Downtime Analysis in Sugar Industry

2321-7871

Weekly Science Research Journal

Vol-1, Issue-14, 24th October 2013

Primary Article

Down Time Analysis In Process Industry-A Case Study Dnyaneshwar R.Thawkar

ABSTRACT The growths of present day industries are forced towards the use of more complex system. The production system consists thousands of parts and components and the failure of one or more component may lead to affect the entire production system. So with increase in automation and usage of complex systems, evaluation of reliability has recently been recognized for effective maintenance. Reliability has been evaluated mostly for electronic components since and presently we are going to calculate Reliability for components in process industry. For this purpose, the break down time is calculated from sugar Industry. The data to be analyzed and reliability is calculated for each component by weibull distribution in probability is analyzed and criticality of each component is found by using FMEA (Failure Mode Effect Analysis) software to suggest some of the preventive maintenance schedules. Keywords:Reliability, Weibull, Availability, MTBF, FMEA. 1.0 INTRODUCTION The study was carried in sugar mills limited is situated NAGAPP ATTINAM district in Tamil Nadu. The crushing capacity of the plant is 3500 TCD (Tones of cane Crushed per day). The various processing sections of the factory are namely a) Loading section b) Mill section c) boiling section. The preliminary discussion with the official's concerned reveal that the plant is often giving rise to problems due to breakdown of various components; and hence, it is decided to carry out failure analysis in this industry, and to suggest measures to improve the availability of the components The objective of the study is to estimate the availability, reliability of the components system and also to perform the FMEA analysis to identify the critical components to prepare PM (Preventive Maintenance) schedule by officials. 1.1 METHODOLOGY The methodology followed to achieve is as follows: 1.The historical failure data, the down time and the availability of the equipment is collected. 2.From the past failure data, the down time and the availability of the equipment is calculated. 3.Weibull statistical distribution is used to model the failure history. 4.Using the parameters of weibull distribution the estimation of reliability has been carried out. 5.Using FMEA software package, the criticality index of all components is calculated. 6.The maintenance schedules are prepared in such a way that the system will operate at or below minimum failure rate. 1.2 MEAN TIME BETWEEN FAILURES (MTBF) The mean time between failures refers to average time of breakdown until the device beyond Repair. The mean time between failures is one of the Page No-1

Dnyaneshwar R.Thawkar From Asst. professor M.Tech.(Industrial Engineering) Umrer college of Engineering, Umrer The Article is published on October 2013 issue & available at www.weeklyscience.org DOI: 10.9780/ 2321-7871/1142013/42

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Down Time Analysis In Process Industry-A Case Study useful terms in maintenance and reliability analysis. Operating Time MTBF = _______________ Number of failures 1.3 DATA COLLECTION Failure data of the plant are collected refers to average time of breakdown until the device beyond repair. The mean time between failures is one of the useful terms in maintenance and reliability analysis. MTBF = Operating Time Number of failures. 1.4 AVAILABILITY It is doable to outline 3 sorts of availableness reckoning on the time parts we have a tendency to soak up to consideration. These are,Inherent availableness is that the chance that a system or instrumentation shall operate satisfactorily once used below expressed conditions in a perfect support settingwithout consideration for any schedule or preventive maintenance at any given time .deliver the goods availableness within the definition of inherent availableness we have a tendency to thought-about MTBF that doesn't take in to account the period caused by maintenance. If this can be conjointly taken into consideration, we get the achieved availableness, that is outlined to the chance that a system or instrumentation shall operate satisfactorily once used below expressed conditions in a perfect support environment at any given time. If any real time operation, we have a tendency to can't scale back body period and provide downtime to zero. a definite quantity of delay can continually be caused by time parts like these, and if they're taken in to account it. Operational Availability of the system be the probability that a system or equipment shall operate satisfactorily and in an actual supply environment at any given time. MTBF A0 = _____________ MTBF + MDT Where MTBF Mean Time Between Failures, MDT Mean Down Time 1.5 ESTIMATION OF OPERATIONAL AVAILABILITY Downtime of Components Downtime is the non-productive time of the machine. Downtime of the components are calculated and tabulated with the help of the data collected. Table 4.2 shows the downtime of the various components from March'04 to May'04. For example, the downtime of the CANRCARRIER during March'04 is observed to be 6.45 hrs: min, which is the sum of the breakdown hours on various occasions during the month of March'04. Similarly for all other components for various periods, the want of cane time are calculated and tabulated. Table 4.3 presents the data with respect to the number of failures for each component month wise. 1.6 RELIABILITY ESTIMATION Definition of Reliability Reliability, which is a measure of quality, is an essential element at each stage of the equipment manufacturing procedure through design and production to final delivery to the user. Reliability, It is simplest form, means the probability that a failure may not occur in a given time interval. A more rigorous definition of reliability is a follows “Reliability of a unit (or product ) is the probability that the unit performs its intended function adequately for a given period of time under the stated operating conditions or environment”. Reliability characteristics, such as probability of survival, mean time to failure, availability, mean down time and frequency of failures are some of the measures of system effectiveness. Apart from the above factors, reliability does change due to other factors like quality, workmanship, manufacturing process, material, storage, handling, engineering changes, and deviations in production, inspection and test.

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Vol-1, Issue-14, 24th October 2013

2321-7871 Down Time Analysis In Process Industry-A Case Study

Application of Weibull Distribution In 1951, Weibull suggested a simple empirical expression, which represents a great varies of actual data. The weibull cumulative distribution function is given by -(t – ë / á)â F(t) = 1-e t > ë, â > 0 = 0, otherwise Where , á – Scale parameter â – Shape factor ë – Location factor There various functions are given as R (t) = Reliabilities = exp[-(t- ë) / á) â] ë (t) = Failure rate = â] / á ((t- ë) / á) â-1 The constants appearing in these expressions represent. MTBF of components Mean Time Between Failures is referred to as the average time to satisfactory operation of the system. This term is useful to carryout the maintenance and reliability analysis. Operating time MTBF = ________________ No. of failures Total Available Time – Non-operating time = _______________________________________ No. of failures For example: Component Name Total available time

= Cane Carrier = (31+30+31) x 24 hrs = 2208 hrs. Non-operating time = Total breakdown time of cane carrier = 13.00 hrs:min[FromTable 4.2] Number of Failures= 10[From Table 4.3] 2208- 13.00 MTBF =

2208 – 13.00 _____________ 10 = 219.50

Mean Downtime The statistical mean of downtime d1, d2,d3, …….. including supply time and administrative downtime is called mean downtime. This mean downtime is concentrated on breakdown time maintenance time and non-availability of components Table 4.5 shows the mean downtime of various components. For Example: Month Component Downtime due to Breakdown General down time Total down time

= March'04 = Cane Carrier = 13.00 hrs: min [Table 4.2] = 156.40 hrs: min [Table 4.4] = 13.00 + 156.40 = 163.25 hrs: min

Mean down time = 163. 25+ 71.00 + 179.50 _____________________ 3 = 138.32 hrs.

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Vol-1, Issue-14, 24th October 2013

2321-7871 Down Time Analysis In Process Industry-A Case Study

Availability of components It is possible to define three types of availability of an equipment hours in actual environments operational availability is defined as to be the probability that a system of equipment shall operate satisfactorily when used under stated condition in an actual environment at any given time. A0

Mean time between failure = ____________________________ Mean time between failure + Mean Down Time

For Example: Component Name MTBF MDT

= Cane Carrier = 219.50 hrs = 138.32 hrs

Mean down time

219.50 = ________________ 219.50 + 138.32 = 61.34%

Thus Availability of all components is calculated and tabulated in the TABLE 4.6 ã – Locating constant defining the starting point or origin of the distribution ã can be thought as a gurantee period in which no failure can occur or it can be thought of as the minimum life. á – Scaling constant, stretching the distribution along the time axis. â – Shape parameter, which decides the shape pattern of failure. When dealing with failure rates, the weibull shape parameter â is special importance as it describes the mode of failure. For example, if â < 1, it indicates that the failure rate is a decreasing function of time and is characterizes as an early failure phase. â =1, it means the failure rate is constant overtime, as is the case for exponential distribution. â > 1, it means that the failure rate is increasing with time and can be characterized as the out phase. 1.7 FAILURE TIME DISTRIBUTION: CALCULATION PROCEDURES The following procedure is adopted to calculate the required parameters. i) Class interval Tmax – Tmin I = ____________________ 1 + 3...31og N Where, T max – max. Time between failures T min – min Time between failures N – Total number of failures in the test time ii) Percentage of failure Number of failures in the time, interval % failed = ___________________________________ Total Number of failures iii) Cumulative percentage of failure n F(t)= Ó fi Page No-4

Vol-1, Issue-14, 24th October 2013

2321-7871 Down Time Analysis In Process Industry-A Case Study I =1 n – Corresponding time interval sequence number. iv) Reliability R (t) Reliabilities = exp [-(t-ã) / á)â] REALIABILITY OF COMPONENTS COMPONENT NAME: CANE CARRIER From Weibull Graph á = 1410 â = 1.8 ì/ á = 0.888 Therefore ì = 1252.08 hrs T=ì+ã = 1252.08+ 0 = 1252.08 hrs. R (t) = exp [- (1252.08-0) /- 1410) 1.8]* 100 = 44.6%

Thus Reliability is calculated for each component and it is tabulated in the TABLE.5.1. From calculation of Reliability for all components it is found that New boiler has low Reliability 1.8 FMEA ANALYSIS AND PROCESS The following logical steps should be followed when an FMEA, 1.Identify the product or system components. 2.List all possible failure modes of each component. 3.Set down the effects that each mode of failure would have on the over all function of products system. 4.List all the possible causes of each failure mode. 5.Asses numerically the failure modes on a scale from 1 to 10. 6.Experience and Reliability data from company is given a input to determine the values, on a scale 1-10 for severity (S), Occurrence (O) 7ecion (D). SEVERITY (S) Severity is the assessment of the seriousness of the effect of potential failure of system, subsystem or component severity is applicable only to effect of failure mode severity is rated by ranking by which 1 is for no effect and 10 for the most severe (serious) effect. OCCURRENCE (O) Occurrence is the probability that one of the specific cause/mechanism of failure will occur.The likelihood of occurrence is assessed as 1 for least chance of occurrence and 10 for highest Chance of occurrence. DETECTION (D) It is the relative measure of difficulty of detecting the failure before the product or service is used by customer. If the design control certainly detect cause/mechanism of failure then it is ranked or it is difficult to detect then it is ranked. Thus when these inputs are given, the results generated from the software are tabulated in the table 6.1. The criticality index for each component is generated and ranked according to the critical failure modes. This indicates the relative priority of each failure mode and to concentrate on preventive activity of critical components. 1.9 CONCLUSION Availability of data regarding the equipment Reliability is of considerable benefit to industry in many situations. Knowledge of life expectancy and wear out characteristics of the system components leads to the development of sound Maintenance and appropriate provision for spare parts and stand by equipment. It is possible to correlate equipment Reliability withmaintenance requirements. Machines made by man, at any time succumb to fail. To attain maximum productivity it is necessary that man minimize failure. This can be achieved by proper Page No-5

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Down Time Analysis In Process Industry-A Case Study maintenance and timely replacements of some parts of machines or at times the whole equipment. The timely replacement improves the machine Reliability as well as Availability and made it useful for a achieving high productivity. An attempt had made in this thesis to study the failure pattern and down time of the components. The critical components have also been identified by carrying out FMEA analysis. It would be economical if the failures of these critical components are minimize by proper preventive maintenance measures. 2.0 REFERENCES 1.Govil. A.K. (1983), Reliability Engineering, Tata, Mcgraw Hill Company Ltd., New Delhi. 2.Lewis W.W.(1987),” Introduction to Reliability Engineering”, John Willey & sons, Newyork. 3.Malik M.A.K(1979),” A note on the physical Meaning of the Weibull Distrubition”, IEEE Trans. On Reliability, Vo 1. 24, No.1, Page:95. 4.Sinha S.K.(1980),” Life Testing And Reliability Estimation”, Willey Eastern Limited, India. 5.Srinath. L., “Reliability Engineering” . Balagurusamu E.,” Reliability Engineering”. TABLE 4.7 : VALUE OF TMAX AND TMIN Sr. No. 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

NAME OF THE COMPONENT CANE CARRIER MILLS RAKE/INTER CARRIER BAGASSE CARRIER NEW BOILER ELECTRICALS OLD BOILER LOW PRESSURE BOILER POWER TURBINE OTHER UNITS IN BOILER RAW JUICE PUMP EVAPORATOR PAN SYRUP STORAGE TANK OTHER UNITS IN BOILING HOUSE

TMAX (HRS) 601.45 44.20 395.20 568.45 1478.00 1313.25 767.00 785.75 881.45 1541.40 819.00 776.15 1132.60 943.45 522.20

T MIN (HRS) 39.15 1.50 0.30 32.00 9.00 14.30 1.25 267.15 153.00 14.35 1.05 1.15 0.45 9.30 27.20

Table 4.1: Failure Data (fro example) Data Wise – March “04” DATE 02.03.04 03.03.04 04.03.04 05.03.04

FROM 7.25 8.40 --8.30 9.25 9.50

TO 7.45 9.15 --8.55 9.40 16.50

TOTAL HOURS 0.20 0.35 --0.25 0.15 7.00

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REASON To reduce Juice Level in the Evaporator To reduce Juice in the evaporator Holiday Holiday Boiler water Scarcity Kicker Jamming 11nd mill top roller shell circumference crack.

Vol-1, Issue-14, 24th October 2013

2321-7871 Down Time Analysis In Process Industry-A Case Study TABLE 4.2 : DOWN TIME OF COMPONENTS S.NO.

NAME OF THE COMPONENT

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

CANE CARRIER MILLS RAKE / INTER CARRIER BAGASSE CARRIER NEW BOILER ELECTRICALS OLD BOILER LOW PRESSURE BOILER POWER TURBINE OTHER UNITS IN BOILER RAW JUICE PUMP EVAPORATOR PAN SYRP STORAGE TANK OTHER UNITS IN BOILIBG HOUSE

MARCH (HRS) 6.45 10.25 3.45 0.45 63.25 0.30 2.00 -8.45 2.55 9.00 1.45 5.00 2.15 1.30

APRIL (HRS) 5.10 6.25 4.35 4.15 -2.05 2.05 2.50 0.25 -2.45 0.15 -1.30 2.05

MAY (HRS) 1.05 1.35 2.30 0.40 0.30 3.15 1.10 0.55 1.10 0.55 1.55 1.55 6.25 2.55 3.20

TOTAL (HRS) 13.00 18.25 10.50 5.40 63.55 5.50 5.15 3.45 10.20 3.50 13.40 3.55 11.25 6.40 6.55

TABLE 4.3: NUMBER OF FAILURES OF COMPONENTS

SR. NO.

NAME OF THE COMPONENT

MARCH (HRS)

APRIL (HRS)

MAY (HRS)

1 2

CANE CARRIER MILLS

2 6

5 6

3 2

TOAL No. OF FAILURES 10 15

3

RAKE / INTER CARRIER

6

7

2

15

4 5 6 7 8 9 10 11 12 13 14

BAGASSE CARRIER NEW BOILER ELECTRICALS OLD BOILER LOW PRESSURE BOILER POWER TURBINE OTHER UNITS IN BOILER RAW JUICE PUMP EVAPORATOR PAN SYRP STORAGE TANK OTHER UNITS IN BOILIBG HOUSE

2 12 1 3 -2 4 5 4 7 3

5 -1 3 2 1 -4 1 -1

2 1 4 2 1 2 2 3 5 4 4

9 13 6 8 3 5 6 12 10 11 8

1

3

3

7

15

TABLE 4.4: GENERAL DOWN TIME MONTH MARCH “04” APRIL “04” MAY “04”

GENERAL CLEANING (HRS) 19.35 15.45 58.45

WANT OF CANE (HRS)

HOLIDAY (HRS)

TOTAL HOURS

65.05 2.05 58.45

72.00 48.00 120.00

156.40 65.50 178.45

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Down Time Analysis In Process Industry-A Case Study TABLE 4.5 : MEAN DOWN TIME OF COMPONENT

S. NO 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

NAME OF THE COMPONENT CANE CARRIER MILLS RAKE / INTER CARRIER BAGASSE CARRIER NEW BOILER ELECTRICALS OLD BOILER LOW PRESSURE BOILER POWER TURBINE OTHER UNITS IN BOILER RAW JUICE PUMP EVAPORATOR PAN SYRP STORAGE TANK OTHER UNITS IN BOILIBG HOUSE

TOTAL DOWN TIME (HRS : MIN) MARCH APRIL MAY (156.40) (65.50) 178.45) 163.25 71.00 179.50 167.05 72.15 180.20 160.25 70.25 181.15 157.25 70.05 179.25 220.05 65.50 179.15 157.10 67.55 182.00 158.40 67.55 179.55 156.40 68.40 179.40 165.25 66.15 179.55 159.35 65.50 179.40 165.40 158.25 161.40 158.55 158.10

68.35 66.05 65.50 6720 67.55

180.40 180.40 185.10 181.40 182.05

MEAN DOWN TIME (HRS:MIN) 138.32 140.20 137.22 135.52 155.30 135.55 135.17 135.13 137.38 135.15 138.05 135.30 137.33 136.12 136.30

TABLE 4.6 : AVAILABILITY OF COMPONENTS

S. NO. 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

NAME OF THE COMPONENT CANE CARRIER MILLS RAKE / INTER CARRIER BAGASSE CARRIER NEW BOILER ELECTRICALS OLD BOILER LOW PRESSURE BOILER POWER TURBINE OTHER UNITS IN BOILER RAW JUICE PUMP EVAPORATOR PAN SYRP STORAGE TANK OTHER UNITS IN BOILIBG HOUSE

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MTBF (HRS) 6.45 10.25 3.45 0.45 63.25 0.30 2.00 -8.45 2.55 9.00 1.45 5.00 2.15 1.30

MDT (HRS) 138.32 140.20 137.22 135.52 155.30 135.55 135.17 135.13 137.38 135.15 138.05 135.30 137.37 136.12 136.30

AVAILABILITY (%) 61.34 51.08 51.64 61.40 51.57 73.03 67.08 84.47 76.19 73.11 57.04 61.97 59.30 66.91 69.76

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2321-7871 Down Time Analysis In Process Industry-A Case Study

TABLE 5.1 : RELIABILITY OF COMPONENTS S. NO. 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

NAME OF THE COMPONENT CANE CARRIER MILLS RAKE / INTER CARRIER BAGASSE CARRIER NEW BOILER ELECTRICALS OLD BOILER LOW PRESSURE BOILER POWER TURBINE OTHER UNITS IN BOILER RAW JUICE PUMP EVAPORATOR PAN SYRP STORAGE TANK OTHER UNITS IN BOILIBG HOUSE

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á

â

1410 1300 1000 1350 410 1500 1200 1600 1500 610 1100 1300 1048 1200 1400

1.8 1.4 1.97 2.5 0.60 2.27 1.6 2.59 2.61 1.00 2.00 1.2 1.8 1.8 2.25

AVAILABILITY (%) 44.6 41.07 45.4 49.16 24.68 48.24 43.03 50.32 55.12 36.79 45.69 38.59 44.52 44.45 47.69

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Down Time Analysis In Process Industry-A Case Study TABLE 6.1 : FMEA ANALYSIS

Boiler

Traveling

New Boiler

Pressure drop

Low pressure Boiler

Pressure drop

Evaporator

SO2 Gas line

PAN

PAN waiting

Bagasse carrier

Drive chain

Mills

Conveyor belt cut

Other unit of boiler Rake / Inter Carrier

Pipe line Rake elevator

Raw Juice pump

Pipe line

Syrup storage tank

Gas line

Other units in Boiling house

Nozzle

Power turbines

Turbine

Electrical

Alternator

Cane carrier

Cane carrier plate

Combustion of coal is affected Low Production of steam Low Production of steam Leakage gas Production of sugar is affected Discharging of Bagasse is affected Discharging of Bagasse is affected Leakage of juice Drive is affected Leakage of juice Leakage of juice Leakage gas Power generation is reduced Affect the bagasse movement Drive is affected

Low quality of coal

1

6

5

6

180

Water Scarcity

2

5

4

5

100

Water Scarcity

3

8

3

4

96

Corrosion effect

4

7

1

8

56

Limited level of syrup in tank

5

4

2

5

40

Jamming of bagasse

6

2

3

4

24

Worn out of belt

7

3

2

3

18

Corrosion effect

7

2

1

14

8

Improper tightening

4

3

1

12

9

Corrosion effect

6

1

2

12

10

Corrosion effect

2

1

4

8

Corrosion effect

3

2

1

6

12

Pressure reduction

3

1

2

6

13

Motor tripped

2

1

2

4

14

Corrosion on the plate

2

2

1

4

15

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