Sara Tavassoli; Farnaz Shahpar; Taha-Hossein Hejazi
Abstract
Most of the existing approaches for fuzzy reliability analysis are based on fuzzy probability. The aim of this paper is to describe fuzzy reliability using fuzzy differential equation. The reliability of a system in real world applications is affected by some uncertain parameters. Fuzzy reliability ...
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Most of the existing approaches for fuzzy reliability analysis are based on fuzzy probability. The aim of this paper is to describe fuzzy reliability using fuzzy differential equation. The reliability of a system in real world applications is affected by some uncertain parameters. Fuzzy reliability is a way to present the reliability function uncertainly using fuzzy parameters. In the proposed fuzzy differential equation for reliability, two types of fuzzy derivative: Hukuhara derivative and generalized differentiability are used. It is proved that the Hukuhara differentiability is not adequate for fuzzy reliability analysis. Finally, using the fuzzy integration, the concept of fuzzy mean time to failure (FMTTF) will be introduced. Some numerical simulations are presented to show the applicability and validity of generalized differentiability, in comparison with the Hukuhara differentiability results for fuzzy reliability analysis.
Y.C. Zanjani; Z. Rafie Majd; A. Mirzazadeh
Volume 2, Issue 1 , June 2015, , Pages 1-15
Abstract
Fuzzy reliability is often used in analyzing the reliability in the large industrial systems. In this paper, a relatively new method is presented to analyze Neishabour (also called Nishapur, a city in Iran) train disaster. In this regards, by using the certain and uncertain propositions, unreliability ...
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Fuzzy reliability is often used in analyzing the reliability in the large industrial systems. In this paper, a relatively new method is presented to analyze Neishabour (also called Nishapur, a city in Iran) train disaster. In this regards, by using the certain and uncertain propositions, unreliability circuit of the system is depicted .Due to the inability to provide exact values for the unreliability of each subsystem, regarding the opinion of experts, fuzzy logic is applied and triangular and Gaussian membership functions are attributed depending to the type of each subsystem and the fuzzy unreliability value of the system is calculated. Finally, by defuzzification and comparing the obtained value with the classification table of linguistic variables, unreliability of the system is identified.