FUZZY SYSTEM RELIABILITY WITH MINIMIZATION OF COEFFICIENT OF VARIANCE FOR MULTISTAGE SERIES-PARALLEL SYSTEMS

2015 ◽  
Vol 96 (2) ◽  
pp. 249-264
Author(s):  
K. Abdul Razak ◽  
K. Rajakumar
Keyword(s):  
System Reliability ◽  
Fuzzy System ◽  
Parallel Systems

Fuzzy System Reliability Analysis Based on Confidence Interval

2012 ◽  
Vol 433-440 ◽  
pp. 4908-4914 ◽  
Author(s):  
Ezzatallah Baloui Jamkhaneh ◽  
Azam Nozari
Keyword(s):  
Confidence Interval ◽  
System Reliability ◽  
Fuzzy System ◽  
Statistical Data ◽  
Parallel Systems ◽  
Fuzzy Data ◽  
Statistical Methodology ◽  
Fuzzy Reliability ◽  
Numerical Examples ◽  
Cut Set

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.

scholarly journals Copula-Based Bayesian Reliability Analysis of a Product of a Probability and a Frequency Model for Parallel Systems When Components Are Dependent

2021 ◽  
Vol 11 (4) ◽  
pp. 1697
Author(s):  
Shi-Woei Lin ◽  
Tapiwa Blessing Matanhire ◽  
Yi-Ting Liu
Keyword(s):  
System Reliability ◽  
Classification Tree ◽  
Parallel Systems ◽  
Reliability Model ◽  
Key Factors ◽  
Frequency Model ◽  
Independent Components ◽  
Aggregate Analysis ◽  
Dependence Assumption ◽  
Disaggregate Analysis

While the dependence assumption among the components is naturally important in evaluating the reliability of a system, studies investigating the issues of aggregation errors in Bayesian reliability analyses have been focused mainly on systems with independent components. This study developed a copula-based Bayesian reliability model to formulate dependency between components of a parallel system and to estimate the failure rate of the system. In particular, we integrated Monte Carlo simulation and classification tree learning to identify key factors that affect the magnitude of errors in the estimation of posterior means of system reliability (for different Bayesian analysis approaches—aggregate analysis, disaggregate analysis, and simplified disaggregate analysis) to provide important guidelines for choosing the most appropriate approach for analyzing a model of products of a probability and a frequency for parallel systems with dependent components.

Optimal Allocation of Components in k-out-of-R Parallel Modules Systems

1994 ◽  
Vol 8 (3) ◽  
pp. 435-441 ◽  
Author(s):  
Fan Chin Meng
Keyword(s):  
System Reliability ◽  
Optimal Allocation ◽  
Parallel Systems ◽  
Coherent Systems ◽  
Special Case

In this note using the notion of node criticality in Boland, Proschan, and Tong [2] and modular decompositions of coherent systems, we obtain algorithms and guidelines for allocating components in a k-out-of-R parallel modules system to maximize the system reliability. An illustrative example is given to compare a special case of our results with the previous result for series-parallel systems due to El-Neweihi, Proschan, and Sethuraman [5].

Reliability optimization for non-repairable series-parallel systems with a choice of redundancy strategies and heterogeneous components: Erlang time-to-failure distribution

2020 ◽  
pp. 1748006X2095257
Author(s):  
Meisam Sadeghi ◽  
Emad Roghanian ◽  
Hamid Shahriari ◽  
Hassan Sadeghi
Keyword(s):  
Lower Bound ◽  
Closed Form ◽  
System Reliability ◽  
Parallel Systems ◽  
Closed Form Expression ◽  
Erlang Distribution ◽  
Time To Failure ◽  
Form Expression ◽  
Integrodifference Equation ◽  
Cold Standby

The redundancy allocation problem (RAP) of non-repairable series-parallel systems considering cold standby components and imperfect switching mechanism has been traditionally formulated with the objective of maximizing a lower bound on system reliability instead of exact system reliability. This objective function has been considered due to the difficulty of determining a closed-form expression for the system reliability equation. But, the solution that maximizes the lower bound for system reliability does not necessarily maximize exact system reliability and thus, the obtained system reliability may be far from the optimal reliability. This article attempts to overcome the mentioned drawback. Under the assumption that component time-to-failure is distributed according to an Erlang distribution and switch time-to-failure is exponentially distributed, a closed-form expression for the subsystem cold standby reliability equation is derived by solving an integrodifference equation. A semi-analytical expression is also derived for the reliability equation of a subsystem with mixed redundancy strategy. The accuracy and the correctness of the derived equations are validated analytically. Using these equations, the RAP of non-repairable series-parallel systems with a choice of redundancy strategies is formulated. The proposed mathematical model maximizes exact system reliability at mission time given system design constraints. Unlike most of the previous formulations, the possibility of using heterogeneous components in each subsystem is provided so that the active components can be of one type and the standby ones of the other. The results of an illustrative example demonstrate the high performance of the proposed model in determining optimal design configuration and increasing system reliability.

Time-dependent intuitionistic fuzzy system reliability analysis

2020 ◽  
Vol 24 (19) ◽  
pp. 14441-14448
Author(s):  
Mohammad Ghasem Akbari ◽  
Gholamreza Hesamian
Keyword(s):  
Reliability Analysis ◽  
System Reliability ◽  
Fuzzy System ◽  
Time Dependent ◽  
Intuitionistic Fuzzy ◽  
System Reliability Analysis
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