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    Identification of Industrial Occupational Safety Risks and Selection of Optimum Intervention Strategies: Fuzzy MCDM Approach
    (MDPI, 2025) Demir, Guelay; Bouraima, Mouhamed Bayane; Badi, Ibrahim; Stevic, Zeljko; Das, Dillip Kumar
    Over 1.1 million deaths occur annually from workplace injuries and diseases, with higher risks in developing countries. Occupational safety studies commonly use quantitative or qualitative methods, but these often fail to address uncertainty. This research targets the Libyan Steel Company (LISCO), aiming to analyze safety risks and develop a structured approach to identify optimal risk mitigation strategies. To this end, the Fuzzy Weights by ENvelope and SLOpe (F-WENSLO) method was chosen to determine the weights of three main safety risks and a total of 18 sub-risks belonging to them, and the fuzzy Bonferroni mean aggregation operator is applied to synthesize expert opinions. The Fuzzy Alternative Ranking Technique based on Adaptive Standardized Intervals (F-ARTASI) method was used to identify and rank the most appropriate safety interventions. While the primary risks identified under the main criteria and sub-criteria are occupational diseases and noise-induced diseases, with weights of 0.4737 and 0.1313, respectively, the intervention strategy deemed most effective for enhancing occupational safety is behavioral safety programs, which hold a weight of 11.0341. The sensitivity test of the analysis results reveals that although the criteria weights and the parameters used in the analysis vary under various scenarios, the ranking of the alternatives remains consistent. Since the general ranking of the alternatives is the same in other methods, decision makers will reach similar results no matter which method they use. This shows that a flexible and reliable decision-making approach is adopted in the process of optimizing occupational safety risks. This research emphasizes the critical importance of prioritizing occupational diseases and natural hazards in the formulation of occupational safety strategies and thus aims to contribute to the protection of workers in industrial plants such as LISCO.
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    Selection of peanut butter machine by the integrated PSI-SV-MARCOS method
    (Ios Press, 2023) Toslak, Melike; Ulutas, Alptekin; Ure, Salim; Stevic, Zeljko
    Production enterprises are enterprises that produce goods or services that aim to meet human needs such as machinery-equipment materials and labour. In order for a manufacturing enterprise to carry out its activities successfully, it must make the right choice when choosing its inputs. The correct execution of production activities and the selection of machinery, which requires high capital investments, also affect the efficiency of the enterprises, the correct use of materials and their costs. Therefore, it is an important decision for business managers to choose the right machine. At this stage, multi-criteria decision making (MCDM) methods are used for choosing the right machine. MCDM methods are methods used in the evaluation of alternatives using more than one criterion. In addition, the MCDM method is used in machine selection as well as in many areas. In this study, PSI, SV and MARCOS methods, which are among the MCDM methods, were used for peanut butter machine selection. First, the criteria and alternatives to be used for the peanut butter machine selection were determined by interviewing a peanut butter factory manager. In the study, while the criteria weights were determined, PSI and SV methods were used, while the machines were ranked with the MARCOS method. In addition, the MARCOS method was compared with other MCDM methods such as PIV, CODAS and WEDBA methods. After the rankings were found according to the methods, the relations between the rankings were examined using the Spearman Correlation method. The main purpose of the study is to determine the suitable butter machine for a peanut paste production factory. Contribution of this study to the literature PSI, SV and MARCOS methods were used together for the first time. In addition, no study has been found in the literature related to peanut butter machine. Therefore, this study is original and contributes to the literature.