Fuzzy System Reliability Analysis Based on Confidence Interval

Abstract

This paper proposes a new method for analyzing the fuzzy system reliability of a parallel-series and series-parallel systems using fuzzy confidence interval, where the reliability of each component of each system is unknown. To compute system reliability, we are estimated reliability of each component of the systems using fuzzy statistical data with both tools appropriate for modeling fuzzy data and suitable statistical methodology to handle these data. Numerical examples are given to compute fuzzy reliability and its cut set and the calculating was performed by using programming in software R.

Interval-Valued Intuitionistic Fuzzy Confidence Intervals

“…Jamkhaneh et al [9] developed a new method for analyzing the fuzzy system reliability of a series and parallel system using fuzzy confidence intervals.…”

A Self-Configuring Membership-Function-Based Approach for Fuzzy Fatigue Reliability Optimization of Welded A-Type Frame Considering Multi-Source Uncertainties

“…The fatigue damage calculation that is based on the traditional stress/strain approach only took the stress level over the fatigue limit into account and it ignored the one below the fatigue limit, which will result in the inaccuracy of this evaluation. The fuzzy linear fatigue damage accumulation could be evaluated by [15][16][17][18][19][20] in order to give consideration to the stress level over and below the fatigue limit: In this paper, a new membership function was constructed based on the limited sample data, whose accuracy was testified by experimental data. According to the fuzzy theory, the failure probability formula was deduced.…”