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- MakaleYalnız künye2024Scopus SJRQ1A stratified Bayesian decision-making model for occupational risk assessment of production facilities
Gul, Muhammet; Yucesan, Melih; Karci, Coskun
In the production industry, harmony and good management of the workplace environment, production machinery/vehicles, and workers are necessary to carry out production by occupational health and safety (OHS) principles. Therefore, occupational risk assessment (ORA) is crucial for manufacturing-based industries. When deciding on the prioritization of risks in ORA, adding to the analysis “how the parameters defining the risk changes in possible different states in the future” positively affects the soundness of decision-making. Therefore, this study aims to develop a unique ORA model handling future changes in the importance levels of risk parameters in the risk assessment process. To this aim, the concept of stratification and the best-worst method (BWM) are used together to determine the importance weights of the risk parameters in the ORA. In addition, the Bayesian version of BWM considers more than one expert's evaluations without losing information. In a nutshell, an approach called stratified Bayesian BWM (SBBWM) that can be used for further studies has been introduced to the literature. The technique determines the priority scores of each hazard by technique for order preference by similarity to the ideal solution sorting (TOPSIS-Sort) method. Thus, while determining each hazard's priority score and order, the class of this risk has also been determined. The proposed approach evaluated thirty-six risks encountered in manufacturing, storage, handling, and laboratory processes of a flour production facility. Control measures to be taken for each risk were also determined. Methodologically, various scenario analyses and sensitivity studies were conducted to reveal how the results changed in different conditions. The proposed approach provides a more comprehensive procedure for production facilities than traditional methods and avoids the deficiencies of traditional methods.
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İncele - MakaleAçık Erişim2023Scopus SJRQ1COVID-19 safe campus evaluation for universities by a hybrid interval type-2 fuzzy decision-making model
Baskak, Dilber; Ozbey, Sumeyye; Yucesan, Melih; Gul, Muhammet
The fight against the COVID-19 pandemic, which has affected the whole world in recent years and has had devastating effects on all segments of society, has been one of the most important priorities. The Turkish Standards Institution has determined a checklist to contribute to developing safe and clean environments in higher education institutions in Turkey and to follow-up on infection control measures. However, this study is only a checklist that makes it necessary for decision-makers to make a subjective evaluation during the evaluation process, while the need to develop a more effective, systematic framework that takes into account the importance levels of multiple criteria has emerged. Therefore, this study applies the best-worst method under interval type-2 fuzzy set concept (IT2F-BWM) to determine the importance levels of criteria affecting the “COVID-19 safe campus” evaluation of universities in the context of global pandemic. A three-level hierarchy consisting of three main criteria, 11 sub-criteria, and 58 sub-criteria has been created for this aim. Considering the hierarchy, the most important sub-criterion was determined as periodic disinfection. The high contribution of the interval-valued type-2 fuzzy sets in expressing the uncertainty in the decision-makers’ evaluations and the fact that BWM provides criterion weights with a mathematical optimization model that produces less pairwise comparisons and higher consistency are the main factors in choosing this approach. Simple additive weighting (SAW) has also been injected into the IT2F-BWM to determine the safety level of any university campus regarding COVID-19. Thus, decision-makers will be better prepared for the devastating effects of the pandemic by first improving the factors that are relatively important in the fight against the pandemic. In addition, a threshold value will be determined by considering all criteria, and it will prepare the ground for a road map for campuses. A case study is employed to apply the proposed model, and a comparison study is also presented with the Bayesian BWM to validate the results of the criteria weights.
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İncele - MakaleYalnız künye2023Scopus SJRQ4Development of a best-worst method based MCDM approach for solar power plant location selection: an application to Tunceli, Turkey
Aykac, Yunus Emre; Yucesan, Melih; Gul, Muhammet
Solar energy stands out with its increasing potential in the world. The decision to choose the location of a solar power plant is very important due to the investment return. In this study, a solar power plant site selection for Tunceli, Turkey is studied with a two-stage multi-criteria decision-making approach. In the first stage, the importance levels of the determined nine factors are obtained by the best-worst method (BWM). In the second stage, the most appropriate site is selected among the eight districts of Tunceli. As a result of the first stage, solar and fault line emerged as the most and least important factor, respectively. The second stage showed that Pertek district is the most suitable place. A comparative framework has been created including five different MCDM methods, which strengthens the final decision's accuracy and reveals whether each method's results are correlated.
AtıfScopus5OpenAlex3İncele - Kitap BölümüYalnız künye2023Determining the Criterion Weights for the Selection of Volunteers in Humanitarian Organizations by the Best-Worst Method
Ozdemir, Umit; Mete, Suleyman; Gul, Muhammet
Today, it is vital for humanitarian organizations operating in many different fields to select volunteers from the determining criteria according to the needs of the institution. Failure to select volunteers in accordance with the institution's needs may cause the volunteers to be unable to continue their duties and interrupt the institution's work. When choosing volunteers, it is essential for effective volunteer management to classify (expert, experienced, inexperienced, and insufficient) them according to the institution’s needs and assign them starting from the volunteer in the best class volunteer when necessary. The aim of this study is to determine the criteria weights in the classification of volunteers who want to participate in search and rescue activities in humanitarian aid organizations according to the criteria determined before their assignment. In this study, a questionnaire is applied to field experts in Turkey to determine the most important and least important criteria, then criteria weights are calculated by using the Best-Worst Method (BWM). The findings obtained as a result of our study are evaluated and suggestions are made on how to improve it for future studies.
AtıfScopus1OpenAlex1İncele - MakaleYalnız künye2023Scopus SJRQ1A holistic failure modes and effects analysis for university plastic injection laboratory under Bayesian Network
Yucesan, Melih; Gul, Muhammet; Pamučar, Dragan
University Research & Development (R&D) laboratories are facilities used for research and manufacturing activities in engineering and basic science fields. Various filling materials are used in plastic R&D laboratories to improve the mechanical properties of thermoplastics or to recycle waste materials. The use of filling materials causes changes in plastic production parameters. This study dealt with the risks arising from extrusion, injection and shredder in a plastic injection laboratory, which led to the inability to manufacture the appropriate product under a holistic methodology. The proposed holistic methodology merges the concepts of failure mode and effects analysis (FMEA), fuzzy best-worst method (FBWM), and a rule-based three-hierarchical Bayesian network (RB-THBN). First, 15 root risks have been identified under a three-stage hierarchy with the support of laboratory decision makers. Then, questionnaires were created using the FMEA concept. The importance values (degree of belief-DoB) of three different FMEA parameters (severity, occurrence and detection) by experts for each risk have been calculated with FBWM. And finally, the RB-THBN has been created, and the final risk values have been computed using the linear utility function for the network. The system has been analyzed via a Bayesian modeling software. A validity test and a control measures planning has also been executed. According to the results, the highest root risk has been determined as “E2-The prepared mixture is not homogeneous” with a crisp risk score of 0.639559. In addition, “Failure due to extrusion” has been determined as the highest risk category with a score of 0.564059. It was discussed in detail that these risks arise from homogenization and how the used mixture should be homogenized. A comparative study among traditional FMEA, FMEA extended under FBWM and the proposed approach is performed to observe the differences in final ranking of root risks and to highlight the arguments that strengthen the advantages of the proposed method over the other two.
AtıfScopus7WoS7OpenAlex8İncele - MakaleAçık Erişim2022Scopus SJRQ1An interval type-2 fuzzy enhanced best–worst method for the evaluation of ship diesel generator failures
Yucesan, Melih; Başhan, Veysi; Demirel, Hakan; Gul, Muhammet
The environmental destruction in our century necessitates the implementation of more safety-based rules and the strict implementation of failure analysis, especially in the maritime sector. The generator system, considered the ship's powerhouse, is expected to be ready and well-maintained for efficient and safe operations. This study proposes a new methodology to analyze ship generator failures. This method includes a version of the best-worst multi-criteria decision-making method enriched with interval type-2 fuzzy logic (IT2FE-BWM). Enrichment with interval type-2 fuzzy numbers shows that a parameter about how much the decision-maker trusts the pairwise comparisons are added to the model. Thus, a more sensitive methodology has been proposed for the confidence of the maritime sector evaluators. A solid decision mechanism has been developed to prioritize generator failures. In addition, a comparison study with some other BWM derivatives and a creative sensitivity analysis were added to this study and its robustness was tested.
AtıfScopus25OpenAlex24İncele - MakaleYalnız künye2020Scopus SJRQ1A manufacturing failure mode and effect analysis based on fuzzy and probabilistic risk analysis
Gul, Muhammet; Yucesan, Melih; Celik, Erkan
This study proposes an improved failure mode and effect analysis (FMEA) with fuzzy Bayesian Network (FBN) and fuzzy best-worst method (FBWM) to assess failures in plastic production. To eliminate the drawbacks of the classical risk priority number (RPN) computation of FMEA, this approach is developed. Unlike classical RPN, a new parameter hierarchy is constructed, and three sub-parameters are injected into the approach. These parameters are weighted by the aid of FBWM. Hereafter, a fuzzy rule-based system is constructed by incorporating Bayesian Network (BN). Also, a sensitivity analysis is performed to observe the final FMEA score changes in accordance with the change of subjective probability values. Finally, a comparative analysis with two approaches of classical FMEA and FBWM-based FMEA (without a fuzzy rule-based system incorporating BN) is fulfilled. The results of the study are strengthened with the experts’ opinions regarding the importance of failure modes for the final product and the whole system and supported them by experience feedback in the observed facility.
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