Enhancing the failure mode and effect analysis methodology with fuzzy inference techniques
Data(s) |
01/01/2010
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Resumo |
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.<br /> |
Identificador | |
Idioma(s) |
eng |
Publicador |
IOS Press |
Relação |
http://dro.deakin.edu.au/eserv/DU:30048745/lim-enhancingthe-2010.pdf http://hdl.handle.net/10.3233/IFS-2010-0442 |
Direitos |
2010, IOS Press and the authors. All rights reserved |
Palavras-Chave | #FMEA #fuzzy inference system #fuzzy production rules #reduced rule base #weighted fuzzy production rules |
Tipo |
Journal Article |