System reliability estimation and cost analysis of series-parallel systems in the presence of repair dependence function

2016 ◽  
Vol 10 (1) ◽  
pp. 48 ◽  
Author(s):  
K.C. Siju ◽  
M. Kumar
Keyword(s):  
Cost Analysis ◽  
System Reliability ◽  
Parallel Systems ◽  
Reliability Estimation ◽  
Dependence Function

scholarly journals Decomposition and Estimation of Multi-State Systems by Dynamic Reliability Indices

2008 ◽  
Vol 4 (1) ◽  
pp. 353-361
Author(s):  
Zaitseva Elena ◽  
Levashenko Vitaly ◽  
Matiaško Karol
Keyword(s):  
Reliability Analysis ◽  
System Reliability ◽  
Parallel Systems ◽  
State System ◽  
Reliability Estimation ◽  
Technical System ◽  
Dynamic Reliability ◽  
Reliability Indices ◽  
Multiple Valued Logic

Decomposition and Estimation of Multi-State Systems by Dynamic Reliability IndicesSome typical configurations of Multi-State System and their mathematical descriptions are considered in paper with relation to Reliability Analysis. Multiple-Valued Logic is applied for these descriptions synthesis and Dynamic Reliability Indices are used for Multi-State System reliability estimation. We concentrate on series and parallel systems, because these structures are basic for most of the technical system. We get measures of reliability for the failure and restoration of this system.

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].

scholarly journals Reliability Estimation of a Network Structure Using Generalized Trapezoidal Fuzzy Numbers

2021 ◽  
Vol 51 (1) ◽  
pp. 225-241
Author(s):  
Amit Kumar ◽  
Pooja Dhiman
Keyword(s):  
System Reliability ◽  
Fuzzy Numbers ◽  
Test System ◽  
Reliability Estimation ◽  
Trapezoidal Fuzzy Numbers ◽  
Level Of Satisfaction ◽  
Degree Of Satisfaction ◽  
Fuzzy Logic Method ◽  
Context Specific ◽  
Generalized Trapezoidal Fuzzy Numbers

Abstract Classical sets are used commonly to consider reliability. Because of the uncertainty in the data (which considered in the present paper) classical sets fail to describe the reliability accurately. Uncertainty leads to fluctuation in the actual situation of the structure. Fuzzy logic method attempts to test system reliability with the benefit of membership function. Within this context, specific problems of reasoning-based approaches are studied, explored and correlated with standard reliability approaches. In this paper Generalized Trapezoidal Fuzzy numbers (GTrFN) are used to assess the structure's fuzzy reliability. The reliability of each event is assigned with different level of satisfaction and some improved operations on the generalized trapezoidal fuzzy numbers (GTrFN) are used to calculate the fuzzy boundaries for the resultant reliability of the final event along with the degree of satisfaction. Also the results are compared to demonstrate the application of the improved operations on Generalized Trapezoidal Fuzzy Numbers (GTrFN). The obtained results converge to more precise interval values as compare to the vague fuzzy number.

System Reliability Estimation for a Manufacturing Network with Joint Buffers

2018 ◽  
Vol 25 (04) ◽  
pp. 1850020 ◽  
Author(s):  
Ping-Chen Chang ◽  
Chia-Chun Wu ◽  
Chin-Tan Lee
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
System Reliability ◽  
Manufacturing System ◽  
Reliability Estimation ◽  
Experimental Result ◽  
Production Lines ◽  
Work In Process ◽  
Process Output ◽  
Manufacturing Network

This paper develops a Monte Carlo Simulation (MCS) approach to estimate the performance of a multistate manufacturing network (MMN) with joint buffers. In the MMN, products are allowed to be produced by two production lines with the same function to satisfy demand. A performance index, system reliability, is applied to estimate the probability that all workstations provide sufficient capacity to satisfy a specified demand and buffers possess adequate storage. The joint buffers with finite storage are considered in the MMN. That is, extra work-in-process output from different production lines can be stored in the same buffer. An MCS algorithm is proposed to generate the capacity state and to check the storage usage of buffers to evaluate whether the demand can be satisfied or not. System reliability of the MMN is estimated through this MCS algorithm. Besides, performability for demand pairs assigned to production lines can be obtained. A practical example of touch panel manufacturing system is used to demonstrate the applicability of the MCS approach. Experimental result shows that system reliability is overestimated when buffer storage is assumed to be infinite. Moreover, joint buffer for an MMN is more reliable than buffers are installed separately in different production lines.

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.

Narrower System Reliability Bounds With Incomplete Component Information and Stochastic Process Loading

2017 ◽  
Vol 17 (4) ◽  
Author(s):  
Yao Cheng ◽  
Daniel C. Conrad ◽  
Xiaoping Du
Keyword(s):  
System Reliability ◽  
Operating Conditions ◽  
Reliability Estimation ◽  
Design Stage ◽  
Shared Environment ◽  
Limited Information ◽  
Reliability Bounds ◽  
Component Design ◽  
Wide Range ◽  
Stochastic Load

Incomplete component information may lead to wide bounds for system reliability prediction, making decisions difficult in the system design stage. The missing information is often the component dependence, which is a crucial source for the exact system reliability estimation. Component dependence exists due to the shared environment and operating conditions. But it is difficult for system designers to model component dependence because they may have limited information about component design details if outside suppliers designed and manufactured the components. This research intends to produce narrow system reliability bounds with a new way for system designers to consider the component dependence implicitly and automatically without knowing component design details. The proposed method is applicable for a wide range of applications where the time-dependent system stochastic load is shared by components of the system. Simulation is used to obtain the extreme value of the system load for a given period of time, and optimization is employed to estimate the system reliability bounds, which are narrower than those from the traditional method with independent component assumption and completely dependent component assumption. Examples are provided to demonstrate the proposed method.

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.

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