A novel fuzzy hybrid multi-criteria decision-making approach for evaluating maintenance strategies in petrochemical industry

Abstract

Purpose

The purpose of this study is to evaluate maintenance strategies based on fuzzy decision-making trial evaluation and laboratory (DEMATEL) and fuzzy analytic network process (ANP) in the petrochemical industry.

Design/methodology/approach

This study proposes a hybrid-structured multi-criteria decision-making (MCDM) method based on fuzzy Delphi, fuzzy DEMATEL and fuzzy ANP as a structured methodology to assist decision makers in strategic maintenance. The fuzzy Delphi method (FDM) is applied to refine the effective criteria, fuzzy DEMATEL is applied for defining the direction and relationships between criteria and Fuzzy ANP is used for the selection of optimized maintenance strategy.

Findings

The results identify “strategic management complexity” as the top criterion. The predictive maintenance (PdM) with the highest priority is the best strategy. It is followed by reliability-centered (RCM), condition-based (CBM), total productive (TPM), predictive (PM) and corrective maintenance (CM).

Originality/value

Today, companies act in an atmosphere that is known with the features of uncertainty. In this atmosphere, only those companies can survive that have a strategy based on presenting the quality services and products to their customers. Similarly, maintenance as a system plays a vital role in availability and the quality of products, which creates value for customers. The selection of maintenance strategy is a kind of MCDM problem, which includes consideration of different factors. This article considers a broad category of alternates, including CM, PM, TPM, CBM, RCM and PdM.

Citation

Aghaee, A., Aghaee, M., Fathi, M.R., Shoa'bin, S. and Sobhani, S.M. (2021), "A novel fuzzy hybrid multi-criteria decision-making approach for evaluating maintenance strategies in petrochemical industry", Journal of Quality in Maintenance Engineering, Vol. 27 No. 2, pp. 351-365. https://doi.org/10.1108/JQME-04-2019-0036