Abstract
A novel integrated model is proposed to optimize the redundancy allocation problem (RAP) and the reliability-centered maintenance (RCM) simultaneously. A system of both repairable and nonrepairable components has been considered. In this system, electronic components are nonrepairable while mechanical components are mostly repairable. For nonrepairable components, a redundancy allocation problem is dealt with to determine optimal redundancy strategy and number of redundant components to be implemented in each subsystem. In addition, a maintenance scheduling problem is considered for repairable components in order to identify the best maintenance policy and optimize system reliability. Both active and cold standby redundancy strategies have been taken into account for electronic components. Also, net present value of the secondary cost including operational and maintenance costs has been calculated. The problem is formulated as a biobjective mathematical programming model aiming to reach a tradeoff between system reliability and cost. Three metaheuristic algorithms are employed to solve the proposed model: Nondominated Sorting Genetic Algorithm (NSGA-II), Multiobjective Particle Swarm Optimization (MOPSO), and Multiobjective Firefly Algorithm (MOFA). Several test problems are solved using the mentioned algorithms to test efficiency and effectiveness of the solution approaches and obtained results are analyzed.
Highlights
Introduction and Literature ReviewIn general, reliability is defined as ability of a system to meet required performance standards under specified conditions during a determined time horizon
The proposed model in this paper aims at finding proper maintenance policies and effective redundancy strategies
In order to improve system reliability, active and cold standby redundancy strategies and periodic maintenance actions are considered for electronic section and mechanical section, respectively
Summary
Reliability is defined as ability of a system to meet required performance standards under specified conditions during a determined time horizon. Tavakkoli-Moghaddam et al [18] studied RAP for a series-parallel system by considering both active and standby redundancy strategies They formulated the problem as a nonlinear integer programming model and used a Genetic Algorithm to solve the NP-hard problem and maximize system reliability. Chambari et al [26] studied a biobjective RAP trying to maximize system reliability and minimize overall cost along with making decision about using active and/or standby redundancy strategies for a system with nonrepairable components They proposed two metaheuristics, NSGA-II and MOPSO, to solve the problem. Different types of redundancy strategies, repair, and replacement actions are considered in order to model the problem as realistic as possible Other practical constraints such as available budget for purchasing redundant components, volume, weight, and maximum allowed failure rate in each inspection period are taken into account.
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