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

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

Reliability Engineering and System Safety, 2019, vol. 183, issue C, 173-183

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.

Keywords: FMEA; MCGDM; R-BWM; R-TOPSIS; Machine tool; Risk management (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (17)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:183:y:2019:i:c:p:173-183

DOI: 10.1016/j.ress.2018.11.018

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