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

Tay, K. M. and Lim, C. P. 2010, Enhancing the failure mode and effect analysis methodology with fuzzy inference techniques, Journal of intelligent and fuzzy systems, vol. 21, no. 1-2, pp. 135-146.

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Title Enhancing the failure mode and effect analysis methodology with fuzzy inference techniques
Author(s) Tay, K. M.
Lim, C. P.ORCID iD for Lim, C. P. orcid.org/0000-0003-4191-9083
Journal name Journal of intelligent and fuzzy systems
Volume number 21
Issue number 1-2
Start page 135
End page 146
Total pages 12
Publisher IOS Press
Place of publication Amsterdam, The Netherlands
Publication date 2010
ISSN 1064-1246
Keyword(s) FMEA
fuzzy inference system
fuzzy production rules
reduced rule base
weighted fuzzy production rules
Summary 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.
Language eng
Field of Research 089999 Information and Computing Sciences not elsewhere classified
Socio Economic Objective 970108 Expanding Knowledge in the Information and Computing Sciences
HERDC Research category C1.1 Refereed article in a scholarly journal
Copyright notice ©2010, IOS Press and the authors. All rights reserved
Persistent URL http://hdl.handle.net/10536/DRO/DU:30048745

Document type: Journal Article
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