Applying an approximate Tω (the weakest t-norm) fuzzy GERT to evaluate two-unit standby redundant system reliability | Zendy

Kuo-Ping Lin | Zendy; Kuo-Chen Hung | Zendy; Ssu-Ping Lai | Zendy; Ya-Ting Yu | Zendy; Pei-Ti Wu | Zendy

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Applying an approximate Tω (the weakest t-norm) fuzzy GERT to evaluate two-unit standby redundant system reliability

Author(s) -

Kuo-Ping Lin,

Kuo-Chen Hung,

Ssu-Ping Lai,

Ya-Ting Yu,

Pei-Ti Wu

Publication year - 2011

Publication title -

procedia computer science

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.334

H-Index - 76

ISSN - 1877-0509

DOI - 10.1016/j.procs.2011.04.143

Subject(s) - computer science , fuzzy logic , reliability (semiconductor) , fuzzy number , arithmetic , norm (philosophy) , interval (graph theory) , reliability engineering , algorithm , mathematical optimization , fuzzy set , mathematics , artificial intelligence , power (physics) , physics , engineering , quantum mechanics , combinatorics , political science , law

tandby redundant system is a powerful tool to enhance the reliability, availability, quality, and safety of operational plants. This study proposed an approximate Tω (the weakest t-norm) fuzzy Graphical Evaluation and Review Technique (GERT) simulation technology to simulate two-unit standby redundant system reliability. The approximate fuzzy arithmetic operations employ principle of interval arithmetic under the Tω arithmetic operations. Therefore, the novel fuzzy arithmetic operations may obtain fitter decision values, which have smaller fuzziness accumulating, under vague environment. In numerical examples the approximate fuzzy arithmetic operations has evidenced that it can successfully calculate results of fuzzy operations as interval arithmetic, and can more effectively reduce fuzzy spreads. In the real fuzzy repairable reliability model the performance also shows that the approximate fuzzy arithmetic operations successfully simulate/analyze the two-unit standby redundant system reliability and obtain more confident fuzzy results under vague environment

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