The Interval Type-2 Fuzzy ELECTRE III Method to Prioritize Machines for Preventive Maintenance
International Journal of Industrial Engineering and Production Research, ISSN: 2345-363X, Vol: 32, Issue: 4
2021
- 4Citations
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Article Description
Preventive maintenance (PM) of machines and equipment plays the critical role in a factory or an organization. It can decrease the number of failures, increase reliability, and minimize total costs of production systems. The duty of maintenance section managers is to prioritize machines and then, implement PM programs for them. Since machines have different measures with respect to the maintenance costs, reliability, mean time between failures (MTBF), availability of spare parts, etc., the machines evaluation problem can be considered as a multiple criteria decision-making (MCDM) problem. Accordingly, the MCDM techniques can be applied to solve them. This paper is aimed at extending a version of the ELimination Et Choix Traduisant la REalité (ELECTRE III) method to interval type-2 fuzzy sets (IT2FSs) where curved membership functions (MFs) are applied. The extended ELECTRE III methodology is then utilized to a maintenance group MCDM (GMCDM) matrix including the quantitative (QNC) and qualitative criteria (QLC). In the proposed approach, the criteria weights, the assessment of alternatives with respect to criteria, and the thresholds are stated with Gaussian interval type-2 fuzzy sets (GIT2FSs). In order to show the effectiveness and applicability of the proposed approach, a case study and an illustrative example are exhibited using real decision-making problems. Due to the high correlation coefficients among our method and the others, it can be considered as a valid and reliable approach to prioritize machines for PM.
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