7 a New Look at Criticality Analisys for Machinery Lubrication

Maintenance and Reliability

AS I SEE IT

JIM FITCH  FITCH   NORIA CORPORATION

A New LOOK at CRITICALITY Analysis for Machinery LUBRICATION For decades, reliability scholars have been stressing the importance of prioritizing new maintenance thrusts thrust s and investments based on need. The word they like to use is “criticality.” For any given machine, how critical is its reliability? What if it failed suddenly and catastrophically? What would be the consequences — lost production, expensive repairs, fatality? Criticality is the logical starting point for all reliability initiatives.  There are many different ways to enhance reliability and improve the quality of mainteFigure 1. Machine Criticality Factor (MCF) (Relates to the consequences of machine failure)

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nance. The T he best options should be risk-based. After all, if it doesn’t reduce risk, why do it? Why spend an incremental dollar to enhance a machine’s reliability if it doesn’t yield multiple dollars in return?  There’s also priorit priority. y. What should be done first, second and third, and what should not be done at all? How do you know which machines return big dollars for enhanced reliability, which machines return marginal dollars and which machines return nothing at all? Once you understand machine criticality

and a machine’s risk profile, you can work smarter to customize improvements. For guidance, look to the Pareto principle, which states that 20 percent of the machines cause 80 percent of the reliability problems. Which machines are these? In addition, consider that 20 percent of the causes of failure are responsible for 80 percent of the occurrences of failure. Which causes are these? It’s about precision — precision maintenance and precision lubrication. It’s also knowing how to make wise, risk-informed choices.

Machinery  achinery  i ry 

L ubrication  Lubrication  b ic io  PUBLISHER

Mike Ramsey - [email protected] GROUP PUBLISHER

FAILURE OCCURRENCE FACTOR (FOF) FAILURE OCCURRENCE FACTOR

Brett O’Kelley - [email protected]

METHOD A. MACHINE RELIABILITY HISTORY IS KNOWN

Never

Machine has long history, has never been k nown to fail and is showing no signs of impaired reliability.

2

Ver y Rare

Machine is highly reliable, and past failures have been extr emely rare (15+ years of service life).

3

Rare

Machine can go more than 10 years without failure.

Infrequent

Machine has been known to fail but only af ter 5 or more years.

1

4 5

Occasional

Failures are likely after 3 to 5 years’ service life.

7

  Somewhat Frequent

Failures tend to occur after 2 to 5 years’ service life.

8

Frequent

Failures tend to occur after 1 to 3 years’ service life.

  Very 9 Frequent 10

SENIOR EDITOR

 Jeremy Wright - jwr ight@nor ia.com Wes Cash - [email protected] Bennett Fitch - bfi[email protected] Complete The Reliability  Elements Qu otient 

Chronic and Failures are expected in less than 1 year’s Certain service life.

Figure 2. Use this table t o determine the Failure Occurrence Factor, corresponding to the probability of failure.

I’ve written previously about the Optimum must be equally low (extreme reliability). It is the Reference State (ORS). This is the prescribed only practical means to hedge risk. Those responstate of machine configuration, operating condi- sible for maintenance usually have little control tions and maintenance activities required to over the consequences of failure (often limited achieve and sustain specific reliability objectives. only to early detection technology). However, reliAs stated, defining the ORS requires a definition ability maintainers frequently have considerable of the specific reliability objectives for a given control over the probability of failure. Indeed, you machine. Defining the reliability objectives can use risk and criticality to develop a master demands an understanding of failure modes and plan for lubrication-enabled machine reliability. machine criticality.  This will be the focus of this article.  This reminds me of the plant manager who Let’s begin with a list of common lubricatold me years ago that he decided the best way tion and oil analysis decisions (all attributes to solve his lubrication problems was to put of the ORS) that can be customized (optisynthetic lubricants in every machine. Do you mized) by understanding failure modes and think he got the result he sought? Does paying a machine criticality: premium for synthetics guarantee a premium • Lubricant selection, e.g., premium vs. econreturn in machine reliability and maintenance omy-formulated lubricants cost reduction? Do synthetics offer forgiveness • Filtration, including things such as filter for negligent and shoddy maintenance? Is this quality, pore size, capture efficiency, location wise decision-making? and flow rate

 The probability of machine failure needs to be inversely proportional to risk. There’s no better example than commercial aviation. Because the consequences of failure are extremely high (death), the probability of failure

 Jason Sowa rds - jsowards@no ria.com

TECHNICAL WRITERS

Failures occur frequently in 0.5 to 2 years’ service life.

Understand the Reliability-Risk Connection

EDITOR-IN-CHIEF

 Jim Fitch - jfitch@no ria.com

Failures can occur in the time range of 3 to 8 years.

  Common and Likely

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METHOD B. MACHINE RELIABILITY IS UNKNOWN

• Lubricant preventive maintenance (daily PMs)

and inspection strategy  • Lubricant delivery method selection and use

CREATIVE DIRECTOR

Ryan Kiker - rk [email protected] GRAPHIC ARTISTS

Steve Kolker - [email protected]  Julia Backus - jback us@noria .com  Terry Kellam - tkella [email protected]  ADVERTISING SALES

 Tim Davidson - tdav idson@nor ia.com 800-597-5460, ext. 224 MEDIA PRODUCTION MANAGER

Rhonda Johnson - [email protected] CORRESPONDENCE

 You may address art icles, case studi es, special requests and other correspondence to: Editor-in-chief MACHINERY LUBRICATION Noria Corporation 1328 E. 43rd Court • Tulsa, Oklahoma 74105 Phone: 918-749-1400 Fax: 918-746-0925 E-mail address: [email protected]

MACHINERY LUBRICATION Volume 13 - Issue 2 March-April 2013 (USPS 021-695) is published bimonthly by Noria Corporation, 1328 E. 43rd Court, Tulsa, OK 74105-4124. Periodicals postage paid at Tulsa, OK and additional mailing offices. POSTMASTER:  Send address changes and form 3579 to MACHINERY LUBRICATION, P.O. BOX 47702, Plymouth, MN 55447-0401. Canada Post International Publications Mail Product (Canadian Distribution) Publications Mail Agreement #40612608. Send returns (Canada) to BleuChip International, P.O. Box 25542, London, Ontario, N6C 6B2. SUBSCRIBER SERVICES: The publisher reserves the right to accept or reject any subscription. Send subscription orders, change of address and all subscription related correspondence to: Noria Corporation, P.O. Box 47702, Plymouth, MN 55447. 800-869-6882 or Fax: 866-658-6156. Copyright © 2013 Noria Corporation. Noria, Machinery Lubrication and associated logos are trademarks of Noria Corporation. All rights reserved. Reproduction in whole or in part in any form or medium without express written permission of Noria Corporation is prohibited. Machinery Lubrication is an independently produced publication of Noria Corporation. Noria Corporation reserves the right, with respect to submissions, to revise, republish and authorize its readers to use the tips and articles submitted for personal and commercial use. The opinions of those interviewed and those who write articles for this magazine are not necessarily shared by Noria Corporation. CONTENT NOTICE: The recommendations and information provided in Machinery Lubrication and its related information properties do not purport to address all o f the safety concerns that may exist. It is the responsibility of the user to follow appropriate safety and health practices. Further, Noria does not make any representations, warranties, express or implied, regarding the accuracy, completeness or suitability, of the information or recommendations provided herewith. Noria shall not be liable for any injuries, loss of profits, business, goodwill, data, interruption of business, nor for incidental or consequential merchantability or fitness of purpose, or damages related to the use of information or recommendations provided.

(e.g., circulating, auto-lube, mist, etc.) • Oil analysis (which machines are included

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AS I SEE IT

• Oil sampling frequency (weekly, monthly, quarterly, never) • Laboratory and test slate selection • Oil analysis alarms and limits

All of these decisions and activities must be within the scope of the Optimum Reference State. For this reason, the importance of criticality should not be taken lightly. However, a practical means of assigning a value to criticality, customized to machine lubrication and tribology, has largely been elusive. In fact, the fields of lubrication and tribology raise unique issues and questions related to criticality that aren’t typically addressed and aren’t common to other types of machinery.

Calculating Overall Machine Criticality Overall Machine Criticality (OMC) is a risk-profile assessment that can be calculated to a single numerical value. The OMC is what you seek to know and control. The lower the OMC, the lower the risk. The OMC is the multiplied product of two factors: the Machine Criticality Factor (MCF) and the Failure Occurrence Factor (FOF). The MCF relates to the consequences of machine failure, which combines both mission criticality and repair costs, while the FOF relates to the probability of machine failure. This probability is highly influenced by maintenance and lubrication practices and therefore is far more controllable.

Machine Criticality Factor A simple method for estimating the Machine Criticality Factor is shown in Figure 1. It requires an understanding of mission criticality Figure 3. An example of a pre-ORS Reliability Elements Quotient.

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and repair costs. While you could call these SWAGs (educated guesses), it is far better to guess using a logical method than to apply dartboard science or do nothing at all.  The MCF is scaled 1 to 10, with 10 corresponding to extreme criticality (high risk). You start by answering the question of mission criticality. Machines that are process-critical can accumulate huge production losses as a result of sudden and prolonged failure. Extremely high mission criticality relates to safety (injury or death). In the event there is minimal business interruption or safety risk, there might still be high repair costs. Although many processes have redundant systems or standby equipment in the event of failure, these systems don’t mitigate the cost of repair, which can be millions of dollars in some circumstances.  The final consideration is the current or potential use of early detection technology (predictive maintenance) to annunciate alarms of impending or precipitous failure events. In such cases, both downtime and the cost of repair can be substantially reduced. Oil analysis (wear debris analysis), vibration analysis, bearing metal temperatures, proximity probes, motor current, etc., are all technologies that can offer real benefit in reducing the Machine Criticality Factor (see the adjusted scale at the bottom of Figure 1, which applies only if effective early warning systems are used).

Failure Occurrence Factor As mentioned previously, the Failure Occurrence Factor relates to the probability of machine failure. This can be estimated from the machine’s failure history or statistical analysis of a group of identical machines. Machines that are inherently prone to failure

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AS I SEE IT

MACHINE CRITICALITY FACTOR

    R     O     T     C     A     F     E     C     N     E     R     R     U     C     C     O     E     R     U     L     I     A     F

1

2

3

4

5

6

7

8

9

10

1

 

1

2

3

4

5

6

7

8

9

10

2

 

2

4

6

8

10

12

14   16

18

20

3

 

3

6

9

12

15

18   21

24   27

30

4

4

8

12

16

5

5

10

15

20   25

6

6

12

18   24

7

7

14   21

28

8

8

16   24

32   40

9

9   18

10   10

27   36

20   30

40

20   24

32   36

35   40

40

45

50

48

54

60

49

56

63

70

48

56

64

72

80

45

54

63

72

81

90

50

60

70

80

90

100

30

30

28

36   42

35   42

(bad actors) get the highest rating on a scale of 1 to 10. High FOFs usually correspond to extreme and chronic conditions (see the table in Figur e 2). If you have good historical knowledge of the machine’s reliability, then use the descriptive rating scheme (Method A) under the “Machine Reliability History is Known” heading. If machine reliability is unknown or uncer tain, go to the Reliability Elements Quotient (REQ) in F igure 3 (Method B). This is a scoring system that shows what causes and controls failure in lubricated machines. Most importantly, it reveals the fundamental strategy for optimizing machine reliability.

Reliability Elements Quotient  The REQ (Figure 3) tallies five critical elements to arrive at a customized composite score that will be used for the FOF in Figure 2. It gets down into the weeds of what causes a greater or lesser likelihood of machine failure. Let’s discuss these elements, starting at the top and working our way down. • Machine Duty - Machine duty is a compilation of operational conditions that can induce premature machine failure. Machines that score high are those that run at or beyond rated loads (catalog loads), operate at high pressure, run at high speed, are exposed to high shock loads or duty cycles, and have other similar mechanical conditions. • Lubricant Quality/Performance -  Good lubricant selection extends machine life, while poor lubricant selection shortens it. The benefit of good lubricants not only reduces friction and wear but can also protect the machine from corrosion, air entrainment, deposit formation and lubricant starvation. Therefore, lubricant quality directly influences the probability of failure. • Lubrication Effectiveness - More machines fail due to poor lubrication than poor lubricants. Lubrication relates to a range of activities and conditions including relubrication frequency, relubrication method, controlling lubricant levels, lubrication procedures, inspection methods and contamination control. For most plants, there is a large gap between doing lubrication and doing lubrication right. 6 | March - April 2013 | www.machinerylubrication.com

Color

Risk  

Remediation Required

Red

Extreme Risk 

Immediate

Amber

High Risk

High Priority

 Yellow

Manageable As Soon as Risk  Possible

Gre en

Minor Risk  

Continuous Improvement

Blue

Low Risk

None

Figure 4. The Overall Machine Criticality (OMC) matrix includes the Machine Criticality Factor on the X-axis, the Failure Occurrence Factor on the Y-axis and fiv e risk zones, each represented by a different color.

• Fluid Environment Severity -  This is largely contamination

control related. Contamination compromises the quality of the lubricant and the state of lubrication. It relates to what the machine is exposed to in its work environment (and the severity of exposure), plus the effectiveness of the machine in excluding and removing contaminants from the lubricant. Machines that are bombarded with dirt, water, corrosive materials, ambient heat/cold and process chemicals have high fluid environment severity. • Early Warning Systems - Early warning technology also

impacts the probability of failure. This is done by catching incipient failures or root-cause conditions that are the precursors to failures. Oil analysis and comprehensive daily machine inspections are extremely effective at providing early warning to a host of problems.  The Reliability Elements Quotient is a scorecard that counts all five factors. For each element, the score range goes left to right, from very low (far left) to extremely high (far right). The numerical scale changes for each factor. The best way to use the REQ is to circle the assigned score for each factor and then write the score in the box to the right. The total score is tallied at the bottom. In the example, this total is 8, which designates high failure probability.

Overall Machine Criticality Matrix and De-Risking Your Plant  The OMC is probably best viewed as a matrix. This is shown in Figure 4 with the MCF on the X-axis and the FOF on the Y-axis. The intersecting box reveals the OMC value (multiplication of the MCF and the FOF). The matrix has five color zones which are actually risk zones (the location of these zones on the grid can be customized). The highest risk is represented by the color red. Next is amber, followed by yellow, then green and finally blue (low risk). Machines that fall in the amber or red zones are targeted for immediate remediation. This is best done by reducing risk values from one or more of the four “addressable” reliabilit y elements (see Figure 3), which are subcomponents of the FOF. These are lubr icant

quality/performance, lubrication effectiveness, fluid environment severity and effectiveness of early warning systems.  This is exactly the purpose of the Optimum Reference State. Figure 5 shows how key ORS performance attributes influence the addressable reliability elements that in turn influence Overall Machine Criticality. Everything is connected. Additionally, failure modes and effects analysis (FMEA) can be used to assign priority to ORS attribute improvements. For more information on FMEA as it applies to machinery lubrication, see http://www.machinerylubrication.com/Read/17/fmea-process. It makes sense that all reliability initiatives need to adjust (improve) the OMC. This typically involves a range of modifications to the ORS performance attributes as shown in Figure 5. These can include machinery modifications, lubricant selection changes, people skills improvements, procedure modifications and others. “Optimizing” the modification master plan through FMEA and

criticality analysis achieves the lowest risk profile or OMC at the lowest possible cost. An example of this is seen in Figures 6 and 7. By making modifications to lubricant selection, lubrication methods, contamination control and oil analysis, the Failure Occurrence Factor improved from 8 to 1. For a machine that has a Machine Criticality Factor of 5, this brought the risk profile down from 40 (amber, high-risk zone) to 5 (blue, low-risk zone).

What It All Means In the January-February 2013 issue of Machinery Lubrication, I wrote about the Technology Adoption Cycle and the impediments to adoption of the Optimum Reference State. People, especially managers, “go with what they know.” If they don’t understand risk and reward as it relates to machine reliability, they will shy away from acceptance and adoption. The state of lubrication continues “business as usual.”  This is a curse indeed, but one that can be remedied.

Figure 5. This table shows how the ORS perfor mance attributes directly influence the elements in the Reliability Elements Quotient (REQ).

 = Major Influence

= Minor Influence

ADDRESSABLE RELIABILITY ELEMENTS

 = Moderate Influence ORS PERFORMANCE ATTRIBUTES Lubricant Attributes

Optimum lubricant products and supplier selection

Lubrication Attributes

Optimum selection of oil change and regrease intervals

MACHINE DUTY*

LUBRICANT QUALITY/ PERFORMANCE

LUBRICATION EFFECTIVENESS

FLUID ENVIRONMENT SEVERITY

EFFECTIVENESS OF EARLY WARNING SYSTEMS

Lubricant reception, labeling, packaging, storing and handling

Optimum selection, documentation and use of lubrication and oil analysis PMs, tasks and procedures Machine Attributes

Proper selection and location of filters Correct selection and location of oil level gauges and inspection sight glasses Correct selection and location of sampling valves

Optimum selection of br eathers and headspace management devices Correct machine relubrication and flushing hardware and tools Optimum selection and use of seals and leakage control devices Optimum selection and use of seals to control contaminant ingression Oil Analysis Attributes People and Program Management Attributes

Oil analysis program design and execution Awareness training, skills training, competency  testing Optimum use of lubrication program metrics and KPIs Optimum program management, data management, work management systems

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* OMC=MCF x FOF

MACHINE CRITICALITY FACTOR

    R     O     T     C     A     F     E     C     N     E     R     R     U     C     C     O     E     R     U     L     I     A     F

1

2

3

4

5

6

7

8

9

10

1   1

2

3

4

5

6

7

8

9

10

2   2

4

6

8

10

12

14   16

18

20

3   3

6

9

12

15 1

18   21

24   27

30

4   4

8

12

16

20 2   24

32   36

40

5

5

10

15

20   25 2

6

6

12

18   24

7

7

14   21

28

8

8

16   24

32   40

9

9   18

10   10

27   36

20   30

40

35   40

POST-ORS

Machine Criticality Factor (MCF)

5

5

Failure Occurrence Factor (FOF)

8

1

Machine Duty

3

3

Lubricant Quality/Performance

2

1

Lubrication Effectiveness

1

0

Fluid Environment Severity

3

0

45

50

48

54

60

-3

56

63

70

Effectiveness of Early Warning   Systems

-1

49

48

56

64

72

80

Overall Machine Criticality (OMC)*

40

5

45

54

63

72

81

90

OMC Zone

Amber

Blue

50

60

70

80

90

100

OMC Risk 

High Risk

Low Risk  

30 3

30

28

PRE-ORS

36   42

3 35   42

Figure 6. This OMC matrix illustrates how improvements in lubricant selection, lubrication methods, contamination control and oil analysis brought a machine’s risk profile down from 40 to 5.

An excellent place to start is by developing a current risk profile of your critical machinery (pre-ORS). This reveals the opportunity and all the low-hanging fruit that no one has seemed to notice. Optimum is undefinable without understanding risk. By using the tools described here, you not only can understand risk (criticality and occurrence), but you can also have a solid plan for r emediation to de-risk your plant. Don’t fail to capitalize on the riches (collect the fruit) that can be gained by transformation to the Optimum Reference State.

Figure 8. Illustration of how bringing a machine to the Optimum Reference State can reduce risk.

About the Author Jim Fitch has a wealth of “in the trenches” experience in lubrication, oil analysis, tribology and machinery failure investigations. Over the past two decades, he has presented hundreds of courses on these subjects. Jim has published more than 200 technical articles, papers and publications. He serves as a U.S. delegate to the ISO tribology and oil analysis working group. Since 2002, he has been director and board member of the International Council for Machinery Lubrication. He is the CEO and a co-founder of Noria Corporation. Contact Jim at jfi[email protected].

Figure 7. This post-ORS Reliability Elements Quotient shows how the Failure Occurrence Factor improved from 8 to 1 after several modifications were made.

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