Inte rnatio nal Jo urnal o f Sc ie ntific & Eng inee ring Re se arc h, Vo lume 3, Issue 1, January -2012 1

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FMECA Analysis (A Heuristic Approach) For Frequency of Maintenance and Type of Maintenance

Malay Niraj, Praveen Kumar, Dr. A.Mishra

Abs tract -- Present study is an approach f or f inding the suitable ma intenance practice and f requency of maintenance w ith th e help of criticality f actor of equipment it is based on f ailure mode evaluation and criticality analysis. Criticality means the f ailure probability of the equipment is very high. The miner f ailure of critical equipment may leads to sever impact on the perf ormance of the equipment. So critical equipment needs very high degree of

maintenance activity and maintenance f requency to prevent any f ailure. This model has imple mented in process industry and man y OEE like f actor has been improved.

Ke y-words- FMECA, Criticality Factor, and Overall Equip ment Ef f ectiveness

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1. INTRODUCTION

he Failure Modes and Effects Criticality Analys is (FMECA) is really an extens ion of the FMEA, focus ing on the quantitative parameters for a criticality ass igned to
each probable failure mode, and is discussed below. A widely accepted military s tandard for conducting FMEAs is Mil-Std-
1629. This military standard details the specifics in conducting a FMEA. Like any analytical tool, if used and implemented correctly the FMEA is a powerful des ign engineering aid, and is us ed in the aerospace, military, automotive and s pace sectors . These industries have their own variance on how to and why conduct a FMEA, however their intent is the s ame. For ins tance NASA focus es on the qualitative aspect of failure modes and their effect on a sys tem, rather than a quantitative approach, which would not be the cas e in conducting a FMECA as oppos ed solely to a FMEA. Supporting the NASA FMEA process is a Critical Items Lis t (CIL). This lis t contains all the failure modes that would have catas trophic effects on a s ystem or mis s ion . The Failure Modes and Effect (Criticality) Analys is is termed as a bottoms up analys is . The FMEA is bas ed on an qualitative approach, whils t the FMECA takes a Quantitative approach and is an extens ion of the FMEA, ass ign a criticality and probability of occurrence for each given failure mode. Maintenance is now a s ignificant activity in industrial practice. According to Halas z et al [1] on the 1996 costs of maintenance across 11 Canadian industry s ectors . "In addition to every dollar spent on new machinery. An additional 58 cents is spent on maintaining exis ting equipment. This amoun ts to repair costs of approximately
$15 billion per year". .As a cons equence. The importance of
maintenance optimization becomes obvious . According to a survey conducted by Jens en [2] bas ed on MATH DATAB.ASE of STY. From 1972 to 1994, the number of publica tions with keyword "Reliability" is $3521 and in addition. 1909 papers have keywords "Maintenance" or "Repair". Thes e papers account for about 0.8% of all mathematical publications which are related to reliability and maintenance. This shows the importance of this field and in the meantime. The difficulty of providing a complete
overview on the subject. Several intens ive surveys can be found in the journal of Naval Res earch Logis tics Quarterly. Where Pies kalla and Voelker [3] has 259 references . Sherif and Smith [4] has an extens ive bibliography of 52.1 references and Valdez- Flores and Feldman [5] has 129 references . Certainly it is getting harder and harder to gras p this huge and growing field. Attempting to summarize this field with s everal univers al optimization models is definitely infeas ible. The different maintenance policies are us ed depending on the characteristic of the equipment. The complexity of maintenance planning is through higher becaus e of some characteris tic that dis tinguish from other types of scheduling (Noemi & William, [6]). Waeyenberg and Pintelon, [7] propos es a maintenance policy decis ion model to identify the correct maintenance po licy for a particular component.

2 .CRITIC ALITY AN ALYSES

Criticality Analysi s

Criticality analys is is bas ed on failure mode evaluation analys is .


Criticality means the failure probability of the equipment is very high. The miner failure of critical equipment may leads to s ever impact on the performance of the equipment. So critical equipment needs very high degree of maintenance activity and maintenance frequency to prevent any failure
Cr iticality Factor = Fr equency Factor X Sever ity
Factor X Protection Factor
Where,

Frequency Factor: It is a number awarded depending on the frequency of failure. More the no. of failure more is the value given to the factor.

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Protection Facto r: It is a number awarded on the account of eas e to protect the equipment from failure. Minimum no. is given when protection against the failure is easy. Maximu m no. is given when protection against the failure is very difficult.

Severity Factor: Severity factor represents the effect level of failure on the equipment on the bas is of down time, s crap rate and s afety

Sever ity Factor = (Dow n time factor + scrap rate factor + safety factor )

Factor Range of Weightage

1. down time factor 1-10
2. Scrape factor 1-5
3. Safety factor 1-20
4. Protection factor 1-10
5. Frequency factor 1-15

Allocation of TBM and CBM schedule on the bas is of criticality factor value

Down time factor

It is the no. awarded in accordance with the failure time associated to the equipment. More the down time more is the factor, less the down time less is the factor.

Scrape rate factor

If the chances to scrap the whole equipment or component in the cas e of failure are high then the scrap factor value is taken more and in the case of less chance to a scrape the equipment or component factor value is taken less .

Safety factor

It repres ents ris k associated in the cas e of failure. If the chances of injury (both man and machine) are high in the cas e of equipment failure more is the value given to the safety factor and less the chances of injury, less is the value given to the safety factor. On the bas is criticality factor of all the component of the any industry is calculated.
This process is given the name failure mode effect and

criticality analysis (FMECA).

The factors associated to the criticality analys is have different
impact level on criticality of the equipment so different range or weightage is provided to them

3 HO W IT WORK IN PROCE SS IN DUSTRY

FLOW CHART FOR CRITI CAL L Y FACTOR VAL UE

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START

ENTER PF, SAF, SRF, DTF, FF

YES NO IF PF>=1

&&PF<=10

Were, PF=PROTECTION

FACTOR

SAF=SAFETY FACTOR SRF=SCRAPE RATE

FACTOR

DTF=DOWNTIME FACTOR

YES

NO IF FF>=1

&&FF<=15

YES

NO IF DTF>=1

&&DTF<=10

YES

NO IF SAF>=1

&&SAF<=20

YES

NO IF SRF>=1

&&SRF<=5

PRINT OUT OF RANGE

YES

SEVERITY FACTOR= DTF+SRF+SAF

CRITICALLY FACTOR=FF*SEVERITY FACTOR*PF

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2 1

IF CRITICALLY FACTOR>=100

0

NO

YES

PRINT MAINTENANCE PRACTICE= TBM&CBM

FREQUENCY OF MAINTENANCE= DAILY or TWICE

IF CRITICALLY FACTOR>=500& CRI TICALLY

NO

YES

PRINT MAINTENANCE PRACTICE= CBM

FREQUENCY OF MAINTENANCE= DAILY or TWICE A WEEK

IF CRITICALLY FACTOR>=200&&C RITICALLY

NO

YES PRINT MAINTENANCE PRACTICE= CBM

FREQUENCY OF MAINTENANCE=WEEKLY

IF CRITICALLY FACTOR>=50&&CR ITICALLY

YES PRINT MAINTENANCE PRACTICE= CBM

FREQUENCY OF MAINTENANCE=WEEKLY

IF CRITICALLY

FACTOR<50

PRINT MAINTENANCE PRACTICE= BREAK DOWN

FREQUENCY OF MAINTENANCE=AT THE TIME OF FAIL URE

STOP

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4. RESULT

The pr esented knowledge model defines a str uctur e for maintenance system model. This is logical tool for finding maintainance of machine which need mor e car e for avoiding failur e with the help of this model fir st we collecting data for cr ticality of machine parts and then on the basis of FMCA analysis(a heur istic appr oach) for example w e can see if Cr iticality factor (CF)in a r ange of
1000 to 500 then Maintainnance practice(MP) is CBM & Fr equancy of maintainance (FM)w ill be daily or tw ice a w eek. On the basis of cr iticality analysis some of the factor has been impr oved.

5. CONC LUSIONS

In this paper the complexity of differ ent main ar eas and parameters or per formers in a system has been discussed. Companies need to be incr easingly awar e of the parameters affecting their pr oduction systems. It might be better to optimize one main ar ea and some par ameters first. In this paper , assumptions have been made that r efer to FMECA, Cr iticality factor . The study is very helpful for new industry or small scale industry for selecting the best maintenance practice and fr equency of maintenance for economic point of view it is new concept for selection of maintenance practice and enhance the moral of employee for taking a strong decision. The time consumption for taking a decision is less in this concept

ACRONYMS

FMECA- The Failur e Modes and Effects Cr iticality
Analysis
FMCA- Failur e mode effect analysis
CF-Cr iticality factor
OEE –Overall Equipment Effectiveness
MP-Maintenance pr evention
CBM-Condition base maintenance
TBM-Time base maintenance

REFERENCES

[1] Halasz, 41.. F. Dub. R. Orc hard and R. Fe rland (1999). The inte g rate d diag no stic syste m (IDS): re mo te mo nito ring and dec isio n suppo rt fo r co rnme rc ial airc raft - putting the o ry into prac tice . http://ai.iit.nrc.c a/IR-public /ids /pape rs/aaai99idspape r.

[2] Je nse n U. (1996). S toc hastic mo de ls o f re liability and mainte nance . In Re liability and Mainte nance o f Co mple x Syste m. Oze kic i S. (e d.); S pring e

[3] Pie rskalla. W. and J. V oe lke r (1976). . -\ survey o f mainte nanc e mo de ls: the Co ntro l and surv e illance o f de te rio rating syste ms. Nav al Re se arc h Logistic s Quarte rly 23. 353-388

[4] S he rif, Y. and iLI. S mith (1981). Optimal mainte nance mo de ls fo r sy ste ms subjec t to failure : a rev ie w. Nav al Rese arc h Log istics Quarte rly 38. 47-74.

[5] V aldez-Flo re s, C. and R.M. Fe ldman (1989). A survey o f preve ntive mainte nance mo de ls fo r stoc hastic ally de te rio rating sing le -unit sy ste ms. Nav al Re se arc h Log istic s 36 (4), 4 19-446

[6] Noe mi, P. M., & William, L. (1994). Mainte nance Sc he duling : Issues, Re sults and Re se arc h Nee ds. Interna tiona l Journa l of Opera tions & Production Ma nagement , Vol.14, No.8, pp 47 -69.

[7] Waeye nbe rg , G., & Pinte lo n, L. (2002). A frame wo rk fo r mainte nance co nce pt de ve lo pme nt. Interna tiona l journa l of production economics, Vo l.77, No .3, pp 299-313.

Malay Niraj

Assistant Professor

Mechanical Engineering Department, National Institute of

Technology, Jamshedpur, INDIA E-mail: malay9mednit@yahoo.in

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