Fine–kinney-based occupational risk assessment using intuitionistic fuzzy todim

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Abstract

This chapter applies a novel occupational risk assessment approach which merges TODIM with the Fine–Kinney method under the intuitionistic fuzzy set concept. Risk parameters of Fine–Kinney and OHS experts are weighted by an intuitionistic fuzzy weighted averaging (IFWA) aggregation operator. Hence, hazards are quantitatively evaluated and prioritized using the proposed approach. To illustrate the novel risk assessment approach, processes of the gun and rifle assembly line of a factory are handled. A comprehensive risk assessment is carried out to improve operational safety and reliability in the industry. We adapt intuitionistic fuzzy sets in the existing study since they reflect uncertainty with the aid of their membership and nonmembership functions in decision-making better than classical fuzzy extensions. An additional sensitivity analysis by changing the attenuation parameter of TODIM is performed to test the validity of the approach. Finally, the Python codes in the implementation of the proposed approach are given for scholars and practitioners for usage in further studies.

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APA

Gul, M., Mete, S., Serin, F., & Celik, E. (2021). Fine–kinney-based occupational risk assessment using intuitionistic fuzzy todim. In Studies in Fuzziness and Soft Computing (Vol. 398, pp. 69–89). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-52148-6_5

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