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Article type: Research Article
Authors: Shahri, Majid Mardani | Jahromi, Abdolhamid Eshraghniaye; * | Houshmand, Mahmoud
Affiliations: Department of Industrial Engineering, Sharif University of Technology, Tehran, Iran
Correspondence: [*] Corresponding author. Abdolhamid Eshraghniaye Jahromi, Department of Industrial Engineering, Sharif University of Technology, Tehran, Iran. Tel.: +989121899546; E-mail: Eshragh@sharif.edu.
Abstract: The purpose of maintenance is to ensure the maximum efficiency and availability of production assets at optimal cost considering quality, safety, and environmental aspects. Assets criticality analysis is one of the main steps in many maintenance methodologies, including Reliability Centered Maintenance. The present study seeks to provide a solution for determining critical assets for more efficient maintenance management. In this regard, an integrated approach of the analytical hierarchy process and fuzzy inference system was proposed based on the concept of the risk matrix. According to the concept of the risk matrix, two main criteria of failure consequences and probability were employed to determine assets criticality. Analytic Hierarchy Process (AHP) was used to consider all sub-criteria of failure consequences and probability. Finally, using two main criteria as inputs, a fuzzy inference system was developed to determine the criticality of the assets. The proposed approach was implemented in a gas refinery; the results showed its effectiveness and applicability in the process of prioritizing assets based on criticality criteria. The proposed approach has the advantages of multi-criteria decision-making techniques, modeling ambiguity and uncertainty in real issues, modeling the process of inference in the human mind, and storing the knowledge of the organization’s expert.
Keywords: Assets criticality analysis, maintenance management, fuzzy inference system, risk matrix, analytical hierarchy process
DOI: 10.3233/JIFS-201407
Journal: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 199-217, 2021
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