Sürdürülebilir Kalkınma Amaçları
Yayınlar
- MakaleAçık Erişim2022Failure-based maintenance planning using bayesian networks: a case study hydraulic turbine
Yucesan, Melih; Kahraman, Gökhan
The assessment of existing infrastructures in the energy sector is of great economic importance for the world. The extension of the power generation life of hydroelectric power plants depends on logical decisions regarding the maintenance and renewal of the equipment. For this purpose, a Bayesian network (BN) has been applied to evaluate the failures in the hydraulic turbine to calculate the failure of the turbine. Forty-six nodes have been identified that will affect the operation of the system. Preventive measures have been established for failures with the highest posterior probability. By creating four different cases, failure probabilities and the change of the main fault have been calculated. How much savings could be made in each case is determined with the maintenance. This proposed framework will be guided in determining the maintenance strategies for hydroelectric power plant operators.
AtıfOpenAlex1
İncele - MakaleAçık Erişim2022Trafik Kazalarının Makine Öğrenmesi Yöntemleriyle Analizi ve Tahmini: Kahramanmaraş İçin Örnek Bir Çalışma
Utku, Anıl; Yucesan, Melih; Bolat, Hüseyin
Dünyada her yıl 1 milyonun üzerinde ölümlü, 50 milyona yakın yaralanmalı trafik kazası meydana gelmektedir. Bu kazalarda ortalama her 2 saniyede bir trafik kazası yaşanırken her 50 saniyede bir ölümcül kaza ile sonuçlanmaktadır. Bu çalışmada, 2017 ile 2020 yılları arasında Kahramanmaraş il merkezi ve ilçelerinde gerçekleşen 28 adet öznitelikten oluşan 7929 adet trafik kazası makine öğrenme teknikleri ile analiz edilmiştir. Trafik kazalarının analizinde sınıflandırma, birliktelik kuralı ve görsel karşılaştırma yöntemleri kullanılmıştır. Sınıflandırma için NB, SVM, kNN, PART, AdaboostM1, J48 ve RF algoritmaları kullanılmıştır. Trafik kazalarının sınıflandırılmasında J48 algoritması en başarılı sonuçları elde etmiştir. Naive Bayes algoritmasının başarı düzeyi kötü olmasa da diğer algoritmalara oranla daha düşük kalmıştır. Tüm yöntemlerin ortak sonucu gelecekte yaşanabilecek ölümle ve yaralanmalı potansiyel kazaların daha çok sabah saat 04:00 ile 08:00 ve akşam saat 16:00 ile 20:00 arasında, Kahramanmaraş il merkezi ve Onikişubat ilçesinde yerleşim yeri içerisinde, Göksun ilçesindeki yerleşim yeri dışındaki eğimli ve virajlı yollarda ve Pazarcık ilçesindeki yerleşim yeri dışındaki bölünmüş yollarda yaşanma riskinin yüksek olduğu belirlenmiştir. Ayrıca meydana gelen kazalarda sürücülerin trafik ve hız kurallarına uymadığı, trafik lambası, trafik levhası, yaya yolu, emniyet şeridi ve banket gibi yol, çevre ve güvenlik ekipmanlarının yetersiz kaldığı belirlenmiştir.
AtıfOpenAlex2TR Dizin2İncele - 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.
AtıfScopus48WoS37OpenAlex51
İncele - 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 - 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 - 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 Erişim2021Scopus SJRQ3A BAYESIAN NETWORK-BASED APPROACH FOR FAILURE ANALYSIS IN WEAPON INDUSTRY
Yucesan, Melih; Gul, Muhammet; Guneri, Ali Fuat
Gun and rifle manufacturing contain various failures in the process of CNC machining, material supply, research & development, infrastructure and, operator. Due to these failures, the enterprise is exposed to great economic losses and a decrease in competition in the global market. In addition, failures in production cause events that seriously threaten human health. Failure analysis can increase safety by determining the cause of potential errors and taking measures for identified errors in the life cycle of the products. Therefore, this study employs a Bayesian Network (BN)-based modeling approach for capturing dependency among the basic events and obtaining top event probability. Firstly, a fault tree analysis (FTA) diagram is constructed, since its target is to pinpoint how basic event failures result in a top event (system) failure by an AND/OR logical gate. While, AND logical gate should take place in both cases, it is sufficient to realize one of the states in the OR logical gate. Then, a BN-based on fault tree transformation is applied. A case study in a leading weapon factory that produces various types of guns and rifles in the Black Sea region of Turkey is performed. For the application viewpoint, appropriate control measures can be taken into account to decrease the number of failed products based on the performed failure analysis.
AtıfScopus6WoS5OpenAlex7İncele - MakaleAçık Erişim2021Scopus SJRQ2Hospital Preparedness Assessment against COVID-19 Pandemic: A Case Study in Turkish Tertiary Healthcare Services
Gul, Muhammet; Yucesan, Melih
Hospitals play a critical role in providing essential health services to people in the healthcare system. Healthcare systems around the world have faced some issues in responding to patients with various disease severity levels. Nowadays, the world as a whole is combating a pandemic called COVID-19. This pandemic causes an increase in the disease spread with fluctuated patient demand that may affect the hospitals' capacity and overall functioning and risks rising based on hospital site, medical staff, patient, and healthcare process. To deal with the challenges of the COVID-19 pandemic, hospitals must have completed their preparations before these events occur. Therefore, this study proposes an integrated approach based on the decision-making concept with interval-valued spherical fuzzy sets (IVSFSs) to the hospital preparedness assessment problem. A technique for order preference by similarity to ideal solution (TOPSIS) extended with IVSFSs is used to rank hospitals from Turkish tertiary healthcare services. A checklist reported by the World Health Organization (WHO) is adapted to conform to Turkey's COVID-19 pandemic management. Ninety-nine subcomponents of the adapted checklist under ten components are weighted by interval-valued spherical weighted arithmetic mean (IVSWAM) operator. The hospitals in the problem are then ranked concerning these weighted subcomponents. With the proposed approach, a COVID-19 pandemic preparedness index is determined for the observed hospitals. In addition, a separate index based on each main component (component-based ranking) is determined. These indexes are vital indicators in determining in which aspects hospitals are ready and in what aspects hospitals are not prepared for pandemics. The proposed approach can be adaptable and applied by national policymakers in assessing all hospitals of the country against the COVID-19 pandemic.
AtıfScopus45WoS33OpenAlex44İncele - MakaleYalnız künye2021Scopus SJRQ2Failure modes and effects analysis based on neutrosophic analytic hierarchy process: method and application
Yucesan, Melih; Gul, Muhammet
Failure modes and effects analysis (FMEA) is a commonly used method in risk evaluation. In this paper, a novel FMEA model based on neutrosophic analytic hierarchy process (NAHP) is proposed to overcome shortcomings of the risk prioritization of classical FMEA. Neutrosophic sets approach real-world decision-making problems from a three-aspect structure (i.e., truthiness, indeterminacy and falsity). Therefore, initially, AHP is merged with neutrosophic sets to assign importance weights to risk parameters in FMEA. The encountered failure modes are then prioritized with respect to the previously weighted risk parameters. Each element in AHP comparison matrices is considered as triangular neutrosophic numbers, and score functions are used to transform NAHP elements to deterministic values. The flexibility of determining the weight to each parameter of FMEA (severity, occurrence and detection) and evaluation of each failure mode against these parameters are more well-suited to the real decision-making condition. Finally, a case study in the textile industry is provided to show the applicability of the novel model. Sensitivity and comparative analysis are also performed to validate the results.
AtıfScopus42WoS27OpenAlex33İncele - MakaleAçık Erişim2021Fermatean fuzzy TOPSIS-based approach for occupational risk assessment in manufacturing
Gul, Muhammet; Lo, Huai-Wei; Yucesan, Melih
The importance of risk assessment in the context of occupational health and safety by manufacturing operators strengthens their hands in solving the problems they may encounter in business processes related to health and safety. One of the most important phases of conducting an exhaustive occupational risk assessment is to analyze potential hazards and associated risks quantitatively. Since manufacturing is one of the industries that require workers to be highly exposed to work, creating a safer environment to reduce occupational injuries is an important task. This study proposes a novel fuzzy risk assessment approach developed by integrating Fermatean fuzzy sets (FFSs) and technique for order preference by similarity to ideal solution (TOPSIS) method for ranking potential hazards in manufacturing. FFSs are a new version of fuzzy set theory that covers the intuitionistic fuzzy sets and Pythagorean fuzzy sets. This version of the fuzzy set is crucial in the decision-making process to handle uncertain information more easily and reflect uncertainty better. A linguistic scale under Fermatean fuzzy documentation has also been developed for experts/decision makers to disclose their judgments easily. Occupational risk analysts can benefit from this approach since FFSs are used for the first time in occupational risk assessment, and the approach is presented in integration with TOPSIS. The proposed approach is applied in the aluminum plate-manufacturing process risk assessment. In the conclusion of the implementation, risks arising in the production are prioritized. In addition, this study made comparisons with other fuzzy methods to demonstrate the proposed approach’s difference and practicality. This study’s results can support practitioners and risk analysts in formulating the improvement measures to increase the safety of the work environment further.
AtıfScopus105WoS86OpenAlex108İncele - Kitap BölümüYalnız künye2021A Risk Prioritization Method Based on Interval-Valued Pythagorean Fuzzy TOPSIS and Its Application for Prioritization of the Risks Emerged at Hospitals During the Covid-19 Pandemic
Gul, Muhammet; Yucesan, Melih
AtıfScopus2İncele - MakaleAçık Erişim2021Scopus SJRQ1A multiple criteria decision-making approach for increasing the preparedness level of sales departments against COVID-19 and future pandemics: A real-world case
Ortiz-Barrios, Miguel; Borrego-Areyanes, Arlen Alaine; Gómez-Villar, Iván Darío; De Felice, Fabio; Petrillo, Antonella; Gul, Muhammet; Yucesan, Melih
The impact of the pandemic and the lockdown has been more devastating than expected on the world economy. It is essential to formulate strategies in real-time. In this research, a multicriteria decision-making model for increasing the preparedness level of sales departments when facing COVID-19 waves and future pandemics is proposed. The model is comprised of 8 criteria, 29 sub-criteria, and 7 alternatives. The study is based on the integration of the AHP and TOPSIS techniques. AHP is used for calculating the criteria and sub-criteria weights. While, TOPSIS is used for calculating the preparedness level, ranking the companies, and identifying the weaknesses that should be addressed for increasing their effectiveness in the current market scenario. The model is developed with the aid of an experts’ group from the electrical appliance sector and studies from the reported literature. This application is completely novel in the literature and has been applied in the wild with remarkable companies in Colombia. A case study in the electrical appliance sector is presented as a pilot study but it should be noted that the methodology is flexible and scalable in any scenario.
AtıfScopus18OpenAlex21İncele - MakaleYalnız künye2021Scopus SJRQ1Failure prioritization and control using the neutrosophic best and worst method
Yucesan, Melih; Gul, Muhammet
Failure prioritization process is described by identifying potential failures and its effects, quantifying their priorities and determining appropriate ways to mitigate or control. In the literature, many approaches are suggested to prioritize failures and associated effects quantitatively. Multicriteria decision-making (MCDM) approaches are forefront that they can express the failures verbally based on decision-makers’ judgments. They explain different types of uncertainties, which are generally modeled by fuzzy sets. However, fuzzy sets focus only on one membership value in decision-making. At this point, neutrosophic sets are more suitable than classical fuzzy sets by proposing three membership values named truth-membership, indeterminacy-membership and falsity-membership. Therefore, in this study, a novel approach based on the neutrosophic best and worst method (NBWM) is proposed and a case study is also performed in the implant production. The best and worst method (BWM) is merged with neutrosophic sets since it has fewer pairwise comparisons while determining the importance weights of failures. To show the applicability of the approach, a case study in an implant manufacturing plant that produces many products, including implants in different shapes and sizes in Turkey is carried out. Besides the case study, a comparative study is performed to test the validity of the proposed NBWM approach. This approach can make the decision-making process more dynamic in real-world problems with indeterminate and inconsistent information, considering the benefits of BWM and neutrosophic sets either individually or in integration. The present study contributes to the knowledge both methodologically and in an application by proposing NBWM for failure assessment problems for the first time in the literature and creating an adaptive model for manufacturing and other industries.
AtıfScopus33WoS32OpenAlex41İncele - MakaleAçık Erişim2021A holistic FMEA approach by fuzzy-based Bayesian network and best–worst method
Yucesan, Melih; Gul, Muhammet; Celik, Erkan
Failure mode and effect analysis (FMEA) is a risk analysis tool widely used in the manufacturing industry. However, traditional FMEA has limitations such as the inability to deal with uncertain failure data including subjective evaluations of experts, the absence of weight values of risk parameters, and not considering the conditionality between failure events. In this paper, we propose a holistic FMEA to overcome these limitations. The proposed approach uses the fuzzy best–worst (FBWM) method in weighting three risk parameters of FMEA, which are severity (S), occurrence (O), and detection (D), and to find the preference values of the failure modes according to parameters S and D. On the other side, it uses the fuzzy Bayesian network (FBN) to determine occurrence probabilities of the failure modes. Experts use a procedure using linguistic variables whose corresponding values are expressed in trapezoidal fuzzy numbers, and determine the preference values of the failure modes according to parameter O in the constructed BN. Thus, the FBN including expert judgments and fuzzy set theory addresses uncertainty in failure data and includes a robust probabilistic risk analysis logic to capture the dependence between failure events. As a demonstration of the approach, a case study was conducted in an industrial kitchen equipment manufacturing facility. The results of the approach have also been compared with existed methods demonstrating its robustness.
AtıfScopus105WoS93İncele - MakaleYalnız künye2021Scopus SJRQ1Green supplier selection for textile industry: a case study using BWM-TODIM integration under interval type-2 fuzzy sets
Celik, Erkan; Yucesan, Melih; Gul, Muhammet
Although environmental awareness has reached a high level, enterprises—regardless of their working domains—follow the concept of greenness for their practices. This awareness among the stakeholders and supply chain experts has a positive impact on the purchasing departments of enterprises in various sectors to consider greenness in their procurement processes. The critical decision that must be made in green supply chain management (GSCM) is supplier selection. In the textile industry, a highly competitive market in recent years, suppliers for this industry have crucial roles in business activities considering environmental issues. Therefore, green supplier selection (GSS) in the textile industry is considered a must-be process for the stakeholders. In this study, a GSS problem is tackled as a multi-criteria decision process. Best worst method (BWM) and TODIM (an acronym in Portuguese of interactive and multi-criteria decision-making) methods are merged under an improved fuzzy concept of interval type-2 fuzzy sets (IT2FSs). In determining green suppliers’ evaluation criteria, BWM with interval type-2 fuzzy numbers (IT2F-BWM) is used. In selecting green suppliers, an interval type-2 fuzzy TODIM (IT2F-TODIM) is applied. Considering the characteristics of IT2FSs, BWM, and TODIM methods either individually and in integrated style, the proposed approach can handle uncertainty in the decision-making of GSS. To demonstrate the applicability of the approach, a case study in the Turkish textile industry is performed. Three green supplier alternatives (S1, S2, and S3) are assessed under forty-two sub-criteria. The study shows the most significant sub-criteria are recognized as dye and print quality, product design and pattern suitability, profit on the product, variation in price, and purchase cost. S2 green supplier has been selected as the most appropriate one. A sensitivity analysis is also fulfilled to check variation in the ranking of green suppliers.
AtıfScopus88WoS72OpenAlex100İncele