Scientia Iranica

Scientia Iranica

Maintenance policy selection considering resilience engineering by a new interval-valued fuzzy decision model under uncertain conditions

Document Type : Research Article

Authors
N. Foroozesh 1
S.M. Mousavi 2
M. Mojtahedi 3
H. Gitinavard 1
1 Department of Industrial Engineering and Management Systems, Amirkabir University of Technology, Tehran, Iran
2 Department of Industrial Engineering, Faculty of Engineering, Shahed University, Tehran, Iran
3 Faculty of Built Environment, University of New South Wales, Sydney, Australia
10.24200/sci.2020.52928.2952
Abstract
Different maintenance policies, including preventive maintenance and predictive maintenance, are introduced to enhance the execution of systems. Maintenance professional experts have faced numerous challenges with distinguishing the proper maintenance policy, among which causes of failure, accessibility, and the capability of maintenance should be regarded seriously. Moreover, most organizations do not have a deliberate and compelling model for evaluating maintenance policies under uncertainty to deal with real-world conditions. The aim of this paper is to introduce a new interval-valued fuzzy (IVF) decision model for the selection of maintenance policy based on order inclination with comparability to ideal solutions by Monte Carlo simulation. This paper introduces novel separation measures and a new IVF-distinguish index via possibilistic statistical concepts (PSCs) which can assist maintenance decision makers to rank maintenance policy candidates. Also, resilience engineering (RE) factors are considered along with conventional evaluation criteria. Finally, the steps of the proposed IVF model-based PSCs are applied to survey a real case in manufacturing industry. Results of the presented model are compared with the recent literature and could help maintenance personnel in identifying the best policy systematically.
Keywords
Maintenance policy
Resilience engineering (RE)
Interval-valued fuzzy sets
Possibilistic statistical concepts
Monte Carlo simulation
Distinguish index

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Scientia Iranica
Volume 29, Issue 2
Transactions on Industrial Engineering (E)
March and April 2022
Pages 783-799

  • Receive Date 13 February 2019
  • Revise Date 13 February 2020
  • Accept Date 08 June 2020