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Performance analysis of repairable system using GA and fuzzy Lambda-Tau methodology

Ajay Kumar (Department of Applied Sciences, ABV-IIITM Gwalior, Gwalior, India)
S.P. Sharma (Department of Mathematics, IIT Roorkee, Roorkee, India)
Dinesh Kumar (Department of Mechanical and Industrial Engineering, IIT Roorkee, Roorkee, India)

International Journal of Quality & Reliability Management

ISSN: 0265-671X

Article publication date: 7 October 2013

295

Abstract

Purpose

The purpose of this paper is to develop a new approach for computing various performance measures such as reliability, availability, MTBF, ENOF, etc. for any industrial system.

Design/methodology/approach

Pulping system, the main functionary part of paper industry, is the subject of the study. The interactions among the working components are shown using Petri nets (PNs). Failure and repair rates are represented using triangular fuzzy numbers (TFNs), as they allow expert opinion, linguistic variables, operating conditions, uncertainty and imprecision in reliability information, to be incorporated into system model. The failure rates and repair times of all constituent components are obtained using genetic algorithms (GAs) and then various performance measures are computed using fuzzy Lambda-Tau methodology (FLTM).

Findings

The proposed methodology provides a better understanding about the behavior of any repairable system through its graphical representation.

Originality/value

A new approach has been given to compute various performance measures and based on calculated reliability parameters, a structured framework has been developed that may help the maintenance engineers to analyze and predict the system behavior.

Keywords

Acknowledgements

The authors would like to thank the referees for a careful reading of the manuscript and for several suggestions, which led to substantial improvements in this paper.

Citation

Kumar, A., Sharma, S.P. and Kumar, D. (2013), "Performance analysis of repairable system using GA and fuzzy Lambda-Tau methodology", International Journal of Quality & Reliability Management, Vol. 30 No. 9, pp. 1017-1032. https://doi.org/10.1108/IJQRM-06-2013-0104

Publisher

:

Emerald Group Publishing Limited

Copyright © 2013, Emerald Group Publishing Limited

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