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An integrated rough ELECTRE II approach for risk evaluation and effects analysis in automatic manufacturing process

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Abstract

Smart manufacturing is an essential part of fourth industrial revolution in which robotic machines can control and perceive automatically to provide effectiveness and convenience in production process. However, the existence of potential failures and defects not only influence the manufacturing process but also damages the resources and cause negative impacts on environment. Failure modes and effects analysis (FMEA) is a key approach to identify and eliminate possible failures and evaluate the risks from design, system and process. This research paper provides a novel FMEA approach for risk evaluation by integrating rough set theory and ELimination and Choice Translating REality (ELECTRE) II method to handle the subjectivity and uncertainty in experts’ judgements without much prior information, membership functions and additional adjustments. Rough numbers are used to study uncertainty in linguistic terms using intervals instead of single fixed values. The proposed approach is formulated by defining different types of concordance and discordance sets using optimization techniques based on statistical dispersion and maximum deviation method. The presented technique shows the strong, weak and neutral pairwise relations among failure modes by systemically comparing them from each risk component. The distance functions and averaging methods are applied to check the similarities and differences among error modes which improves the accuracy of the results. The developed rough FMEA approach is applied to identify the potential failures of robot working in optical cable industry and evaluate the risk components of manufacturing and production process. Rough ELECTRE II approach can be effectively applied to enhance the efficiency of working conditions and prevent the loss of crude materials and energy.

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Correspondence to Peide Liu.

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Sarwar, M., Akram, M. & Liu, P. An integrated rough ELECTRE II approach for risk evaluation and effects analysis in automatic manufacturing process. Artif Intell Rev 54, 4449–4481 (2021). https://doi.org/10.1007/s10462-021-10003-5

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