Open AccessFuzzy reliability‐redundancy allocation problem of the overspeed protection system
Author(s) -
Taghiyeh Sajjad,
Mahmoudi Morteza,
Fadaie Saber,
Tohidi Hossein
Publication year - 2020
Publication title -
engineering reports
Language(s) - English
Resource type - Journals
ISSN - 2577-8196
DOI - 10.1002/eng2.12221
Subject(s) - reliability (semiconductor) , redundancy (engineering) , fuzzy logic , mathematical optimization , parametric statistics , flexibility (engineering) , mathematics , computer science , parametric programming , fuzzy number , membership function , point (geometry) , nonlinear system , reliability engineering , fuzzy control system , fuzzy set , artificial intelligence , engineering , statistics , power (physics) , physics , geometry , quantum mechanics
System reliability is defined as the probability of satisfactory performance of a system under stated conditions for a specified period of time. According to this definition, four parameters, including probability, satisfactory performance, specific conditions, and time should be exactly characterized to evaluate the system reliability accurately. However, due to the uncertainty involved in real situations, it is hardly possible to assess the aforementioned parameters precisely. In this article, two general and distinct approaches, including Zadeh's extension principle and modification of fuzzy parametric programming (FPP), are proposed to take into account such uncertainty in a famous reliability problem called the overspeed protection system. According to Zadeh's extension principle, a pair of nonlinear programming problems is formulated to compute α ‐level cuts of fuzzy system reliability. The membership function of fuzzy system reliability can then be constructed analytically by numerating different values of α . This fuzzy system reliability presents flexibility for further system analysis. In the second approach, from a different point of view, a variant of FPP is improved that provides a crisp value as a system reliability measure. The rewarding point of the latter procedure is to handle the problem in a computationally easier way.