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Selection of optimum maintenance strategy based on FAHP integrated with GRA–TOPSIS

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  • B. Kirubakaran

    (K. S. Rangasamy College of Technology)

  • M. Ilangkumaran

    (K. S. Rangasamy College of Technology)

Abstract

In today’s competitive environment, industries are required to increase reliability and safety level of their equipment with reasonable cost. Consequently, it is essential to select the appropriate maintenance strategy. In the paper industry, pumping of cooked pulp requires abrasion- and sometimes corrosion-resistant pumps that are able to handle up to 70 % solids content. But the maintenance engineer and supervisor often face failures of the pump. Hence, this article describes the application of multi criteria decision-making (MCDM) technique for the selection of optimum maintenance strategy for pumps used in the paper industry. The proposed hybrid MCDM model comprises fuzzy analytical hierarchy process (FAHP), grey relational analysis (GRA), and technique for order preference by similarity to ideal solution (TOPSIS) technique. The FAHP is used to compute the criteria weights whereas GRA–TOPSIS is used for determining the ranking of alternatives. This study discusses four maintenance strategies: corrective maintenance, predictive maintenance, time-based preventive maintenance, and condition-based maintenance. Four main criteria—safety, cost, added value, and feasibility—have been used to evaluate the optimum maintenance strategy.

Suggested Citation

  • B. Kirubakaran & M. Ilangkumaran, 2016. "Selection of optimum maintenance strategy based on FAHP integrated with GRA–TOPSIS," Annals of Operations Research, Springer, vol. 245(1), pages 285-313, October.
    • Handle: RePEc:spr:annopr:v:245:y:2016:i:1:d:10.1007_s10479-014-1775-3
    DOI: 10.1007/s10479-014-1775-3
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    5. Liang, Decui & Fu, Yuanyuan & Ishizaka, Alessio, 2023. "A consensual group ELECTRE-SORT approach considering the incomparable classes with the application of machine maintenance strategy assignment," Omega, Elsevier, vol. 118(C).
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    11. Ilya Stepanov & Johan Albrecht, 2019. "Decarbonization And Energy Policy Instruments In The Eu: Does Carbon Pricing Prevail?," HSE Working papers WP BRP 211/EC/2019, National Research University Higher School of Economics.
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    15. Teng, Sin Yong & Leong, Wei Dong & How, Bing Shen & Lam, Hon Loong & Máša, Vítězslav & Stehlík, Petr, 2021. "Debottlenecking cogeneration systems under process variations: Multi-dimensional bottleneck tree analysis with neural network ensemble," Energy, Elsevier, vol. 215(PB).
    16. Hua Shi & Mei-Yun Quan & Hu-Chen Liu & Chun-Yan Duan, 2018. "A Novel Integrated Approach for Green Supplier Selection with Interval-Valued Intuitionistic Uncertain Linguistic Information: A Case Study in the Agri-Food Industry," Sustainability, MDPI, vol. 10(3), pages 1-18, March.
    17. Patanjal Kumar & Sachin Kumar Mangla & Yigit Kazancoglu & Ali Emrouznejad, 2023. "A decision framework for incorporating the coordination and behavioural issues in sustainable supply chains in digital economy," Annals of Operations Research, Springer, vol. 326(2), pages 721-749, July.

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