Redundancy Allocation for Serial-Parallel System Considering Heterogeneity of Components

2018 ◽  
Author(s):  
Zhicheng Zhu ◽  
Yisha Xiang ◽  
David Coit
Keyword(s):  
System Design ◽  
System Reliability ◽  
Raw Materials ◽  
Parallel System ◽  
Redundancy Allocation Problem ◽  
Redundancy Allocation ◽  
Numerical Examples ◽  
System Cost ◽  
The Impact ◽  
Cost Components

The redundancy allocation problem (RAP) for series-parallel system is a system design problem by selecting an appropriate number of components from multiple choices for desired objectives, such as maximizing system reliability, minimizing system cost. RAP has been extensively studied in the last decades. The majority of existing RAP models assume that components for selection are from homogeneous populations. However, due to manufacturing difficulties and variations in raw materials, many manufactured components/parts are heterogeneous, consisting of multiple subpopulations. In this research, we consider a typical RAP with the objective of maximizing the system reliability subject to the constraint of system cost. Components in each choice are assumed to be degradation-based, and each choice consists one normal subpopulation and several abnormal subpopulations. Numerical examples are investigated to illustrate the impact of the component heterogeneity.

Application of the NSGA-II algorithm to a multi-period inventory-redundancy allocation problem in a series-parallel system

2017 ◽  
Vol 160 ◽  
pp. 1-10 ◽  
Author(s):  
Najmeh Alikar ◽  
Seyed Mohsen Mousavi ◽  
Raja Ariffin Raja Ghazilla ◽  
Madjid Tavana ◽  
Ezutah Udoncy Olugu
Keyword(s):  
Parallel System ◽  
Allocation Problem ◽  
Nsga Ii ◽  
Redundancy Allocation Problem ◽  
Redundancy Allocation

ANT COLONY OPTIMIZATION ALGORITHM FOR HETEROGENEOUS REDUNDANCY ALLOCATION IN MULTI-STATE SERIES-PARALLEL SYSTEMS

2009 ◽  
Vol 16 (02) ◽  
pp. 163-186 ◽  
Author(s):  
MANJU AGARWAL ◽  
VIKAS K. SHARMA
Keyword(s):  
System Design ◽  
Ant Colony Optimization ◽  
Optimization Algorithm ◽  
System Reliability ◽  
Optimization Problems ◽  
Ant Colony ◽  
System Structure ◽  
Ant Colony Optimization Algorithm ◽  
Redundancy Allocation ◽  
Demand Distribution

This paper addresses the redundancy allocation problem of multi-state series-parallel reliability structures where each subsystem can consist of maximum two types of redundant components. The objective is to minimize the total investment cost of system design satisfying system reliability constraint and the consumer load demand. The demand distribution is presented as a piecewise cumulative load curve. The configuration uses the binary components from a list of available products to provide redundancy so as to increase system reliability. The components are characterized by their feeding capacity, reliability and cost. A system that consists of elements with different reliability and productivity parameters has the capacity strongly dependent upon the selection of components constituting its structure. An ant colony optimization algorithm has been presented to analyze the problem and suggest an optimal system structure. The solution approach consists of a series of simple steps as used in early ant colony optimization algorithms dealing with other optimization problems and still proves efficient over the prevalent methods with regard to solutions obtained/computation time. Three multi-state system design problems have been solved for illustration.

scholarly journals Application of an Intelligent Hybrid Metaheuristic Algorithm for Multiobjective Redundancy Allocation Problem with Sustainable Maintenance

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Tri Tjahjono ◽  
Dinesh Mavaluru ◽  
Dowlath Fathima ◽  
Akila Thiyagarajan ◽  
Wanich Suksatan ◽  
...  
Keyword(s):  
System Reliability ◽  
Failure Time ◽  
Spare Parts ◽  
Allocation Problem ◽  
Test Problems ◽  
Redundancy Allocation Problem ◽  
Redundancy Allocation ◽  
Repair Costs ◽  
Whale Optimization ◽  
Distribution Parameters

The present study aimed to optimize the redundancy allocation problem based on sustainable maintenance. For this purpose, the goal is to design a complex system based on redundancy allocation by considering the weight and reliability criteria of the system and the maintenance and repair costs through the sustainability approach. In this regard, a mathematical model has been developed. This model minimizes system reliability and system weight simultaneously. There are also budget constraints on repair costs, environmental costs, purchase of spare parts, and energy risk costs. In order to optimize this model, a hybrid algorithm based on Whale Optimization Algorithm (WOA), Genetic Algorithm (GA), and Simulated Annealing (SA) is proposed. Accordingly, 81 test problems are provided and optimized by the proposed algorithm. The obtained numerical results indicate that, with increasing failure time of each component, the system’s reliability increases and the weight of the whole system increases. Moreover, changing the Weibull distribution parameters directly affects the total amount of system reliability, but does not have a definite and accurate effect on the total weight of the system. Moreover, increasing the budget for maintenance leads to finding solutions with more reliability and less weight.

scholarly journals A Novel Constraints Model of Credibility-Fuzzy for Reliability Redundancy Allocation Problem by Simplified Swarm Optimization

2021 ◽  
Vol 11 (22) ◽  
pp. 10765
Author(s):  
Hota Chia-Sheng Lin ◽  
Chia-Ling Huang ◽  
Wei-Chang Yeh
Keyword(s):  
Climatic Factors ◽  
Raw Materials ◽  
Fuzzy Theory ◽  
Allocation Problem ◽  
Credibility Theory ◽  
Swarm Optimization ◽  
Redundancy Allocation Problem ◽  
Redundancy Allocation ◽  
Fuzzy Constraints ◽  
Constraints Model

A novel constraints model of credibility-fuzzy for the reliability redundancy allocation problem (RRAP) is studied in this work. The RRAP that must simultaneously decide reliability and redundancy of components is an effective approach in improving the system reliability. In practice various systems, the uncertainty condition of components used in the systems, which few studies have noticed this state over the years, is a concrete fact due to several reasons such as production conditions, different batches of raw materials, time reasons, and climatic factors. Therefore, this study adopts the fuzzy theory and credibility theory to solve the components uncertainty in the constraints of RRAP including cost, weight, and volume. Moreover, the simplified swarm optimization (SSO) algorithm has been adopted to solve the fuzzy constraints of RRAP. The effectiveness and performance of SSO algorithm have been experimented by four famous benchmarks of RRAP.

Distributionally Robust Design for Redundancy Allocation

2020 ◽  
Vol 32 (3) ◽  
pp. 620-640
Author(s):  
Shuming Wang ◽  
Yan-Fu Li
Keyword(s):  
System Reliability ◽  
Linear Program ◽  
Allocation Problem ◽  
Mixed Integer ◽  
Modeling Framework ◽  
Worst Case ◽  
Redundancy Allocation Problem ◽  
Redundancy Allocation ◽  
Case System ◽  
Distributionally Robust

In this paper, we consider a redundancy allocation problem for a series parallel system with uncertain component lifetimes that minimizes system costs while safeguarding system reliability over a given threshold level. We consider mixed redundancy strategies of cold standby and active redundancy with multiple types of components. We address lifetime uncertainty in the framework of distributionally robust optimization. In particular, we assume the probability distributions of the component lifetimes are not exactly known with only limited distributional information (e.g., mean, dispersion, and support) being available. We protect the worst-case system reliability constraint over all the possible component lifetime distributions that are consistent with the given distributional characteristics. The proposed modeling framework enjoys computationally attractive structures. The evaluation of the worst-case system reliability in our redundancy allocation problem can be transformed into a linear program, and the resulting overall redundancy allocation optimization problem can be cast as a mixed integer linear program that does not induce any additional integer variables (other than original allocation variables). In addition, the extreme joint distribution of component lifetimes can be efficiently recovered by solving a linear program. Our modeling framework can also be extended to incorporate the startup failures and common-cause failures for cold standbys and active parallels, respectively, to cater to more computationally complex settings. Finally, the computational experiments positively demonstrate the performance of the proposed approach in protecting system reliability.

Redundancy allocation problem in a bridge system with dependent subsystems

2018 ◽  
Vol 233 (4) ◽  
pp. 658-669
Author(s):  
Kamyar Sabri-Laghaie ◽  
Milad Eshkevari ◽  
Mahdi Fathi ◽  
Enrico Zio
Keyword(s):  
System Reliability ◽  
Allocation Problem ◽  
Bridge Structure ◽  
Swarm Optimization ◽  
Redundancy Allocation Problem ◽  
Redundancy Allocation ◽  
Reliability Design ◽  
Copula Theory ◽  
Real World Applications ◽  
System Configurations

The redundancy allocation problem is an important problem in system reliability design. Many researchers have investigated the redundancy allocation problem under different assumptions and for various system configurations. However, most of the studies have disregarded the dependence among components and subsystems. In real-world applications, the performance of components and subsystems can affect each others. For instance, the heat radiated by a subsystem can accelerate degradation of adjacent components or subsystems. In this article, a procedure is proposed for solving the redundancy allocation problem of a bridge structure with dependent subsystems. Copula theory is utilized for modeling dependence among subsystems, and artificial neural network and particle swarm optimization are applied for finding the best redundancy allocation. A numerical example is included to elaborate the proposed procedure and show its applicability.

scholarly journals MILP Models for Complex System Reliability Redundancy Allocation with Mixed Components

2020 ◽  
Vol 32 (3) ◽  
pp. 600-619
Author(s):  
Young Woong Park
Keyword(s):  
Complex System ◽  
Sample Size ◽  
System Reliability ◽  
Optimal Allocation ◽  
Resource Constraints ◽  
Optimal Solution ◽  
Allocation Problem ◽  
Mixed Integer ◽  
Redundancy Allocation Problem ◽  
Redundancy Allocation

The redundancy allocation problem (RAP) aims to find an optimal allocation of redundant components subject to resource constraints. In this paper, mixed integer linear programming (MILP) models and MILP-based algorithms are proposed for complex system reliability redundancy allocation problem with mixed components, where the system have bridges or interconnecting subsystems and each subsystem can have mixed types of components. Unlike the other algorithms in the literature, the proposed MILP models view the problem from a different point of view and approximate the nonconvex nonlinear system reliability function of a complex system using random samples. The solution to the MILP converges to the optimal solution of the original problem as sample size increases. In addition, data aggregation-based algorithms are proposed to improve the solution time and quality based on the proposed MILP models. A computational experiment shows that the proposed models and algorithms converge to the optimal or best-known solution as sample size increases. The proposed algorithms outperform popular metaheuristic algorithms in the literature.

scholarly journals On constrained reliability maximization using active redundancy in coherent systems with non-overlapping subsystems

2014 ◽  
Vol 5 (1) ◽  
pp. 33-39
Author(s):  
Debasis Bhattacharya ◽  
Soma Roychowdhury
Keyword(s):  
Sensitivity Analysis ◽  
Exact Solution ◽  
System Design ◽  
System Reliability ◽  
Optimal Allocation ◽  
Resource Constraints ◽  
Coherent Systems ◽  
Numerical Examples ◽  
Fail Safe ◽  
The Cost

The paper investigates a problem of constrained reliability maximization by allocating redundancy and proposes how to solve it for a broad group of complex coherent systems. Redundancy is an effective engineering tool to enhance system reliability to make a system fail-safe. Since adding redundancy increases the cost and complexity of a system design, it should be used wisely. The work considers an exact solution to the problem under resource constraints and finds optimal redundancy numbers. The proposed method can accommodate any number of constraints. Numerical examples have been included. A sensitivity analysis has been carried out to show how sensitive the optimal allocation of redundant components and the gain in system reliability are to the budget allocation.

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