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A novel failure mode and effect analysis model for machine tool risk analysis

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  • Lo, Huai-Wei
  • Liou, James J.H.
  • Huang, Chun-Nen
  • Chuang, Yen-Ching

Abstract

Increasing the reliability of machine tools and reducing possible risks during the manufacturing process is crucial for the future of industry. The failure mode and effects analysis (FMEA) method is reliant upon the experience of experts to determine the primary failure modes and detect the most critical factors for preventing risk. Clearly, an effective method capable of integrating the various different expert opinions is required. This study proposes a novel FMEA model based on multi-criteria group decision-making, which is developed by integrating a rough best–worst method, and modified rough technique for order preference by similarity to an ideal solution for ranking failure modes. The model can overcome some of the limitations of the conventional FMEA. It also includes the expected cost as a risk element to provide a more practical result. The effectiveness of the proposed model is demonstrated by conducting a case study involving a machine tool company. The results indicate that the proposed model can effectively assist managers in evaluating risk factors and identifying critical failure modes.

Suggested Citation

  • Lo, Huai-Wei & Liou, James J.H. & Huang, Chun-Nen & Chuang, Yen-Ching, 2019. "A novel failure mode and effect analysis model for machine tool risk analysis," Reliability Engineering and System Safety, Elsevier, vol. 183(C), pages 173-183.
    • Handle: RePEc:eee:reensy:v:183:y:2019:i:c:p:173-183
    DOI: 10.1016/j.ress.2018.11.018
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    References listed on IDEAS

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    Cited by:

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    6. Liu, Peide & Li, Ying, 2021. "An improved failure mode and effect analysis method for multi-criteria group decision-making in green logistics risk assessment," Reliability Engineering and System Safety, Elsevier, vol. 215(C).
    7. Li, He & Deng, Zhi-Ming & Golilarz, Noorbakhsh Amiri & Guedes Soares, C., 2021. "Reliability analysis of the main drive system of a CNC machine tool including early failures," Reliability Engineering and System Safety, Elsevier, vol. 215(C).
    8. Zhou, Jian-Lan & Tu, Ren-Fang & Xiao, Hai, 2022. "Large-scale group decision-making to facilitate inter-rater reliability of human-factors analysis for the railway system," Reliability Engineering and System Safety, Elsevier, vol. 228(C).
    9. Perry C. Y. Liu & Huai-Wei Lo & James J. H. Liou, 2020. "A Combination of DEMATEL and BWM-Based ANP Methods for Exploring the Green Building Rating System in Taiwan," Sustainability, MDPI, vol. 12(8), pages 1-19, April.
    10. Huang, Jia & You, Jian-Xin & Liu, Hu-Chen & Song, Ming-Shun, 2020. "Failure mode and effect analysis improvement: A systematic literature review and future research agenda," Reliability Engineering and System Safety, Elsevier, vol. 199(C).
    11. Lo, Huai-Wei & Liou, James J.H. & Huang, Chun-Nen & Chuang, Yen-Ching & Tzeng, Gwo-Hshiung, 2020. "A new soft computing approach for analyzing the influential relationships of critical infrastructures," International Journal of Critical Infrastructure Protection, Elsevier, vol. 28(C).
    12. Balali, Amirhossein & Valipour, Alireza & Edwards, Rodger & Moehler, Robert, 2021. "Ranking effective risks on human resources threats in natural gas supply projects using ANP-COPRAS method: Case study of Shiraz," Reliability Engineering and System Safety, Elsevier, vol. 208(C).
    13. Ferenc Bognár & Csaba Hegedűs, 2022. "Analysis and Consequences on Some Aggregation Functions of PRISM (Partial Risk Map) Risk Assessment Method," Mathematics, MDPI, vol. 10(5), pages 1-19, February.
    14. Zhou, Jian-Lan & Yu, Ze-Tai & Xiao, Ren-Bin, 2022. "A large-scale group Success Likelihood Index Method to estimate human error probabilities in the railway driving process," Reliability Engineering and System Safety, Elsevier, vol. 228(C).
    15. Tai-Wu Chang & Huai-Wei Lo & Kai-Ying Chen & James J. H. Liou, 2019. "A Novel FMEA Model Based on Rough BWM and Rough TOPSIS-AL for Risk Assessment," Mathematics, MDPI, vol. 7(10), pages 1-20, September.

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