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Enhancing the failure mode and effect analysis methodology with fuzzy inference techniques

journal contribution
posted on 2010-01-01, 00:00 authored by K Tay, Chee Peng LimChee Peng Lim
Traditional Failure Mode and Effect Analysis (FMEA) adopts the Risk Priority Number (RPN) ranking model to evaluate failure risks, to rank failures, as well as to prioritize actions. Although this approach is simple, it suffers from several shortcomings. In this paper, we investigate a number of fuzzy inference techniques for determining the RPN scores, in an attempt to overcome the weaknesses associated with the traditional RPN model. The main objective is to examine the possibility of using fuzzy rule interpolation and reduction techniques to design new fuzzy RPN models. The performance of the fuzzy RPN models is evaluated using a real-world case study pertaining to the test handler process in a semiconductor manufacturing plant. The FMEA procedure for the test handler is performed, and a fuzzy RPN model is developed. In addition, improvement to the fuzzy RPN model is proposed by refining the weights of the fuzzy production rules, hence a new weighted fuzzy RPN model. The ability of the weighted fuzzy RPN model in failure risk evaluation with a reduced rule base is also demonstrated.

History

Journal

Journal of intelligent and fuzzy systems

Volume

21

Issue

1-2

Pagination

135 - 146

Publisher

IOS Press

Location

Amsterdam, The Netherlands

ISSN

1064-1246

eISSN

1875-8967

Language

eng

Publication classification

C1.1 Refereed article in a scholarly journal

Copyright notice

2010, IOS Press and the authors. All rights reserved