the product shipment

Definition of Lean Lean has been defined in many different ways –

 

“A systematic approach to identifying and eliminating waste (non-value-added activities) through continuous improvement by flowing the product at the pull of the customer in pursuit of perfection.”





Definition by the MEP Lean Network 

Give the customers what they want, when they want it, and do not waste anything.



Definition of Value Added Waste is any activity that does not add value to the final product for the customer. • Value-added is an activity that transforms or shapes raw material or information to meet customer requirements. • Non-value added is an activity that takes time, resources or space, but does not add to the value of the product or service itself. • Non-value-adding, but necessary – does not add value to the product or service but is required (e.g., accounting, governmental regulations, etc.). 

Waste



“Anything that adds Cost  to the product  without adding Value”

Toyota Way – the 14 Principles by Jeffrey K. Liker 1. Base management decisions on long-term philosophy, even 2. 3. 4. 5. 6. 7. 8.

at expense of short-term financial goals. Create continuous process flow to bring problems to surface. Use pull systems to avoid overproduction. Level out workload (heijunka); work like a tortoise, not a hare. Build culture of stopping to fix problems, to get quality right first time. Standardized tasks are the foundation for continuous improvement and employee empowerment. Use visual controls so no problems are hidden. Use only reliable, thoroughly tested technology that serves people and processes.

Toyota Way - 14 Principles (cont.) 9. Grow leaders who thoroughly understand work, live philosophy,

and teach others. 10.Develop exceptional people and teams that follow company’s

philosophy. 11.Respect extended network of partners and suppliers by

challenging them and helping them improve. 12.Go and see to thoroughly understand situation (genchi

genbutsu). 13.Make decisions slowly by consensus, thoroughly considering

all options; implement decisions rapidly. 14.Become a learning organization through relentless reflection

(hansei) and continuous improvement (kaizen).

Liker Model Toyota Terms Genchi Genbutsu Problem Solving People and Partners

Respect and Teamwork

Kaizen

Process

Philosophy

Challenge

Liker Model - 4 Ps 1. Philosophy

Long-term thinking even at expense of short-term financial goals 2. Process • Eliminate waste by focusing on flow, pull, workload balance, error reduction, standardization, visual controls, and jidoka or use of reliable, tested technology/automation with mistake proofing and human touch 3. People and Partners • Respect, develop, and challenge people 4. Problem Solving • Fix and prevent problems by continual learning, going to place where problem occurs, getting hands dirty, and making good decisions based on fact •

What Is Lean? Lean is a methodology



• that allows organizations to drastically improve bottom line • by improving processes and monitoring everyday business activities to reduce errors • in ways that increase value and minimize work, nonvalue-add tasks, and waste while increasing customer satisfaction -



Based on idea that faster processes yield less waste, less cost, less work in process, less complexity, higher quality, and happier customers

Womack and Jones Model 1.Define value from customers’ perspective 2.Document value stream 3.Improve flow of value stream 4.Drive for pull versus push 5.Continuously improve

Lean Principles • Create value for customer • Understand: – Who is customer – person or entity who is recipient of product or service; one who places value on output; catalyst/trigger in value chain • Another business • Someone inside own business • Specific individual, group, or team • Consumers—ultimate customer

– What customer considers valuable • Make value flow based on customer’s needs

Lean Principles (cont.) • Consider life cycle of information, materials, processes, products, and services • Look for process problems that prevent people from performing best work • Eliminate waste

– Non-value-add steps – WIP – Cost • Standardize work • Do not become distracted by other stakeholders •

Value-Add Quiz 

In which category should the following be placed? Activity Value Add Attending weekly team coordination meeting Filtering through daily e-mail list Reporting status to upper management Gaining multiple approvals on documents Gaining management approval for routine actions Expediting document through approval list Writing formal policies and procedures Writing brief work-method instructions Gaining regulatory or agency approvals Creating ISO 9000 documentation Hunting for needed information to do your job Building “best practices” database Holding lessons learned meeting Spending time on process improvements

Type 1

Type 2

Lean vs. Traditional Lean



• • • • • • • •

Simple and visual signals Demand driven Inventory as needed Reduce non-value added Small lot size Minimal lead time Quality built Value stream managers

Traditional



• • • • • • • •

Complex Forecast driven Excessive inventory Speed up value-added work Batch production Long lead time Inspected-in Functional departments

Benefits of Lean Manufacturing Helps in – • Cost reduction Lead Time Reduction • Cycle time reduction Productivity Increase • “Waste” minimization WIP Reduction • Elimination of non- Quality value-added Improvement activities Space Utilization • Resulting in a more “lean,” competitive, agile, and marketresponsive 

Real Results 0

50

100

Why the Emphasis on Lean Now? • • • • • •

Global economy Pressure from customers for price reduction Fast-paced technological changes (e.g. Internet auctions) Continued focus on quality, cost, delivery Higher and higher expectations of customers Quality standards, such as QS-9000 (or TS 16949), the new ISO 9000:2000 • Holding on to “Core Competencies,”outsourcing the rest • Market-driven pricing: Customers expect better performance at lower prices year after year

Evolution of Lean Across Markets • Proven global concept since 1980s • Transformed business processes across many industries: –Automotive –Aerospace • Other industries beginning to embrace Lean concepts with excellent results: –Construction –Hospitals –Pharmaceutical Manufacturing –Service Organizations

Pricing Model Costs Increase

Old Way



Maintain Profits

Increase Price

 

New Way

Cost + Profit = Price Customers Demand Lower Prices

If Costs Stay the Same

Profits Decrease

Price - Cost = Profit

What can we do?

Pricing Model Old Way

Costs Increase

Maintain Profits

Increase Price

Cost + Profit = Price

New Way

Customers Demand Lower Prices

Implement Lean

Increased Profits

Price - Cost = Profit

Core Concepts of Lean • Creativity before Capital • A solution that is not-so-perfect implemented today, is better than a perfect solution that is late. “Just do it.” • Inventory is not an asset, but a waste/cost. • Typically, 95% of lead-time is not value added. • Lean implementation using the Plan-Do-CheckAct methodology • Continuous Improvement environment: both incremental and breakthrough. • Lean is a never-ending philosophy.

Aluminum Can Example •From aluminum ore to usable cans, it typically takes about 300 days Bauxite

Cryolite

Aluminum

Cast Product

3 hours Cans

Sheet

Rolled Plate

Guess what the total value-added time is?

Video • Introduction to Lean 

7 Wastes of Lean 

• • • • • • • •

“OMIT What U DO”

Overproduction Motion Inventory Transportation (Movement) Waiting Defects (Correction) Over-processing Underutilized People

C O M M WI P

Overproduction Making more-earlier-faster than the next process needs it



•Just in case logic •Unbalanced workload •Unleveled scheduling •False sense of efficiency

•Printing 20 copies of a report that only 3 people look at •All-staff e-mails when it pertains to only a few •Waiting to “batch” work

Motion Any movement of people that does not add any value to the product or service 

•Poor layout •Inefficient Workplace Organization •Lack of Standardization, inconsistent work methods •People, Material and Machine Ineffectiveness

•Where is are copier, printer, files and coffee-maker located? •How far does the paperwork travel?

Inventory Any supply in excess of one-piece flow



•Just in case logic •Unbalanced workload •Unleveled scheduling •Unreliable suppliers •Reward system •“Pack rat” mentality

•Printed forms or tags that become obsolete •8 weeks of paper located by the copier •How many pens do you have in your desk drawer?

Transportation Moving people, materials and information around the organization



•Poor layout •Inefficient “flow” •Carrying large quantities

•Moving “banker’s boxes to a storage area •Mail carts •Messenger services

Waiting Waiting for… man, machine, materials, information etc.





•Just in case logic •Unbalanced workload •Unleveled scheduling •Unplanned downtime •Needs not understood

•Waiting for files or information •Need a signature •Customer reply to a voice-mail or email •Someone is printing 50 copies of a 70 page report

Defects 

Information, products and service that need correction •Not using Jidoka or Poka-yoke •Lack of Standardization, inconsistent work methods •Ineffective communication •Little investment in training

•Have to fix paperwork that is not completely filled in or track down the right person to get the information •An entry error causes the wrong actions like shipping too many, or too few to the wrong address, etc.

Over-processing Effort that adds no value to the product or service from the customer’s standpoint 

•Just in case logic •Inconsistent work methods •Ineffective communication •Redundant approvals •Excessive information, extra copies

•Multiple sign-offs or checks

Underutilized People Not utilizing people’s experience, skills, knowledge, creativity



•Not utilizing Teams •Organization structure •Poor hiring practices •Little investment in training

•Lack of suggestions •“That’s not my job” attitude •Waiting for lead from management

Mura and Muri • Mura (unevenness) – variation in operation, wasted resources when quality, cost, or delivery cannot be predicted

– Testing/inspection, Containment, Rework, Returns, Overtime, Unscheduled travel • Muri (overdoing) – unnecessary or unreasonable overburdening of people, equipment, or systems when demand exceeds capacity or tasks are not designed properly including harmful, wasteful, or unnecessary tasks

Building Blocks of Lean Continuous Improvement & Kaizen Blitz Cellular & Pull System & TPM JIT Flow Kanban Poka-yoke

Self Inspection Batch Size Reduction

POUS Layout

Standard Work

Change Management

Autonomation

Quick Changeover Visual

5S Teams

V S M

Building Blocks of Lean Continuous Improvement & Kaizen Blitz Cellular & Pull System & TPM JIT Flow Kanban Poka-yoke

Self Inspection Batch Size Reduction

POUS Layout

Standard Work

Change Management

Autonomation

Quick Changeover Visual

5S Teams

V S M

5 Words that begin with “S” Japanese Seiri Seiton

Translation Organization Neatness

Conversion Sort Set in order

Seison Seiketsu

Cleaning Shine Standardization Standardize

Sweeping Standardize

Shitsuke

Discipline

Selfdiscipline

Sustain

*Other Sorting Simplifying access

* There are several other conversions

5 Steps to Workplace Organization 1 Clear/Sort By red tagging

5 Continuous Improvement Sustain Discipline

Waste

4 Maintain/Standardize Establish standards

2 Organize/Straighten A place for everything

3 Clean/Sweep Housekeeping / Inspection

Workplace Scan 

“Understand your Current State”

• Start with a workplace Scan • Team Based • Define the boundaries • Complete a Diagnostic Checklist • Draw a Spaghetti Diagram • Take “Before” Photos • Starts the 5S Program •

Workplace Scan Display Area Details

Checkli st Score

Spaghetti Diagram

Before Photos

After Photos

Sort 

“When in doubt, move it out”

• Move unneeded items out of the area • Use the Red Tag Technique • Use a Temporary Red Tag Holding Area • Criteria for unneeded items – “30-day Rule”

Name____ Date___ Item _____________ Reason _________

• Keep only what you need in the area •

Set in Order 

“A place for everything and 

everything in its place.”

• Make it easy for anyone to find – “30-second Rule”

• Make it obvious if an item is out of place • Decide where to keep items, how many items to keep, how and when to replenish items • Make it Visual

Shine 

“Clean and Inspect”

• Get items to a like-new condition – “10 Second Rule”

• Must plan Shine – assignments & supplies • Perform as a Team • Prevent dirt, grime, or contamination • Repair as needed •

Standardize 

“Create the rules and follow them”

• Determine how the first 3S conditions are met • Use “One-Point Lessons” • Maintain and monitor the conditions • Use Visual techniques

Sustain 

“Make 5S a habit”

• 5S is not something additional, it is part of everyone’s daily job • Supports discipline • Train • Communicate • Support from Management • Reward and recognition

5S is Fundamental to Lean • 5S is directly related to other Building Blocks – Teams – Visual – POUS – Standard Work – TPM

Point-Of-Use Storage • Raw material and WIP are stored at workstation where used, which reduces the inventory that can be carried. • Works best if vendor relationship permits frequent, on-time, small shipments (JIT). • Simplifies physical inventory tracking, storage, and handling.

Carpenter Story • Does the carpenter walk back to the toolbox every time a tool is needed? • Which waste is this? • What does the carpenter do?

Proximity • Typically, up to 60% of time is spent on finding/collecting items needed. • Minimize non-value activities • Store as close as possible and within reach • Layout and workstation design should accommodate required materials • Try to use the packaging from the supplier or have the supplier change packaging

POUS Components • Have the: – Information – Parts & materials – Tools & equipment 

that you need to perform you tasks within reach

•

POUS Workplace Zones • Items used most often (i.e., daily) should be kept within reach • Items used less often (i.e., weekly) should be kept close-by • Items used rarely (i.e., monthly) should be kept in the vicinity

Daily Weekly Monthly

Location of items • Use horizontal transfers and gravity feeds when possible • Support heavy objects • Set items ergonomically • Must be comfortable for a day’s work

Benefits • Supports 5S & Visual and other Building Blocks • Simplifies inventory tracking and accuracy • Reduces waiting, inventory, motion and transportation waste

Benefits of 5S • Improved equipment reliability • Superior quality • Increased productivity • Better workflow • Enhanced Safety • Reduced inventory • More pleasant place to work • Impress customers •

Video • Introduction to 5S

Building Blocks of Lean Continuous Improvement & Kaizen Blitz Cellular & Pull System & TPM JIT Flow Kanban Poka-yoke

Self Inspection Batch Size Reduction

POUS Layout

Standard Work

Change Management

Autonomation

Quick Changeover Visual

5S Teams

V S M

Visual



Signs, lines, labels and color coding

Why Visual? • What you need to know • Cockpit view • Information sharing 

How do you know where to park when you



drive to a shopping mall?



Does someone have to tell you where to



park?





How to Apply Visual • Use Signs, Lines,

Examples



Labels and Color-

• Productivity Goals

coding

• Quality Goals

• Charts, pictures, lights, scoreboards • Kanban, Andon lights • Inventory Levels

• Delivery schedules • Set-up specification • Safety Initiatives • Attendance Goals • Team Objectives

More Examples of Visual • Signs • Charts • Goals • Pictures • Color coding • Lights • Scoreboards • VSM Current & Future State • Standard Work instructions

• • • • • • • •

Tags Forms Training hours Employees’ suggestions Cross trained skills Employee awards Absenteeism Critical maintenance points • Customer satisfaction goals • Performance targets •

Visual Controls as Communication Tools • Visual controls expose waste so we can reduce or eliminate it • Visual controls help in: – Improving motivation & morale – Focus on safety – Pride of workplace & workmanship

• Visuals and performance metrics – What gets measured, gets done – Policies drive behaviors

World Class Visual Controls • Anyone knows what’s going on by looking around • You do not have to wait for information to do your job • Everyone passes the 30 second test 

Visual Examples

Andon Lights Display Panels

Range Markings On Gauges Shadow Boards

Standard Work



Reduce task variability

Standard Work 

Best sequence of operations, using the most productive combination of resources:

• Man, machine, materials, changeovers, etc. • Details any special skill/knack needed • Safety, ergonomics are integrated • Tool for perfect quality and efficiency

Standard Work Properties • Specific • Measurable • Repeatable • Documented

Standard Work Identifies value added versus non-value added activities • Reduce or eliminate non-value added activities • Convert Internal Time to External Time, wherever possible • Continuous Improvement: once Standard Work is established as a base and displayed at workstations, operators monitor and implement improvements • Use as a training tool for new employees • Created by input from the people who actually work in the process 

Philosophy of Standard Work Be specific about: Example: Installing a Car Seat • Content • Bolts are installed and tightened in the same • Sequence exact order • Timing • The time required to tighten • Outcome bolts is stated and followed • Specified torque is applied and checked Used as the basis from where the next level of improvement is made. 

Types of Standardized Work Forms • Process Capacity Table • Work Combination Sheet • Standard Work Sheet • Others forms may be used based on your organization’s needs

Process Capacity Table Times for: • Elapsed time • Element time • Internal Time • External Time • Manual Time Step Identification • Transportation • Process • Inspection • Storage Use to identify bottlenecks Use to calculate the capacity of machines, and identify bottlenecks 

Process: Seq No.

Date:

Element

Symbol

Name: Elapsed Element Internal External Time Time Time Time

Shift:

Comments

1

Review work order for die number and material

600

600

300 Convert to External

2

Locate the die

1800

1200

300 Convert to External

3

Locate material

3000

1200

300 Convert to External

4

Get tools

3600

600

5

Tagout machine

4500

900

60

Prepare Tags before

6

Loosen bolts

4980

480

60

Use quick connects

7

Disconnect hoses

5280

300

60

Use quick connects

8

Remove die from press

5580

300

120

9

Return die to Tool Room

6180

600

10

Load die into press

6480

300

11

Align die

6960

480

12

Tighten bolts

7440

480

60

13

Connect hoses

7740

300

60

14

Position material

8340

600

15

Clear tagout

8940

600

16

Make sample piece

9000

60

60

17

Take first piece sample to QC

9600

600

120

18

Adjust die and press

10800

1200

19

Make sample piece

10860

60

11460

600

20 Return tools Transport

Process

Inspection

Storage

Total Time

11460

NVA = X

Changeover Analisys Chart

300 Convert to External

Position die cart

300 Convert to External

90

Use positive stops

0 Eliminate

X

Use quick connects Use quick connects

300 Convert to External

60

Have QC Tech ready

0 Pre-adjust die

X

0 Eliminate

X

600 Convert to External

750

2400

Page ____ of _____

Work Combination Sheet Sequence of: • Manual work time • Machine operations time • Walking 



Shows the interactions between machines and operators



Pr oduct Fam ily:B - Generators

ID 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30

Allows to recalculate operator work content as takt time changes



Description of Work Element Manually load WC-1 Start WC-1, go to WC-2 Unload part, Load Part, Start Machine, go to WC-3 Unload part, f ile c orner, inspect to print Load nex t part, s tart machine, go to WC-1 Fas ten parts A-1, and B-1 together, go to A S-2 Fas ten Housing and Base Pac kage generator Load on c art

Total Time:

 

Tim e Available : 24,600

Proces s : A ssembly Cell #23 De s cription:Final Assembly Cyclical Work Ele m e nt

Percent Operator Time: Non-cyclical Work Ele m e nts

De m and: 200 Tak t Tim e : 123 Element Time Manual Machine Operation Operation Walking 12 32 0 3 0 2 1 16 2 45 120 0 2 15 3 23 41 2 42 0 0 35 0 0 5 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 168

224

41% 55% Total Cyclic Time: Seconds Time PCS

1 2 3 4 5

13

seconds

Date : January 31, 200X

piec es seconds per piece

Nam e : Eileen N. Terpris e V S M gr: I.C. Flow Graph Data

Operation Times Start 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30

44 5 19 165 20 66 42 35 9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

0 44 49 68 233 253 319 361 396 405 405 405 405 405 405 405 405 405 405 405 405 405 405 405 405 405 405 405 405 405 100

0 49 68 233 253 319 361 396 405 405 405 405 405 405 405 405 405 405 405 405 405 405 405 405 405 405 405 405 405 405 200

300

400

500

3% 405 Rate

Total Time (Cyclical + Non-cyclical): Throughput per shif t = A vailable Time / Total Operating Time: Work Flow Diagram

WC-1

AS-1 Total Non-cyc lic Time:

Manual Operation Machine Operation Walking 12 32 3 0 1 16 45 120 2 15 23 41 42 0 35 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

WC-2

AS-1

WC-3

AS-1

405

0 2 2 0 3 2 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

Standard Work Sheet Sequence of processing steps • Worker • Machine • Tools • Layout • Material location (Standard stock) 

Standard Wo

Product F



Displayed at Workstations

 

Continuously reviewed and updated



B - Gene

Proce

Uses • The Process Capacity Table can be used to reduce changeover times • The Work Combination Sheet can be used for line balancing when creating a cell • The Standard Work Sheet can be used for training and team development •

Standard Work Examples

Adobe Acrobat Document

Adobe Acrobat Document

Adobe Acrobat Document

Standard Work and Training Questions to ask Operators about Standard Work • How do you do this work? • How do you know you are doing this work correctly? • How do you know there are no defects? • What do you do if you have a problem? • If these questions cannot be answered satisfactorily, then either the Operator needs additional training or the Standard Work is unclear 

Uses of Standard Work • Consistent performance of tasks = better quality • Track performance = actual versus standard for continuous improvement • Easy to Train = reduced learning cycle time

• New Learning Curve

Productivity

Productivity

Old Learning Curve

Time

Time

Benefits of Standard Work • Standard documentation for all shifts • Reductions in injuries and strain • Employee ownership of process • More pleasant working conditions; higher morale • Better than traditional time and motion studies • Reduced variability 

Poka-yoke • Error proof (mistake proof) takes away the possibility of human error • The term Poka-yoke was made popular by Shigeo Shingo • Fail-safe devices • Low cost, highly reliable mechanisms • Detects abnormal situations before they occur,  or • Once they occur, will stop the equipment from further production. The machine stoppage makes the problem visible. •

Other Poka-yoke Examples • USB ports on computers • Re-typing passwords to verify • Computer prompts before deleting file • Bar codes & scanning • ATM swipe card or beep •

Benefits of Poka-yoke • Gives immediate feedback for root cause analysis & correction (and prevention for the future). • Failure Mode and Effect Analysis (FMEA) solution can be Poka-yoke • Some examples of Poka-yoke devices are: sensors, counters, feelers, limit switches, electric eyes, probes, automatic stops.

Building Blocks of Lean Continuous Improvement & Kaizen Blitz Cellular & Pull System & TPM JIT Flow Kanban Poka-yoke

Self Inspection Batch Size Reduction

POUS Layout

Standard Work

Change Management

Autonomation

Quick Changeover Visual

5S Teams

V S M

Value Stream Mapping



See the Flow

Value Stream Analysis 

Value stream analysis encompasses all activities company must do to design, order, produce, and deliver its products and services to customers – Flow of tasks, from request for service (trigger event) to service complete, from receipt of materials or information from suppliers to delivery of finished product or service to customers – From viewpoint of customer, service, or transaction – Flow of information that supports and directs both flow of materials and transformation of raw materials or information into finished goods or services Purchasing

Human Resources

Operations

Value Stream Value Stream

Finance

Sales

Purpose of Value Stream Map • Has customers’ perspective and focuses on meeting customers’ wants and needs • Starts with immediate customer and maps back to receiving inputs from suppliers and shows how fits into overall value stream • Provides single view that is a complete, fact-based, and time-based representation of stream of activities • Provides common language and view for analysis • Shows how information triggers and supports activities • Shows time for activities and whether they add value

Elements of Value Stream Map • Process steps • Value-add classification for each step • Information flow such as orders, requirements, schedules, messages, approvals, specifications, kanban signals, shipping information, standard procedures • Box score of key operational metrics including cycle time, waiting time, working time, conveyance time, distance traveled, items per shift, items processed per hour,setup time, backlog/workin-process, amount of inventory between last step and consumer, defects, cost information, resource availability and active time, process variations • Lead time is amount of time for one item to flow completely through process, noted along bottom of flow • Takt time showing customer demand rate, in upper right corner of flow

Value Stream Analysis Steps • Identify deliverable, value stream, and sponsor who has authority and responsibility to allocate resources and make changes across organization • Identify customer and value from customer’s perspective as well as regulatory, legal, and compliance requirements • Draw visual representation of process current state, generally draw steps starting at consumer’s view working back through steps to sources of material and labor; flows from left to right with time, with steps in order of occurrence • Add metrics and observations like Takt time/throughput, cycle times, defect rates, and inventory/work-in-process and information flows to identify magnitude and frequency of waste • Use lean principles to reduce or eliminate waste and reduce cycle time • Develop future state map, document steps of process that need to happen, and prioritize and implement action plans to achieve future state

Value Analysis Matrix Steps • • • • •

Structure value analysis matrix Number process steps on sub process map Have column for each process step Estimate time for each process step Place check in category for each process step, either value-add or one of non-value-add categories • Total number of hours or number of checks for each row • Report percentages of value-add and noncustomer required

Value Analysis Matrix Example Process Step

11

Time (Hours)

22

33

44

55

66

77

88

99

10 10

1212 1010 1 1 1010 2020 6 6 1010 1 1 1010 2020

√√

Value - Add Added

√√

Total

% Total

100 100

100% 100%

22

2% 2%

1010

10% 10%

Non Customer Required Internal Failure

√√

External Failure

√√

Control/Inspection

√√

Delay

66

√√

√√

6% 6%

5252

52% 52%

3030

30% 30%

Prep/Set Prep/Set-Up - Up

√√

Move

Total

√√

√√

100 100

100% 100%

RFQ Creation Value Stream Map Customer Meetings C/T = 14 days W/T = 2 days VA/T = 1 day

Iterate Assign Buyer C/T = 3 days W/T = 4 hours VA/T = ~ 0

Gather Requirements C/T = 14 days W/T = 2 days VA/T = 1 day

Verify Customer Requirements

Consult with Manufacturing Engineer

Create Preliminary RFQ

C/T = 14 days W/T = 2 days VA/T = 1 days

C/T = 5 days W/T = 2 days VA/T = 4 hours

C/T = 5 days W/T = 2 days VA/T = 1 day

Revise Triggering Event

Review and Approval Cycle C/T = 5 days W/T = 1 day VA/T = ~ 0

Continue C/T = Calendar Time W/T = Work Time VA/T = Value-Add Time

Measurable Deliverable Continue

Create Final RFQ

Review and Approval Cycle

C/T = 5 days W/T = 2 days VA/T = 1 day

C/T = 5 days W/T = 1 day VA/T = ~0

Revise

Release RFQ C/T = 2 days W/T = 1 day VA/T = 2 hours

As-Is Process Cycle Time*: C/T = 58 days W/T = ~14 days VA/T = 5 days

Assumes no revisions!

Sales Order Processing Value Stream Map

C/T = Calendar Time W/T = Work Time VA/T = Value-Add Time

Time Customer is On Telephone Initial Phone Contact C/T = 0 W/T = 0 VA/T = 0

Wait for Available Sales Person

Sales Pitch

Configure System

Fill Out Order Form

Promise to Ship

C/T = 5 minutes W/T = 0 VA/T = 0

C/T = 10 minutes W/T = 10 minutes VA/T = 10 minutes

C/T = 30 minutes W/T = 30 minutes VA/T = 5 minutes

C/T = 10 minutes W/T = 10 minutes VA/T = 5 minutes

C/T = 5 minutes W/T = 5 minutes VA/T = 0

Change Ship Date

Triggering Event Measurable Deliverable

While customer is on telephone:

Issue Work Order to Factory Floor C/T = 1 Day W/T = 1 hour VA/T = 0

Yes

MtlNo . Av ail abl e ?

C/T = 60 min. W/T = 55 min. VA/T = 20 min.

Check Availability of Materials C/T = 3 Days W/T = 1 hour VA/T = 0

From Contact to Order Launch:

Batch Together Similar Systems

Pending Order “FIFO” Queue

C/T = 6 Days W/T = 1 Day VA/T = 0

C/T = 7 Days W/T = 0 VA/T = 0

C/T = 17 days W/T = ~ 1 day VA/T = 0

Buying a Salad Process Flow Customer buys salad with salmon Processed salmon is shipped to fish markets

Restaurant supply company distributes food

Container company sells containers

Grocer offers premade salads

Salad company makes salad and delivers to grocer

Salmon is processed at fishery

Fishers catch salmon

Produce is package and shipped Meat companies process animals Manufacturers make containers

Salad company buys supplies Mother nature makes salmon

Farmers grow and harvest produce Farmers raise meat animals

Chemical producers make plastics from petroleum

Oil refined for petroleum products

Cycle Time Definition 



“One of the most noteworthy accomplishments in keeping the price of products low is the gradual shortening of the cycle time. The longer an article is in the process and the more it is moved about, the greater is its ultimate cost.” Henry Ford, 1926



  

Work

Errors, waiting, transportation, movement etc….. Total Cycle Time

• Time that elapses from beginning to end of process • Ultimate objective or goal of Lean processes is to reduce cycle time by eliminating waste 

Benefits of VSM • Helps you visualize more than the single process level • Links the material and information flows • Provides a common language • Provides a blueprint for implementation • More useful than quantitative tools • Ties together lean concepts and techniques

4 Steps for VSM 1.Determine the Product Family 2.Draw your Current State Map 3.Create the Future State Map 4.Develop your plan to get there

Current State Map • Understanding how the floor currently operates – Material and Information flows – Draw using symbols – Start with the “door to door” flow – Have to walk the flow and get actuals • No standard times • Draw by hand, with pencil and eraser – Foundation for the future state

Current State Icons Customers

Process Box Painting

Go See

Suppliers Mon., Wed., Fri. I

ShipmentTruck Inventory Push System

Operator Data Box C/T=1 sec C/O= 1 hr Rel.= 98% FPY = 95%

Cycle Time Changeover Reliability Quality

More Current State Icons

Train

Hardcopy Electronic Cell

Boat Person Plane

Fun Current State Icons ? ? ?

o

Fa x

&@#$%!

Current State Map Setup Tips •Use 11” x 17” paper, landscape •Use pencil and eraser •Draw by hand •Don’t waste time putting it on a computer just to make it look nice (non-value added time) •Practice, practice, practice Steps •Customer •Supplier •Process •Information flow •Calculate process time and lead-time

Current State Map Setup Supplier informati on

Information Flow Area

Custome r informati on

Process Flow Area

Process Time and Lead-time Area Title Block

Current State Map 2 days

PhlyeBiknight

30/60/90 Prod Ctrl Forecast MRP

Order Entry MRP

Weekly

2 Weeks

10 days

5,300 pcs/mo.

P/T = 20 min

265 pcs/day

Schedule Stamping Shared

=1

I

Deburr I

=1

C/T=1 sec

C/T=39 sec

C/O= 4 hrs

1,400

Dewey, Cheatem & Howe Daily

Daily

Spot Weld

5,425

Monthly Weekly

L/T= 2 days

Weekly Weekly

I

20 min

Assemble I

=1

1,225

=2

C/O= 11 min

C/T=17 sec C/O= 0 min

C/T=48 sec C/O= 5 min

Rel.= 98%

Rel.= 99%

Rel.= 80%

Rel.= 100%

FPY = 95%

FPY = 90%

FPY = 100%

FPY = 98%

1 sec

20.5 days

39 sec

5 days

17 sec

4.5 days

48 sec

40 days 105 sec

Future State Questions 1. What is the Takt Time? 2. Will we build to shipping or to a supermarket? 3. Where can we use continuous flow? 4. Where do we have to use supermarket pull system? 5. At what single point in the production chain do we trigger production? 6. How do we level the production mix at the pacemaker process? 7. What increment of work will we release and take away at the pacemaker process? (Leveling the volume) 8. What process improvements will be necessary? (e.g. uptime, changeover, training)

1. What is the Takt Time? • Takt means drumbeat • Ability to meet customers’ demand 

• Formula 

Takt Time =

Time Available Demand

Takt Time Calculation Time available Shift (8 hours) = 480 mins Breaks (2 x10) - 20 mins Lunch - 30 mins Meetings 5 mins C/O 5 mins Total Time = 420 mins = 25,200 sec Demand = 265 parts  Takt Time = 95 sec/part 

Takt Time Calculation • Takt Time = Demand Rate – Goal: Produce to demand with no excess capacity • Takt Time = work time available number of units sold • Assume 5 people work, sell 500 units/week: – TaktTime = (5 x 40 x 60) / 500 = 24 min/unit – Set cycle time to match personnel/operation

Exercise • Takt time calculation

Takt Time Calculation • Old requirements: 847/day * 240 workdays/yr = 203,000/yr • 10% growth = 223,600/yr • New requirements: 223,60/yr/240 workdays/yr = 931/day • Time available: 8.5 hrs/day - .5 hrs (lunch) - .33 hrs (breaks) = 7.67 hrs/day • 3,600 secs/hr * 7.67 hrs/day = 27,612 seconds/day • 27,612 seconds/day divided by 931 units/day = 29.3 secs per unit • Cycle time (actually 116 secs/unit) divided by Takt time (29.3 secs/unit) = 3.95 = 4 operators required •

Quick Changeover



Changeovers in less than 10 minutes

Quick Changeover • Factory definition – the time from the last good piece of previous run to the next good piece of new run • Office definition – the time it takes to switch from one task to a new task – Typically, in the office the time savings is not as significant as in manufacturing

2 Hour C/O – Large Batch Size 8 7 6 5 4 3 2 1 0

A Mon

B Tue

W ed

C Thu

D Fri

E

1 Hour C/O – Half Batch Size 8 7 6 5 4 3 2 1 0

B

D

A

C

E

A

C

E

B

D

Mon

Tue

W ed

Thu

Fri

10 Minute C/O – Small Batch Size 8 7 6 5 4 3 2 1 0

E

E

E

E

E

D

D

D

D

D

C

C

C

C

C

B

B

B

B

B

A

A

Mon

A

Tue

Wed

A

Thu

A

Fri

10 Minute C/O – Many Different Small Batches 8 7 6 5 4 3 2 1 0

D

D C E

B E F

B

C

A

H

C B

B Mon

D

Tue

Wed

F

A Thu

G

H Fri

A

G B

I

Changeover Summary Based on per week C/0 Time Number of 40 hours Number of Production Changeovers Production Time Runs Available

2 Hour

5

5

30 hours

1 Hour

10

10

30 hours

30 Minute 15

15

32.5 hours

10 Minute 25

25

35.8 hours

SMED • Single Minute Exchange of Dies (SMED) • Shigeo Shingo (1970) 1.Separate internal steps and external steps 2.Convert internal steps to external where ever possible 3.Streamline all steps •

4 Categories of SMED time 1. Preparation, afterprocess adjustments, checking of material and tools (30%) 2. Mounting, removing tools and parts (5%) 3. Measurements, settings and calibrations (15%) 4. Trial runs and

30%

5% 15%

50%

Typical proportions

Step 1. Separate Internal and External Times • Checklists • Functional checks • Transportation of parts and tools

Step 2. Convert Internal Time to External Time • Preparation conditions – Pre-heat, correct air pressure, stage materials

• Standardize – Centering, gripping, securing, replace fewest parts, standardize heights, standardize bolts or fasteners

• Intermediary jigs – Mounting plates

Step 3. Streamline • Parallel operations – More than one person working at the same time

• Eliminate adjustments – Markings – Scales

• Functional clamps • Mechanization

Changeover Cart Example

Before • Waste of time to find correct tools • Tools can become damaged • Waste of money for extra tools 

After • Saves time • Do not have to replace tools as often • Have what you need where its needed 

QCO and Other Building Blocks • 5S, Visual, POUS, Teams and Standard Work • VSM can discover opportunities for QCO • As Batch Size Reduction continues, QCO becomes more important • Kaizen Blitz is a great method to implement QCO • Must sustain the gains

Benefits of Quick Changeover • Shorter lead time • Less material waste • Fewer defects • Less inventory • Lower space requirements • Higher productivity • Greater flexibility • Better Teamwork

Building Blocks of Lean Continuous Improvement & Kaizen Blitz Cellular & Pull System & TPM JIT Flow Kanban Poka-yoke

Self Inspection Batch Size Reduction

POUS Layout

Standard Work

Change Management

Autonomation

Quick Changeover Visual

5S Teams

V S M

Continuous Improvement Kaizen vs. Kaizen Blitz, or Incremental vs. Breakthrough Improvements Kaizen Incremental Improvements: • Are continuous, since there is always room for improvement in any process • It is never-ending • Many small improvements throughout the enterprise • Done by individuals or small teams • Could be functional, departmental, or task-oriented • Part of the “useful many” • A little time spent on an ongoing basis • Standardization of processes (i.e., process improvement oriented) • Plan-Do-Check-Act methodology 



Continuous Improvement 

Ideas for continuous improvement could come from: – – – – – – – – –

•

Employee suggestions Corrective & Preventive actions Non-conformities, defects Customer complaints, returns Benchmarks The Lean “wastes” Variations from the standard Assessments, audits & competitive analyses Research & Development activities

Continuous Improvement & Continuous Learning

• Continuous Learning goes hand in hand with continuous improvement • Management should have training given to employees in Lean and Quality tools, problem solving and root cause analysis, the process model, concepts of Theory of Constraints, basic statistical techniques, graphical tools, etc. • Understanding of Plan-Do-Check-Act and Standardize-Do-Check-Act (SDCA) will be beneficial

Continuous Improvement & Continuous Learning

• Continuous improvement and learning: – Becomes part of daily work life – Is practiced at both personal, functional and organizational levels – Is result oriented – Is shared within the enterprise – Becomes part of institutional memory and knowledge, even after employees retire, move up/laterally or leave

Why C. I.? • Standing still is not an option: – – – – –

Competitors will overtake us Globalized economy Higher customer expectations Technical and breakthrough changes Tapping into human potential and creativity

• Improvements based on: – – – – –

Cost and cycle time reduction “Waste” minimization Defect prevention Enhancing customer satisfaction/delight Attaining competitive advantage

Kaizen Blitz

• Breakthrough strategies for lasting results

Building Blocks of Lean Continuous Improvement & Kaizen Blitz Cellular & Pull System & TPM JIT Flow Kanban Poka-yoke

Self Inspection Batch Size Reduction

POUS Layout

Standard Work

Change Management

Autonomation

Quick Changeover Visual

5S Teams

V S M

Kaizen Blitz • Kaizen Blitz is a combination of the Japanese word Kaizen for “continuous improvement” and the German word Blitz for “lightning.” It is a focused, week-long workshop where a cross-functional team reviews a process, identifies and eliminates waste, thereby achieving dramatic and tangible breakthrough (rather than incremental) improvement results. • Kaizen Blitz now stands to mean the improvement activity itself. • It is treated more as a “Project” (rather than a “Process”).

Why Kaizen Blitz? • Major benefits in a flash. • Can use benchmarking for setting goals. • Innovation has become indispensable in today’s competitive world economy. • Cycle Time Reduction translates directly to cost savings. • Kaizen Blitzes typically attack wasted time. • Positive impact on organizational culture through “breakthrough” type improvements.

Who Will be Involved? • Kaizen Blitz teams that come together for one week to implement improvements in a pre-selected bottleneck project or process. • Cross-functional teams (seven to ten persons) • Hourly and salaried personnel • Operators, engineers, supervisors, maintenance persons, managers, technical experts, material handlers, quality personnel, business support personnel, participants from the outside • Typically, the Team Leader is person with clout and is the highest stakeholder in the process who possess leadership skills, open minds, strong desire to succeed and some prior Lean experience.

Kaizen and Cycle Time Reduction • • • • 

Focus on Process. Focus on Elimination of Waste. Focus on Speed. Time improvement translates directly to cost savings and customer satisfaction.

Kaizen Blitz Steps 1.Select specific area for improvement. 2.Define current situation in measurable terms 3.Set aggressive goals (stretch goals). 4.Identify team members. 5.Conduct training on the first day of the project. 6.Do it (in three to five days).

Step 1 – Select Project • • • • • • •

Value Stream Map Bottlenecks Customer or quality related issues Interdepartmental Long lead-times or setup times Competitive advantage Cost reduction or avoidance

Step 2 – Define Current State • • • • •

Video tape Time study Flowchart Historical information Observations and interviews

Step 3 – Identify Team Members • Cross-functional teams (seven to ten persons) • Hourly and salaried personnel • Operators, engineers, supervisors, maintenance persons, managers, technical experts, material handlers, quality personnel, business support personnel, participants from the outside • Typically, Team Leader is person with clout and is the highest stakeholder in the process. Ideally, the team leader must possess leadership skills, open minds, strong desire to succeed and some prior “Lean” experience.

Step 4 – Set Aggressive Goals • Define the purpose or objective and set stretch goals. • Goals should be clearly defined and quantifiable (e.g., reduce machine set up time by 75%, increase throughput by 40%, reduce floor space by 30%). • Emphasis should be on identifying and eliminating waste, and then standardizing at the improved level. • Benchmark when possible

Step 5 – Conduct Training • Select hands-on training that is compatible with the project • Do training on the first morning • Provided by an internal or external expert

Step 6 – Do it!

• Perform in 3 to 5 days

Example 1 – Universal Joint QCO Category

Changeover

Tool Change

Target savings 4.9 hours (75%) 14.8 hours (75%) Actual savings 4.5 hours (69%) 13.8 hours (70%) Target savings $291 per day

$879

Actual savings $268 per day

$820

Total savings

$272,041 per year

Example 2 – Tube Mill SMED • Changeover savings per year: $510,000 • Reduced changeover time from 4 hours, 40 minutes to 2 hours, 11 minutes • Employees happier – bonuses based on changeovers • Management happier – more changeovers, more production, more cash in the door

How to Start and Sustain your Lean Journey

• A journey of one thousand miles, starts with a single step

8 Ways to Get Started 1.Baseline Assessment or Gap Analysis 2.Value Stream Map 3.Training in Lean 4.Basic Building Blocks 5.Kaizen Blitz 6.Pilot Projects 7.Change Management 8.OEE •

1. Baseline Assessment Baseline Assessment or Gap Analysis performed by experienced Lean experts • Use 

– – – –

Interviews Observations Process mapping Analysis of reliable data

• Create a “Gap Analysis” with focus on eliminating the Eight Wastes • Generate an Action Plan for implementing Lean improvements

2. Value Stream Mapping Value Stream Mapping • Assemble the cross functional team • Have a Value Stream Manager • Determine a Product Family • Create the Current State Map • Create the Future Stats Map • Develop the Plan to get there, tie-in with business objectives • Review the Plan, stay on course • Your Future State then becomes your Current State • Expand to Multiple Value Streams 



•

3. Training in Lean Training in Lean



• “Massive” training in Lean • Need to build a critical mass of trained employees • Perform the training just before implementation • Lean Champions should have advanced skills in Lean •

4. Basic Building Blocks • Start with one of the Basic Building Blocks of Lean • • Continuous Improvement & Kaizen Blitz TPM

JIT

Poka-yoke POUS

Cellular & Flow Self Inspection

Batch Size Reduction

Layout

Pull System & Kanban

Standard Work

Change Management

Autonomation

Quick Changeover Visual

5S Teams

V S M

Basic Building Blocks Basic Building Blocks • Start with the implementation of the Basic Building Blocks • Build up layer by layer until TPM, Cellular Manufacturing and Pull/Kanban are established • Then continuously improve using Kaizens, suggestion systems and periodic Value Stream Maps. • • 

Example – Implementing 5S • Plan – Identify 5S Champions & Teams – Decide how to rollout to entire organization – Resources required

• Train – Train just before Kaizen – Train-the-trainer

• Do • Improve & Repeat

5S Implementation Map 8 9 7 8 8 9 9 10 13 8 8 9 9 10 5 1 4 2 11 1 1 1 4 3 5 6 12 4 4

5. Kaizen Blitz Select a Kaizen Blitz project • Perform in 3-5 days • Focus on speed and elimination of waste • Can perform on “low hanging fruit” • Generates quick victories and improvements • Do not continue in an Ad-hoc approach, use your Value Stream Map 

6. Pilot Projects Pilot Projects • Implement Lean Pilot Projects where bottlenecks have been identified • Use cross-functional teams • PDCA methodology is best • Can use benchmarks and best practices for goal setting • Communicate results • Migrate lessons learned to other areas • • 

7. Change Management Change Management



• Begin with cultural Change Management before rolling out Lean • Address the human side of Lean in your three to five year Master Plan • Use internal/external change agents • Communicate the need for change: ultimately, Lean has to become integrated into daily work life • Open up channels for sharing ideas •

8. OEE Overall Equipment Effectiveness (OEE) analysis can identify where to start your Lean journey • Pareto the time spent on: 

– – – – – – – –

Breakdowns Setups Tool changes Idling time Slower speed Minor stoppages Producing defects, rework Start-up issues

• This exercise will self-identify the “biggest bang for the buck” and where to start

Plan • You must have a plan • Utilize a Steering Committee, Design Teams and Lean Champions • Tie the Lean Objectives with the Business Objectives • Commit resources (time, people, budgets)

Stages of Lean Implementation Generally, organizations can use this model for the stages of implementing Lean



• Takt – Establish takt time and meet it

• Flow – After meeting takt time, then create Flow

• Pull – Where you can’t Flow, Pull

How to Sustain Lean? • Lean will not be sustainable without proper training in Lean and satisfied employees • Internalize into daily work • Understand that it is a never-ending process or philosophy: no turning back • Create discipline/motivation/incentives • Standardize so as not to slip back

How to Sustain Lean? • Continued, visible management commitment • Open communication channels • Emphasize accountability • Use Lean performance metrics • Role of Lean champions • Job rotation 

How to Setup the Lean Team

• Steering Committee • Design Teams • Champions

Lean Team Roles & Responsibilities Design Team 5S, Visual, POUS Design Team

Champions

Lean Steering Committee

Cellular Design Team

Champions

HPT Design Team Pull/Kanb an Design Team

Champions

Steering Committee Roles & Responsibilities • Set the Lean policy • Provide resources – time, people, Lean Steering budgets & remove barriers Committee • Develop and share the Lean Vision • Develop the Communication Plan and then deploy it • Members usually • “Walk the talk” everyday and fully from top support the Lean initiatives management, but can include “Value • Determine the Design Team makeAdders” up and members • Review the work of the Design Teams 

Design Teams Roles & Responsibilities • Deploy the Lean policy • Determine the resources required – Time, people, budgets, etc • Determine the best way to implement the Lean Building Blocks in your organization • Report to the Steering Committee on progress • Support your Lean Champions 

Design Team

• Members usually from management or “Value Adders” • Group like Building Blocks together

Design Team Agenda • Design Teams decide how • Design Teams may change Lean will be implemented over time at their facility – At first they oversee • Take into account: the implementation plan – Organizational Culture – Then they support the sustaining – Change management efforts – Resources – They may disband, – Current skills & be absorbed into needed skills another Design – Size and timing of Team or morph projects into a new design Team – Metrics & Goals

Lean Champions Roles & Responsibilities • Deploy the Lean policy via training, implementation and Kaizen Blitz • Feedback information to the Design Team on progress • Be given the time to support the Lean efforts • Make presentations and communicate the results of the Lean projects 

Champions

• Members usually from management or “Value Adders” • Motivated to learn, lead and improve their organization

Champion’s Agenda • Be ready to commit time to Lean projects • Be willing to learn and continually improve • Become a Lean content expert • Have skills in training, public speaking, project management and be a team

WIIFM



• Gain new skills • Valued by the organization • Exciting, new assignments • Learn other aspects of Lean

Multi-facility Deployment Example Small Facility Lean Steering Committe e Design Team/ Champio ns

Organizat ion Lean Steering Committe e

Desi gn Tea m

Desi gn Tea m Champions

Large Facility Lean Steering Committe e Desi Desi gn gn Tea Tea m m

Momentum • Have to build a “critical mass” of employees trained in Lean and apply principles • Build “buy-in” and get people onboard • “Bandwagon” affect 

Organizational Alignment

Dealing with Objections to Lean • Put yourself in their shoes • Help answer “WIIFM” • Communicate, communicate, communicate and then communicate some more! • Create an “Elevator Speech” •

Getting People on Board se i d a r a P Lean

!

?

Status Quo Land

Lean Enterprise vs. Lean Manufacturing

• Taking Lean beyond the shop floor

Lean Enterprise • Move from the shop floor to Enterprise-wide Lean implementation • Many of the Building Blocks are essential for efficient office functions – 5S, Visual, POUS, Standard Work, Layout, Self Inspection, Pokayoke • The goal is to reduce or eliminate the wastes to reduce lead times and to enhance responsiveness, competitiveness and customer satisfaction •

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