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Improved risk assessment model based on rough integrated clouds and ELECTRE-II method: an application to intelligent manufacturing process

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Abstract

Failure Modes and Effect Analysis (FMEA) is a significant mathematical technique for the risk assessment of the failure modes in the industrial automation and robotics which are used for various manufacturing process. Due to the existence of uncertainty and diversity in the assessment information, various FMEA techniques depend on fuzziness, rough approximations, and other uncertain theories have been presented. A novel approach to discuss various types of uncertainties and randomness is proposed by integrating the rough numbers clouds and and ELimination and Choice Translating REality (ELECTRE) II method in this research paper. Rough integrated clouds, a form of normal cloud evaluations, have been utilized to deal with ambiguity and randomness with the initial parameters and suppository functions. First, the weights are calculated using objective and subjective aspects of vagueness based on statistical expectation and the maximum deviation method instead of using decision-makers’ preferences. The standard derivation of cloud evaluation is computed from entropy and hyperentropy values instead of existing complicated formula based on central mean value. Second, rough approximation technique is applied on the initial data without additional information which is then transformed into cloud evaluations to deal with fuzziness and randomness using a single mathematical approach. The proposed rough integrated cloud model is a risk assessment approach to recognise the potential risks and their effects. The neutral, weak, and strong discordance and concordance relations are derived to discuss the similarities, differences, and pairwise relations of failure modes. Third, the normalization method is based on two formulae instead of a single formula considering both benefit and cost criteria. Finally, the presented approach is described with a case study to identify the failure modes in automatic robotics. The applications of presented approach have been observed in many research domains like in intelligent manufacturing processes and engineering problems. The comparison of the proposed approach with certain existing techniques is presented to elaborate its out-performance, rationality, and efficacy of findings.

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Authors and Affiliations

  1. Department of Mathematics, GC Women University, Sialkot, 51310, Pakistan

    Musavarah Sarwar, Wajeeha Gulzar & Samia Ashraf

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  1. Musavarah Sarwar
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  2. Wajeeha Gulzar
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  3. Samia Ashraf
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Contributions

MS and WG: concept, design, analysis, modeling, writing, modifications, and corrections of the manuscript. SA: proof reading of the manuscript.

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Correspondence to Musavarah Sarwar.

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Sarwar, M., Gulzar, W. & Ashraf, S. Improved risk assessment model based on rough integrated clouds and ELECTRE-II method: an application to intelligent manufacturing process. Granul. Comput. 8, 1533–1560 (2023). https://doi.org/10.1007/s41066-023-00385-y

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