Abstract
This chapter proposed an improved Fine–Kinney occupational risk assessment approach using a well-known MCDM method “TOPSIS” under interval type-2 fuzzy set concept. It is defined as a technique for order preference by similarity to ideal solution by Hwang and Yoon [1]. It is based on separation from ideal and anti-ideal solution concept. Since the initial crisp data-based version is insufficient by time in reflecting the uncertainty in decision-maker’s opinions, fuzzy sets are integrated to the TOPSIS algorithm to provide a solid and comprehensive method. Interval type-2 fuzzy set is an improved version of the type-1 fuzzy set. It is also a special version of a general type-2 fuzzy set. Since general type-2 fuzzy systems contain complex computational operations, they cannot be easily applied to real-world problems such as occupational risk assessment. Interval type-2 fuzzy sets are the most frequently used type-2 fuzzy sets due to their ability in handling more uncertainty and producing more accurate and solid results. The Fine–Kinney concept is merged with the interval type-2 fuzzy set concept and TOPSIS for the first time through the literature. To demonstrate the applicability of the proposed approach, a case study is carried out in a chrome plating unit of a gun factory. Some beneficial validation and sensitivity analysis are also performed. Finally, as a creative contribution of our book, the implementation of the proposed approach in Python is performed.
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Notes
- 1.
Reprinted from Ref. [5], Copyright 2014, with permission from Elsevier
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Gul, M., Mete, S., Serin, F., Celik, E. (2021). Fine–Kinney-Based Occupational Risk Assessment Using Interval Type-2 Fuzzy TOPSIS. In: Fine–Kinney-Based Fuzzy Multi-criteria Occupational Risk Assessment. Studies in Fuzziness and Soft Computing, vol 398. Springer, Cham. https://doi.org/10.1007/978-3-030-52148-6_3
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