Title: Solving a multi-objective redundancy allocation problem under opportunistic maintenance strategy

Authors: Ali Salmasnia; Mohsen Afsahi; Ali Ghorbanian; Hadi Mokhtari

Addresses: Department of Industrial Engineering, Faculty of Engineering and Technology, University of Qom, Iran ' Department of Industrial Engineering, Faculty of Engineering, Tarbiat Modares University, Iran ' Department of Industrial Engineering, Esfarayen University of Technology, North Khorasan, Iran ' Department of Industrial Engineering, Faculty of Engineering, University of Kashan, Kashan, Iran

Abstract: Redundancy allocation problem includes enhancing system reliability within parallel arrangement of each subsystem component. During recent years, various approaches have been proposed to solve this problem, although most of them only pursue the maximisation of the system reliability. Meanwhile, increasing the number of identical components in each subsystem leads to higher cost of the system. Therefore, this paper presents an approach based on design of experiments (DOE) and data envelopment analysis (DEA) in order to determine the number of redundant component by considering both reliability and cost of the system. Since most of continuous production systems has high setup cost, the proposed approach uses the opportunistic maintenance policy for application of most restorative operations in each system halt.

Keywords: redundancy allocation problem; multi-objective optimisation; experimental design; data envelopment analysis; DEA; opportunistic maintenance policy.

DOI: 10.1504/IJDATS.2017.085897

International Journal of Data Analysis Techniques and Strategies, 2017 Vol.9 No.2, pp.145 - 166

Received: 26 Jun 2015
Accepted: 10 Jan 2016
Published online: 18 Aug 2017 *

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