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INTERNATIONAL CONFERENCE ON ADVANCES IN PRODUCTION AND INDUSTRIAL ENGINEERING 20-21, FEBRUARY 2015 Sponsors Maintenance Strategies Selection Using Fuzzy FMEA and Integer Programming INCAPIE 2015 Pranav Sankpal Post-Graduate Student A. Andrew BHEL PPPU, Thirumayam. Dr. S. Kumanan Professor Department of Production Engineering National Institute of Technology, Tiruchirappalli.

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Page 1: Incapie Ppt Pranav

INTERNATIONAL CONFERENCE ON ADVANCES IN PRODUCTION AND INDUSTRIAL ENGINEERING

20-21,  FEBRUARY 2015

Sponsors

Maintenance Strategies Selection Using Fuzzy FMEA and Integer Programming

INCAPIE 2015

Pranav SankpalPost-Graduate Student

A. AndrewBHEL PPPU, Thirumayam.

Dr. S. KumananProfessor

Department of Production Engineering

National Institute of Technology, Tiruchirappalli.

Page 2: Incapie Ppt Pranav

INTERNATIONAL CONFERENCE ON ADVANCES IN PRODUCTION AND INDUSTRIAL ENGINEERING

20-21,  FEBRUARY 2015

Sponsors

Contents

•Introduction

•Literature Analysis

•Problem Statement

•Objectives

•Proposed Model

•Case study

•Conclusion

INCAPIE 2015

Page 3: Incapie Ppt Pranav

INTERNATIONAL CONFERENCE ON ADVANCES IN PRODUCTION AND INDUSTRIAL ENGINEERING

20-21,  FEBRUARY 2015

Sponsors

Introduction

Efficient maintenance planning is important for achieving higher productivity levels.

Maintenance cost is one of the significant component of operational expenditure.

Selection of right maintenance strategy is critical because it determines future maintenance related direct and indirect costs.

INCAPIE 2015

Page 4: Incapie Ppt Pranav

INTERNATIONAL CONFERENCE ON ADVANCES IN PRODUCTION AND INDUSTRIAL ENGINEERING

20-21,  FEBRUARY 2015

Sponsors

Literature Analysis Pariazar et al. (2008) combined factorial analysis and the

analytic hierarchic process (AHP), (improved by means of rough set theory) and first recognized 19 effective criteria in maintenance strategy selection.

Shyjith et al. (2008) proposed the combination of AHP and TOPSIS to select the suitable maintenance policy for a textile spinning mill ring frame unit.

Mousavi et al. (2009) used factorial analysis for clustering many decision making criteria into groups. Then they applied a fuzzy technique for order preference by similarity to ideal solution (TOPSIS) method to help decision makers to select the most appropriate maintenance strategy.

Arunraj and Maiti (2010) presented an approach to maintenance policy selection based on the combined use of AHP and goal programming.

Braglia, M., Castellano, D. and Frosolini, M.(2013) proposed an integer programming approach to maintenance strategies selection to optimally allocate the budget monetary resources and maximise the potential reduction of the RPN

INCAPIE 2015

Page 5: Incapie Ppt Pranav

INTERNATIONAL CONFERENCE ON ADVANCES IN PRODUCTION AND INDUSTRIAL ENGINEERING

20-21,  FEBRUARY 2015

Sponsors

Problem Statement

Aim is to select most effective combination of maintenance strategies for an industrial equipment.

Currently FMEA is widely used tool for failure mode prioritisation

All the maintenance activities are directed towards critical failure.

Hence criticality evaluation is the most important part of the model

INCAPIE 2015

Page 6: Incapie Ppt Pranav

INTERNATIONAL CONFERENCE ON ADVANCES IN PRODUCTION AND INDUSTRIAL ENGINEERING

20-21,  FEBRUARY 2015

Sponsors

Limitations of traditional FMEA:

Criticality analysis is not realistic

Selection of maintenance strategies is very qualitative and does not consider costs associated with maintenance strategy and their effectiveness.

First limitation is addressed using fuzzy logic system

Problem of selecting optimum mix of maintenance strategies subject to budget constrain is resolved using integer programming.

INCAPIE 2015

Page 7: Incapie Ppt Pranav

INTERNATIONAL CONFERENCE ON ADVANCES IN PRODUCTION AND INDUSTRIAL ENGINEERING

20-21,  FEBRUARY 2015

Sponsors

Objectives

To develop fuzzy logic system for realistic estimation of criticality of each failure mode.

To select optimum mix of maintenance strategies taking into account budget constraint and compatibility constraint.

INCAPIE 2015

Page 8: Incapie Ppt Pranav

INTERNATIONAL CONFERENCE ON ADVANCES IN PRODUCTION AND INDUSTRIAL ENGINEERING

20-21,  FEBRUARY 2015

Sponsors

INCAPIE 2015

Proposed Model

Page 9: Incapie Ppt Pranav

INTERNATIONAL CONFERENCE ON ADVANCES IN PRODUCTION AND INDUSTRIAL ENGINEERING

20-21,  FEBRUARY 2015

Sponsors

Integer Programming Model

RCM prioritises various failure modes based on fuzzy Risk Priority Numbers

Next step is to assign to each failure mode, a suitable maintenance strategy in such a way that reduction in RPN for all failure modes is maximised.

Problem is formulated as mixed-integer linear programming model and solved using GAMS

INCAPIE 2015

Page 10: Incapie Ppt Pranav

INTERNATIONAL CONFERENCE ON ADVANCES IN PRODUCTION AND INDUSTRIAL ENGINEERING

20-21,  FEBRUARY 2015

Sponsors

INCAPIE 2015

Page 11: Incapie Ppt Pranav

INTERNATIONAL CONFERENCE ON ADVANCES IN PRODUCTION AND INDUSTRIAL ENGINEERING

20-21,  FEBRUARY 2015

Sponsors

INCAPIE 2015

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Page 12: Incapie Ppt Pranav

INTERNATIONAL CONFERENCE ON ADVANCES IN PRODUCTION AND INDUSTRIAL ENGINEERING

20-21,  FEBRUARY 2015

Sponsors

Case Study

INCAPIE 2015

Page 13: Incapie Ppt Pranav

INTERNATIONAL CONFERENCE ON ADVANCES IN PRODUCTION AND INDUSTRIAL ENGINEERING

20-21,  FEBRUARY 2015

Sponsors

Continued..

INCAPIE 2015

Page 14: Incapie Ppt Pranav

INTERNATIONAL CONFERENCE ON ADVANCES IN PRODUCTION AND INDUSTRIAL ENGINEERING

20-21,  FEBRUARY 2015

Sponsors

Continued..

INCAPIE 2015

Page 15: Incapie Ppt Pranav

INTERNATIONAL CONFERENCE ON ADVANCES IN PRODUCTION AND INDUSTRIAL ENGINEERING

20-21,  FEBRUARY 2015

Sponsors

Optimum mix of maintenance strategies

INCAPIE 2015

Page 16: Incapie Ppt Pranav

INTERNATIONAL CONFERENCE ON ADVANCES IN PRODUCTION AND INDUSTRIAL ENGINEERING

20-21,  FEBRUARY 2015

Sponsors

Conclusion

INCAPIE 2015

The application of maintenance strategy can reduce the RPN value of a failure mode.

The proposed model allows to choose a set of maintenance strategies which will maximise total reduction in RPN for all failures.

Also the major difficulty in realistic assessment of RPN value is addressed using fuzzy logic system.

More refinement in cost estimation task is required to enhance the utility of proposed model.