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Failure mode and effects analysis for submersible pump component using proportionate risk assessment model: a case study in the power plant of Agartala

Author

Listed:
  • Pushparenu Bhattacharjee

    (NIT Agartala)

  • Syed Abou Iltaf Hussain

    (Chandigarh University)

  • V. Dey

    (NIT Agartala)

  • U. K. Mandal

    (NIT Agartala)

Abstract

The comprehensive intention of the present study is to propose a robust mathematical model for Failure Modes and Effect Analysis (FMEA) for submersible pump components. FMEA helps discover potential failures existing within the design of a product, process, or system of components. In this paper, a novel Multi-criteria decision-making method named as Proportionate Risk Assessment Model (PRASM) is proposed to evaluate the most susceptible potential failure modes (PFMs) for the submersible pump. The PRASM method selects the most susceptible PFM by assessing the amount of risk associated with it. This approach is the first of its kind that considers the individual importance of each PFM, as well as exclusive contribution of risk attributes during FMEA evaluation. Decision makers rate the different PFMs concerning the criteria using linguistic terms which are then converted into a non-linear triangular interval-valued fuzzy number $$\left( {NTrIVFN} \right)$$ NTrIVFN . It is a special case of interval-valued fuzzy numbers with non-linear membership functions. This paper also scrutinizes the impact of non-linear membership functions in the process of decision-making. Moreover, ranking is done using the centroid method which is extended for $$NTrIVFN$$ NTrIVFN . Furthermore, the proposed approach with $$NTrIVFN$$ NTrIVFN rating is endorsed with a case study involving failures in components of submersible pumps used in a power plant.

Suggested Citation

  • Pushparenu Bhattacharjee & Syed Abou Iltaf Hussain & V. Dey & U. K. Mandal, 2023. "Failure mode and effects analysis for submersible pump component using proportionate risk assessment model: a case study in the power plant of Agartala," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 14(5), pages 1778-1798, October.
  • Handle: RePEc:spr:ijsaem:v:14:y:2023:i:5:d:10.1007_s13198-023-01981-6
    DOI: 10.1007/s13198-023-01981-6
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    References listed on IDEAS

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    1. Liao, Huchang & Wu, Xingli, 2020. "DNMA: A double normalization-based multiple aggregation method for multi-expert multi-criteria decision making," Omega, Elsevier, vol. 94(C).
    2. Jian-qiang Wang & Zhi-qiu Han & Hong-yu Zhang, 2014. "Multi-criteria Group Decision-Making Method Based on Intuitionistic Interval Fuzzy Information," Group Decision and Negotiation, Springer, vol. 23(4), pages 715-733, July.
    3. Benítez-Fernández, Amalia & Ruiz, Francisco, 2020. "A Meta-Goal Programming approach to cardinal preferences aggregation in multicriteria problems," Omega, Elsevier, vol. 94(C).
    4. Carpitella, Silvia & Certa, Antonella & Izquierdo, Joaquín & La Fata, Concetta Manuela, 2018. "A combined multi-criteria approach to support FMECA analyses: A real-world case," Reliability Engineering and System Safety, Elsevier, vol. 169(C), pages 394-402.
    5. Wan, Shu-Ping & Li, Deng-Feng, 2013. "Fuzzy LINMAP approach to heterogeneous MADM considering comparisons of alternatives with hesitation degrees," Omega, Elsevier, vol. 41(6), pages 925-940.
    6. Rezaei, Jafar, 2016. "Best-worst multi-criteria decision-making method: Some properties and a linear model," Omega, Elsevier, vol. 64(C), pages 126-130.
    7. Rezaei, Jafar, 2015. "Best-worst multi-criteria decision-making method," Omega, Elsevier, vol. 53(C), pages 49-57.
    8. Cuiping Wei & Yuzhong Zhang, 2015. "Entropy Measures for Interval-Valued Intuitionistic Fuzzy Sets and Their Application in Group Decision-Making," Mathematical Problems in Engineering, Hindawi, vol. 2015, pages 1-13, January.
    9. Hu-Chen Liu & Yi-Zeng Chen & Jian-Xin You & Hui Li, 2016. "Risk evaluation in failure mode and effects analysis using fuzzy digraph and matrix approach," Journal of Intelligent Manufacturing, Springer, vol. 27(4), pages 805-816, August.
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