1、2900 单词， 14800 英文字符， 4740 汉字 出处： Kai M T. On Fuzzy Inference System Based Failure Mode and Effect Analysis (FMEA) MethodologyC/ Soft Computing and Pattern Recognition, International Conference of. IEEE, 2009:329-334. 附录 A 外文翻译原文 On Fuzzy inference system based Failure Mode and Effe
2、ct Analysis (FMEA) methodology Kai Meng Tay Electronic Engineering Department, Faculty of Engineering, University Malaysia Sarawak Sarawak, Malaysia kmtayfeng.unimas.my Abstract-Filure Mode and Effect Analysis (FMEA) is a popular problem prevention methodology. It utilizes a Risk Priority Number (RP
3、N) model to evaluate the risk associated to each failure mode. The conventional RPN model is simple, but, its accuracy is argued. A fuzzy RPN model is proposed as an alternative to the conventional RPN. The fuzzy RPN model allows the relation between the RPN score and Severity, Occurrence and Detect
4、 ratings to be of non-linear relationship, and it maybe a more realistic representation. In this paper, the efficiency of the fuzzy RPN model in order to allow valid and meaningful comparisons among different failure modes in FMEA to be made is investigated. It is suggested that the fuzzy RPN
5、should be subjected to certain theoretical properties of a length function e.g. monotonicity, sub-additivity and etc. In this paper, focus is on the monotonicity property. The monotonicity property for the fuzzy RPN is firstly defined, and a sufficient condition for a FIS to be monotone is app
6、lied to the fuzzy RPN model. This is an easy and reliable guideline to construct the fuzzy RPN in practice. Case studies relating to semiconductor industry are then presented. Keywords: Fuzzy inference system, monotonicity property, sufficient conditions, FMEA, manufacturing NTRODUCTION Failure Mode and Effect Analysis (FMEA) is an effective problem prevention methodology that can easily interface with many engineering and reliability methods 1. It can be described as a systemized group of activities intended
