Developing a Tω (the weakest t-norm) fuzzy GERT for evaluating uncertain process reliability in semiconductor manufacturing

被引:31
作者
Lin, Kuo-Ping [1 ]
Wu, Ming-Jia [2 ]
Hung, Kuo-Chen [3 ]
Kuo, Yiyo [4 ]
机构
[1] Lunghwa Univ Sci & Technol, Dept Informat Management, Tao Yuan 333, Taiwan
[2] Lunghwa Univ Sci & Technol, Grad Sch Business & Management, Tao Yuan 333, Taiwan
[3] Natl Def Univ, Dept Logist Management, Taipei 112, Taiwan
[4] Hsing Kuo Univ Management, Dept Mkt & Logist Management, Tainan 709, Taiwan
关键词
Graphical Evaluation and Review; Technique (GERT); Fuzzy GERT; The weakest t-norm arithmetic operations; Lithography area; R-AND-DS; NETWORK; NUMBERS;
D O I
10.1016/j.asoc.2011.05.043
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper develops a novel weakest t-norm (T-omega) fuzzy Graphical Evaluation and Review Technique (GERT) simulation technology. This proposal is designed to be useful in a realistic environment and improve upon the traditional fuzzy GERT insofar as it has been developed for analyzing complex systems in uncertain environments; the traditional system usually adopts alpha-cut arithmetic operations for its calculations. In this research, the fuzzy support system develops the T-omega fuzzy GERT as a substitute for traditional fuzzy GERT technology. In the examples, the fuzzy support system constructs a model of 300 mm manufacturing processes in the context of a lithography area. Moreover, the manufacturing processes model is examined with regard to the fuzzy support system using two types of fuzzy arithmetic: alpha-cut arithmetic and the T-omega operator. Notably: (1) both types of fuzzy arithmetic provide a reliable analysis of the fuzzy GERT model with regard to a lithography area; (2) under the traditional fuzzy GERT model, the alpha-cut arithmetic provides results such that the fuzziness of the model calculation was fuzzier than that of the T-omega fuzzy arithmetic due to the accumulation of fuzziness of the alpha-cut arithmetic; (3) the alpha-cut arithmetic cannot effectively preserve the original shape of a membership function; and (4) the T-omega arithmetic gives a justifiable fuzziness/fuzzy spread because it takes only the maximal fuzziness encountered and calculates that into the operation. Our proposed T-omega fuzzy GERT can successfully analyze a 300 mm manufacturing process; this has been evidenced in the research. Additionally, the proposed model uses simple arithmetic operations rather than traditional fuzzy GERT with applications in complex manufacturing systems. Moreover, the T-omega arithmetic provides more credible (or conservative) information/results with regard to the amount of fuzziness in the 300 mm manufacturing processing model. (C) 2011 Elsevier B. V. All rights reserved.
引用
收藏
页码:5165 / 5180
页数:16
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