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Article type: Research Article
Authors: Tatar, Veysela; * | Yazicioglu, Osmanb | Ayvaz, Berkb
Affiliations: [a] Istanbul Commerce University, Institute of Science and Technology, Istanbul, Türkiye | [b] Istanbul Commerce University, Faculty of Engineering, Industrial Engineering, Istanbul, Türkiye
Correspondence: [*] Corresponding author. Veysel Tatar, Istanbul Commerce University, Institute of Science and Technology, Istanbul, Türkiye. E-mail: [email protected].
Abstract: Work-related musculoskeletal disorders (WMSDs) are the most common occupational health problems in agriculture workers due to repetitive and excessive force movement activities involved in their job processes. The Fine-Kinney method has been commonly used as a quantitative evaluation method in risk assessment studies. Classically, the risk value via Fine–Kinney is calculated by the mathematical multiplication irrespective of the degree of importance of each risk parameter (probability (P), exposure (E), and consequence (C)). Hence, a novel risk management model was proposed based on integrating Fine-Kinney and spherical fuzzy AHP-TOPSIS. First, each risk parameter is weighted using the spherical fuzzy AHP (SF-AHP). Second, the spherical fuzzy TOPSIS (SF-TOPSIS) method is used for hazard ranking. The proposed model is applied to evaluate risks in tea harvesting workers for work-related musculoskeletal disorders. Subsequently, a sensitivity analysis is carried out to test the proposed model. Finally, we compare the proposed model’s applicability and effectiveness with the spherical fuzzy COmbinative Distance-based ASsessment (SF-CODAS) method based on Fine-Kinney. The ranking similarity between the proposed Fine-Kinney-based SF-TOPSIS and SF-CODAS methods is checked by applying Spearman’s rank correlation coefficient, in which 92% of rankings are matched.
Keywords: Risk assessment, Fine–Kinney method, Spherical fuzzy sets, Work-related musculoskeletal disorders (WMSDs), AHP-TOPSIS
DOI: 10.3233/JIFS-222652
Journal: Journal of Intelligent & Fuzzy Systems, vol. 44, no. 2, pp. 2305-2323, 2023
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