Sürdürülebilir Kalkınma Amaçları
Yayınlar
- 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.
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İncele - Kitap BölümüYalnız künye2023A GIS-Based BWM Approach for the Location Selection of Solar Power Plant in Tunceli Province (Turkey)
Konurhan, Zekeriya; Yucesan, Melih; Gul, Muhammet; Rezaei, J; Brunelli, M; Mohammadi, M
The world has recently tended to turn to renewable energy sources due to the serious negative impact of fossil fuels on the environment. One of the top priorities for solar energy is the selection of the most suitable location of the solar power plant to be established. In this study, the most suitable solar power plant location selection for Tunceli, a province located in the eastern part of Turkey, is studied with an approach based on Geographic Information System (GIS) and the best-worst method (BWM). A weighting was performed using the BWM model for 16 sub-criteria under four the main criteria of “climatic conditions, geographical conditions, land conditions, and location (distance to crucial points)”. Afterward, maps were created for these criteria, and a 6-point scale in the legends of each map for each sub-criteria was applied. Finally, the most suitable locations were determined with GIS-based calculations.
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İncele - Kitap BölümüYalnız künye2023Avalanche Risk Analysis by a Combined Geographic Information System and Bayesian Best-Worst Method
Konurhan, Zekeriya; Yücesan, Melih; Gul, Muhammet
The formation of avalanches is related to the land structure, climatic conditions, and snow cover. It is usually seen in mountainous and sloping terrains without vegetation. In Turkey, especially in Eastern Anatolia and the Black Sea Region, which have high elevations, avalanche events are observed. This study aims to perform a risk analysis by integrating the Bayesian Best-Worst method (BWM) and Geographic Information System (GIS) for Tunceli province, which is the scene of significant avalanche events. Bayesian BWM is a method that improves the original BWM by effectively integrating the preferences of multiple experts. In the study, 16 sub-criteria, such as elevation, slope, and the number of snowy days, were determined, and experts evaluated these criteria through questionnaires created. The weight of each criterion were calculated using the Bayesian-BWM. By integrating the criteria weights from the Bayesian-BWM model into GIS, the risky places for natural avalanche disasters in Tunceli province were determined, according to which the risk in the northern part of the study area is identified as high.
AtıfScopus5İncele - Kitap BölümüYalnız künye2023A Multi-parameter Occupational Safety Risk Assessment Model for Chemicals in the University Laboratories by an MCDM Sorting Method
Gul, Muhammet; Yucesan, Melih; Karacahan, Mehmet Kayra
University laboratories are high-risk working environments where many chemicals coexist to conduct teaching and scientific research. The frequent occurrence of such chemical-related occupational accidents in recent times highlights the importance of ensuring these units’ safety in universities for researchers, students, workplaces, and institutions. In occupational safety risk assessment, very few studies have grouped risks. Many of them also ignored some important risk parameters. Overcoming these disadvantages, this study developed a multi-parameter and multi-criteria decision-making (MCDM) sorting-based methodology for the occupational safety risk assessment of chemicals in a university laboratory. First, six different risk parameters (probability, severity, exposure, detectability, worsening factor, sensitivity to non-usage of personal protective equipment) were determined. The weight value was calculated using the best–worst method (BWM). Then, a risk priority value and classification for each chemical with TOPSIS-Sort, the MCDM sorting method. Finally, some control measures are recommended to reduce the safety risk of the laboratory. The applicability of the proposed methodology has been tested with a real case study. The methodology is intended to adapt to university laboratories’ risk assessment and become a primary reference for university safety analysts.
AtıfScopus2OpenAlex1İncele - 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 Erişim2023Scopus SJRQ1Integrating stratified best–worst method and GIS for landslide susceptibility assessment: a case study in Erzurum province (Turkey)
Konurhan, Zekeriya; Yucesan, Melih; Gul, Muhammet
Landslides are among the most destructive geological disasters that seriously damage human life and infrastructures. Landslides mainly occur in mountainous regions around the world. One of the key processes to reduce these damages is to uncover landslide-exposed areas through different data-driven methods such as Geographical Information System (GIS) and multi-criteria decision-making (MCDM). In the literature, there are many studies developed with these fundamental tools. In this study, unlike the literature, a new landslide susceptibility assessment model is proposed by integrating GIS with the stratified best–worst method (S-BWM). This model has four main dimensions and 16 sub-dimensions under topography, environment-land, location, and hydrological factors, weighted with the S-BWM. A network was created considering the different states that may arise in the importance weights of these dimensions in the future. The transition probabilities of these states were predicted and injected into the classical BWM. Then, maps were created for these dimensions and classifications for each sub-dimension according to the map characteristics. Finally, the most susceptive landslide locations were determined with GIS-based calculations. To demonstrate the model’s applicability, a case study was conducted for the Erzurum region, one of Turkey’s landslide-prone regions. In addition, besides the landslide map, an analysis and discussion about the spatial distribution of susceptibility classes was presented, contributing to the study’s robustness. In the results of landslide susceptibility analysis, landslides are higher in the range of about 1600–2500 m. Approximately 42% (35.59 sq. km) of the study area has high landslide susceptibility, while 58% (64.41 sq. km) has medium and low landslide susceptibility.
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İncele - MakaleYalnız künye2023Scopus SJRQ1An integrated hybrid MCDM approach to evaluate countries’ COVID-19 risks
Mete, Suleyman; Yucesan, Melih; Gul, Muhammet; Ozceylan, Eren
To enable planning and early reaction efforts, it is important to identify the nations most at risk from COVID-19's health and humanitarian effects, which could exceed present national response capabilities. INFORM COVID-19 Risk Index developed by European Commission is one of the initiatives to meet the aforementioned need. However, the Index has 40 conflicting and comprehensive indicators (e.g., health system capacity, hygiene, vulnerability) and different countries that lead to a need for multicriteria decision-making (MCDM) approaches. This paper offers an integrated MCDM approach with two phases to re-assess the countries' COVID-19 risks based on INFORM COVID-19 Risk Index. In the first phase, the 40 indicators are prioritized using the Entropy-based multi-choice best-worst method (MC-BWM) to provide multiple viewpoints for the preferences values. In the second phase, 29 countries from different geographical regions are ranked using the COPRAS (Complex Proportional Assessment) method. Applying these three methods together on the COVID-19 risk assessment of countries is the most significant novelty for the relevant literature. The proposed approach has undergone a thorough comparative evaluation with the released INFORM COVID-19 Risk Index, and recommendations are provided based on different scenario analyses.
AtıfScopus21WoS16OpenAlex18İncele - MakaleAçık Erişim2023Scopus SJRQ2A Fuzzy Hybrid MCDM Approach for Assessing the Emergency Department Performance during the COVID-19 Outbreak
Ortíz-Barrios, Miguel; Jaramillo-Rueda, Natalia; Gul, Muhammet; Yucesan, Melih; Jiménez-Delgado, Genett; Alfaro-Saíz, Juan-José
The use of emergency departments (EDs) has increased during the COVID-19 outbreak, thereby evidencing the key role of these units in the overall response of healthcare systems to the current pandemic scenario. Nevertheless, several disruptions have emerged in the practical scenario including low throughput, overcrowding, and extended waiting times. Therefore, there is a need to develop strategies for upgrading the response of these units against the current pandemic. Given the above, this paper presents a hybrid fuzzy multicriteria decision-making model (MCDM) to evaluate the performance of EDs and create focused improvement interventions. First, the intuitionistic fuzzy analytic hierarchy process (IF-AHP) technique is used to estimate the relative priorities of criteria and sub-criteria considering uncertainty. Then, the intuitionistic fuzzy decision making trial and evaluation laboratory (IF-DEMATEL) is employed to calculate the interdependence and feedback between criteria and sub-criteria under uncertainty, Finally, the combined compromise solution (CoCoSo) is implemented to rank the EDs and detect their weaknesses to device suitable improvement plans. The aforementioned methodology was validated in three emergency centers in Turkey. The results revealed that the most important criterion in ED performance was ER facilities (14.4%), while Procedures and protocols evidenced the highest positive D + R value (18.239) among the dispatchers and is therefore deemed as the main generator within the performance network.
AtıfScopus28OpenAlex29İncele - MakaleAçık Erişim2022Scopus SJRQ1A Bayesian BWM and VIKOR-based model for assessing hospital preparedness in the face of disasters
Saner, Halit Serdar; Yucesan, Melih; Gul, Muhammet
Hospitals are the first point of contact for people in the face of disasters that interfere with the daily functioning of life and endanger health and social life. All preparations should be made considering the worst possible conditions and the provided service should continue without interruption. In this study, a multi-criteria decision-making model was developed to evaluate disaster preparedness of hospitals. This decision model includes Bayesian best–worst method (BBWM), the VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) and technique for order preference by similarity to ideal solution (TOPSIS) methods. With the proposed decision model, six main criteria and 34 sub-criteria related to disaster preparedness of hospitals were considered. The criteria and sub-criteria evaluated in pairwise comparison manner by the experts were weighted with BBWM. These weight values and the data obtained from the six Turkish hospitals were combined to provide inputs for VIKOR and TOPSIS. In addition, a comparative study and sensitivity analysis were carried out using weight vectors obtained by different tools. BBWM application results show that the “Personnel” criterion was determined as the most important criterion with an importance value of 26%. This criterion is followed by “Equipment” with 25%, “Transportation” with 14%, “Hospital building” and “Communication” with 12%, and “Flexibility” with 11%. Hospital-2 was determined as the most prepared hospital for disasters as a result of VIKOR application. The VIKOR Q value of this hospital was obtained as 0.000. According to the results of the comparative study, Hospital-2 was determined as the most disaster-ready hospital in all six different scenarios. This hospital is followed by Hospital-4 (Q = 0.5661) and Hospital-5 (Q = 0.7464). The remaining rankings were Hospital-6, Hospital-3 and Hospital-1. The solidity of the results was checked with TOPSIS. Based on TOPSIS application results, Hospital-2 was again found the most-ready hospital. The usage of BBWM in this study enabled the expert group’s views to be combined without loss of information and to determine the criteria and sub-criteria weights with less pairwise comparisons in a probabilistic perspective. Via the “Credal ranking”, which is the contribution of BBWM to the literature, the interpretation of the hierarchy between each criterion has been performed more precisely.
AtıfScopus48WoS37OpenAlex51İncele - MakaleAçık Erişim2022Scopus SJRQ1A multicriteria approach to integrating occupational safety & health performance and industry systems productivity in the context of aging workforce: A case study
Ortiz-Barrios, Miguel; Silvera-Natera, Esnela; Petrillo, Antonella; Gul, Muhammet; Yucesan, Melih
Aging represents one of the greatest challenges that mankind will have to face in the 21st century. In this regard, there is a need to deepen the technical and organizational aspects for rebalancing the job/employee relationship. Nevertheless, there are no robust approaches assisting decision-makers in the effective management of Occupational Safety & Health Performance (OSHP) and Industry Systems Productivity (ISP) convergence with a focus on Aging Workforce (AW). There is no single and unique solution. Therefore, in a win-to-win logic that favors the characteristic of the reference scenario, the aim of this paper is to propose a multicriteria approach to integrate OSHP and ISP in the context of AW. More specifically, Intuitionistic Fuzzy Analytic Hieararchy Process (IF-AHP) was used to elicit the criteria and sub-criteria under uncertainty considering degree of belongingness and non-belongingness. Decision Making Trial and Evaluation Laboratory (DEMATEL) was applied to evaluate the presence and strength of the interrelations and feedback among OSHP and ISP criteria and sub-criteria. Finally, Combined Compromise Solution (CoCoSo) was implemented to calculate a Working Suitability Index (WSI) per aging. Based on this index, interventions on each worker are proposed to underpin redesign of the company while to provide a flexible management propelling high performance in terms of OSHP and ISP. A real case study in Colombia is presented. The results revealed that Efficiency and Quality with 0.162 were found to be the most important factors in evaluating the performance of aging electrical engineers while Psychosocial risk and Occupational Safety were concluded to be the main drivers for a joint OSHP-ISP aging workforce management. The model can be an useful tool for policy and business decision-makers from the electrical sector and can be replicated with slight changes in other industries.
AtıfScopus17WoS11OpenAlex23İncele - MakaleAçık Erişim2022Scopus SJRQ1A fuzzy hybrid decision-making framework for increasing the hospital disaster preparedness: The colombian case
Ortiz-Barrios, Miguel; Gul, Muhammet; Yucesan, Melih; Alfaro-Sarmiento, Isaac; Navarro-Jiménez, Eduardo; Jiménez-Delgado, Genett
The recent increase in the number of disasters over the world has once again brought to the agenda the question of preparedness of the hospitals, which are the most necessary units of healthcare pillar to resist these disasters. The COVID-19 epidemic disease, which has affected the whole world, has caused a large number of people to die in some countries simply because of the inadequate and incomplete planning and lack of readiness of hospitals. For this reason, determining the disaster preparedness level of hospitals is an important issue that needs to be studied and it is important in terms of disaster damage reduction. In this study, a fuzzy hybrid decision-making framework is proposed to assess hospital disaster preparedness. The framework covers three important decision-making methods. For the first phase, Intuitionistic Fuzzy Analytic Hierarchy Process (IF-AHP) is used to assign relative weights for several disaster preparedness criteria considering uncertainty. Secondly, Intuitionistic Fuzzy Decision Making Trial and Evaluation Laboratory (IF-DEMATEL) is applied to identify interrelations among these criteria and feedback. Finally, via the VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) method, priorities of hospitals regarding disaster readiness are obtained. A case study involving the participation of 10 Colombian tertiary hospitals is carried out to show the applicability of this fuzzy hybrid approach.
AtıfScopus27WoS24OpenAlex34İncele - 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 - MakaleAçık Erişim2022Scopus SJRQ1How Covid-19 pandemic and partial lockdown decisions affect air quality of a city? The case of Istanbul, Turkey
Celik, Erkan; Gul, Muhammet
The world is currently struggling with a new type of coronavirus (2019-nCoV) pandemic that first appeared in Wuhan, China, and then spread to almost all countries. As in other countries of the world, public authorities in Turkey are implementing many preventive and mitigating partial lockdown (PL) actions against the virus's effects. Some decisions and policies implemented before and after March 11, 2020, when the first virus case has been identified, have reduced people and traffic circulation, which has also turned into some improvements in air quality. At this point, this study aims to investigate how this pandemic affects the air quality of a metropolis. A case study of the city of Istanbul, the most affected city with more than half of Turkey's cases, is performed. In our analysis, we observe, compare, and discuss the impact of the COVID-19 pandemic and PL decisions on Istanbul city's air quality. We consider the particulate matter (PM10), sulfur dioxide (SO2), carbon monoxide (CO), nitrogen dioxide (NO2), nitrogen oxide (NO), nitrogen oxides (NOx), and ozone (O3) concentrations. We used data from 19 air monitoring stations (AMSs) and obtained improvements in the air quality for the pandemic period. In summary, the concentration levels in PM10, NO2, NO, and NOx result in a clear decline in pandemic times compared to the normal times in Istanbul. On the other hand, a non-homogenous trend for SO2 and CO concentrations is observed for different AMSs. A partial increase in O2 concentration is obtained in the comparison of before and during the PL period.
AtıfScopus15WoS13OpenAlex22İncele - Kitap BölümüYalnız künye2022A Multi-attribute Decision-Making to Sustainable Construction Material Selection: A Bayesian BWM-SAW Hybrid Model
Alkan, Ramazan; Yucesan, Melih; Gul, Muhammet; Rezaei, J; Brunelli, M; Mohammadi, M
The increase in urbanization and developments in the production industry has led to rapid progress in the construction sector. Many new strategies are developed in the industry to reduce costs and improve building quality. In recent years, the necessity of sustainable construction practices comes to the fore to renew the building stock damaged as a result of natural disasters and reduce the cost concerns that arise in this situation to a reasonable level. Due to limited resources and environmental concerns, researchers and practitioners have begun to develop sustainable building materials. The problem of selecting these materials when constructing a new building is vital. In particular, depending on the sector's rapid growth in Turkey, it is becoming more and more important to select the best sustainable construction material. Therefore, this paper proposes a model to evaluate the most appropriate sustainable construction material via two multi-attribute decision-making (MADM) methods called “Bayesian Best-Worst Method (BWM) and Simple Additive Weighting (SAW)”. Initially, the criteria derived from existing literature were evaluated with the aid of construction sector-based respondents and extra information about the interrelationship between the criteria were determined by credal ranking in Bayesian BWM. Then, via SAW, the most appropriate material was selected among a set of alternatives. Two cases regarding sustainable insulating material selection are considered for the demonstration of the proposed MADM model.
AtıfScopus15WoS14OpenAlex13İncele - MakaleYalnız künye2022Scopus SJRQ1A calibrated Fuzzy Best-Worst-method to reinforce supply chain resilience during the COVID 19 pandemic
López, Cristina; Ishizaka, Alessio; Gul, Muhammet; Yücesan, Melih; Valencia, Daniela
Making decisions require increasingly more sophisticated methods. The Best-Worst method was developed recently to find a good balance between the amount of information required and its consistency. The Fuzzy Best-Worst method was then proposed to integrate the uncertainty and imprecision of evaluations. In this paper, we propose the Calibrated Fuzzy Best-Worst Method, which enables us to define personalized fuzzy numbers. This new method was applied to the real case study of a global fashion supply chain suffering a dramatic drop of demand due to the COVID-19 shocks. Since its upstream was leading to a ripple effect on the rest of the supply chain stages, our study focused on evaluating the viability of its distribution channels based on weighted resilience capabilities and performance indicators. The proposed method allowed being more precise than the traditional Best-Worst method because it personalizes the uncertainty and subjectivity. The results revealed that cash flow, revenues, and inventory turnover were the most important performance indicators in the supply chain resilience. Financial strength, adaptability, and market position were shown to be the most critical resilience capabilities in preserving supply chain survivability with low-demand items and longer disruptions. Their effects explain why e-commerce was the most viable distribution channel.
AtıfScopus26WoS24OpenAlex29İncele - MakaleAçık Erişim2022Scopus SJRQ2Health, safety, and environmental failure evaluation by hybridizing fuzzy multi-attribute decision-making methods for maritime scrubber systems
Başhan, Veysi; Yucesan, Melih; Demirel, Hakan; Gul, Muhammet
Many shipping companies have started using scrubbers in their fleet to eliminate sulfur emissions from ships, per IMO (International Maritime Organization) rules. Before and during the scrubbers’ selection, the scrubbers’ operational failures have also started to appear and cause serious concerns. In this study, classified scrubber types are explained and open type, closed type, and hybrid scrubber systems are evaluated. To contribute to this gap in the literature, scrubber failures were identified, five experts with different perspectives were consulted, and the most common and critical malfunctions were evaluated with the fuzzy best–worst method (F-BWM) and fuzzy technique for order preference by similarity to an ideal solution (F-TOPSIS). F-BWM was used to determine the importance weights of the risk parameters used in evaluating failures since it provides fewer comparisons among pairwise comparison–based decision-making methods and a more consistent judgment in the evaluation. F-TOPSIS, on the other hand, was used to determine the final priority scores of the scrubber failures, taking into account the risk parameter weights obtained in the first stage. It has been preferred due to its easy to useness and based on its closeness to the ideal solution and applicability to risk and failure analysis problems. Considering all different systems in general, important issues such as collection efficiency, sulfur emission problem, abrasion, leakages, pump failures, heat exchanger failures, air fan sealing failures, sensors and failures in monitoring the whole system have been investigated. Results show that too high axial velocity for separator and flooded separator, too high solids concentration in recirculation liquid (SF2), piping leakages (SF5), poor quality or inappropriate consumables and chemicals (SF11), and feed circulation pump problems (SF6) are found to be the most important problems among thirteen failures.
AtıfScopus23OpenAlex23İncele - MakaleAçık Erişim2022Scopus SJRQ1Control measure prioritization in Fine − Kinney-based risk assessment: a Bayesian BWM-Fuzzy VIKOR combined approach in an oil station
Gul, Muhammet; Yucesan, Melih; Ak, Muhammet Fatih
The Fine − Kinney is a risk assessment method widely used in many industries due to its ease of use and quantitative risk evaluation. As in other methods, it is a method that recommends taking a series of control measures for operational safety. However, it is not always possible to implement control measures based on the determined priorities of the risks. It is considered that determining the priorities of these measures depends on many criteria such as applicability, functionality, performance, and integrity. Therefore, this study has studied the prioritization of control measures in Fine − Kinney-based risk assessment. The criteria affecting the prioritization of control measures are hierarchically structured, and the importance weights of the criteria are determined by the Bayesian Best–Worst Method (BBWM). The priorities of control measures were determined with the fuzzy VlseKriterijumska Optimizacija I Kompromisno Resenje (FVIKOR) method. The proposed model has been applied to the risk assessment process in a petrol station’s liquid fuel tank area. According to the results obtained with BBWM, the most important criterion affecting the prioritization of control measures is the applicability criterion. It has an importance weight of about 42%. It is followed by performance with 31%, functionality with 18%, and integrity with 10%, respectively. FVIKOR results show that the “Periodic control of the ventilation device” measure is the top priority for Fine − Kinney risk assessment. “The absence of any ducts or sewer pits that may cause gas accumulation in the tank area and near the dispenser; Yellow line marking of entry and exit and vehicle roads; Placing of speed limit warning signs” has been determined as a secondary priority. On conclusion, this proposed model is expected to bring a new perspective to the work of occupational health and safety analysts, since the priority suggested by Fine − Kinney risk analysis methods is not always in the same order as the one in the stage of taking action, and the source, budget, and cost/benefit ratio of the measure affect this situation in practice.
AtıfScopus51WoS42OpenAlex54İncele - MakaleYalnız künye2022Scopus SJRQ1Occupational health, safety and environmental risk assessment in textile production industry through a Bayesian BWM-VIKOR approach
Ak, M. Fatih; Yucesan, Melih; Gul, Muhammet
Occupational risk assessment (ORA) is a process that consists of evaluating, ranking, and classifying the hazards and associated risks arising in any workplace from the viewpoint of occupational health and safety. Many ORA methods have been proposed in the literature, from a single independent expert to participatory methodologies made by group decision and simple to complex ones. In this paper, a holistic ORA is presented, which uses two important multi-attribute decision methods named Bayesian Best-Worst Method (Bayesian BWM) and VIseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR). Bayesian BWM is used to determine the importance weights of six different assessment criteria, which are the probability of hazardous event (P), frequency (F), severity (S), detectability (D), cost (C) and sensitivity not to use personal protective equipment (SNP). Since the classical BWM finds solution to the weights of a number of criteria from only one expert's judgment, Bayesian BWM is preferred in this paper (1) to enable participation of a group of experts, (2) to aggregate the preferences of these multiple experts into consensus without loss of information and (3) to follow a probabilistic way for solving the ORA problem. The hazards are then ranked by VIKOR. The approach is implemented in the ORA process of a textile production plant. Results of risk analysis showed that electricity hazard and associated risks constitute the highest risk ratings. These hazards arise from the product, process, human and working environment. The associated risks are evaluated, prioritized, and detailed control measures are proposed. This study made comparisons with the classical BWM-VIKOR approach to demonstrate the proposed approach's difference and practicality. Results can also help practitioners and risk analysts in formulating the improvement measures to increase the overall safety of the working environment further.
AtıfScopus87WoS78OpenAlex87İncele - MakaleYalnız künye2022Scopus SJRQ1Performance evaluation of Turkish Universities by an integrated Bayesian BWM-TOPSIS model
Gul, Muhammet; Yucesan, Melih
This study aims to develop a university ranking model with the aid of performance measures in the “University monitoring and evaluation reports-2019” published by the Council of Higher Education Institution in Turkey. In this context, some of the performance criteria stated in these reports are filtered and 34 sub-criteria under five main criteria are weighted using the Bayesian Best-Worst Method (BBWM). Then, 189 listed public and private universities are ranked using the TOPSIS multicriteria decision-making (MCDM) method. We have adopted the MCDM concept because many evaluation criteria/sub-criteria and alternative universities are taken into account. For this study, we apply an integrated MCDM model. First, we use BBWM to accomplish the first goal and adopt the TOPSIS method for the second purpose, using the BBWM results. Our purpose in using BBWM is due to its probabilistic structure that reduces the loss of information when handling group decisions. In this context, the evaluations of 11 academic experts are combined and a solid weighting is made by obtaining the credal rankings of performance criteria. Using TOPSIS is its logic of proximity to ideal and the ability to evaluate many alternatives. In the context of the study, state-private university-based, nomenclature of territorial units for statistics-2 (NUTS-2)-based and classical geographical regions-based rankings are also discussed. The study seeks to help universities optimize their performance efficiently. The results of the study can be adapted as a reference for other educational institutions and public institutions in their efforts to evaluate, improve their performance and form various policies.
AtıfScopus79WoS61OpenAlex79İncele - MakaleAçık Erişim2021TOPSIS-Sort temelli nicel bir mesleki risk değerlendirme metodolojisi ve alüminyum ekstrüzyon endüstrisinde uygulanması
Gul, Muhammet
Alüminyum ekstrüzyon üretimini de kapsayan metal ürünleri sektörü, iş sağlığı ve güvenliği (İSG) açısından yüksek risk taşıyan sektörlerden biridir. Bu durum ve sektördeki iş kazalarının artış eğilimi göz önüne alındığında, iş güvenliğinin artırılması ihtiyacı ortaya çıkmaktadır. Bu nedenle, bu çalışma, alüminyum ekstrüzyon endüstrisindeki riskleri yönetmek için kümeleme temelli bir TOPSIS yaklaşımı (TOPSIS-Sort) ile nicel bir mesleki risk değerlendirmesi önermektedir. Risk değerlendirmesinde önemli bir süreç olan elde edilen risk değerine göre risk sınıflandırmasının gerekliliği nedeniyle sıralamaya dayalı bir metodoloji önerilmiştir. Metodolojinin uygulanabilirliği, 28 potansiyel tehlikenin üç risk parametresi (olasılık, ciddiyet ve sıklık) altında değerlendirilmesiyle gösterilmiştir. Değerlendirilen tehlikeler beş risk kümesine (Çok yüksek risk, Yüksek risk, Önemli risk, Olası risk ve Risk) bölünmüş ve risklerin azaltılmasını sağlayacak kontrol önlemleri belirlenmiştir. Çalışmanın sonuçları, Çok yüksek risk kümesine bir tehlikenin, Yüksek risk kümesine 3, Önemli risk kümesine 23 ve Olası risk kümesine bir tehlike atandığını göstermektedir.
AtıfOpenAlex16TR Dizin4
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