Sürdürülebilir Kalkınma Amaçları
Yayınlar
- Derleme MakaleAçık Erişim2021Scopus SJRQ2Hospital location selection: A systematic literature review on methodologies and applications
Gul, Muhammet; Guneri, Ali Fuat
The increased focus of people on the quality of health care in recent years has led hospital owners to develop strategies and policies to improve medical services through the establishment of new hospitals. For hospitals to be competitive, the hospital's location and proximity to potential patients are considered crucial factors in establishing new hospitals. In this context, evaluating and selecting the most suitable hospital location to establish a new hospital from the multicriteria decision-making (MCDM) perspective is a priority for the entrepreneurs or government to gain a competitive advantage. Therefore, this study aims to present a systematic literature review of the hospital location selection problem considering the applied methods and application areas. The preferred reporting items for systematic review and meta-analysis statement (PRISMA) are used as a reference framework. Initially, known electronic databases (Web of science, IEEEXplore, Scopus, Science direct, and Google Scholar) were searched up to the early 2021. A number of 47 articles are selected and analyzed under this systematic framework based on inclusion-exclusion points. State-of-the-art developments in adopting MCDM methods and their fuzzy extensions are summarized. All the articles have been examined in a systematic taxonomy to find answers to six research questions (trend, country of origin, outlet journal, MCDM methods used, MCDM environment and criteria type, and decision criteria used). Results show that (1) AHP and GISbased MCDM models are the most contributing approaches to the solution of this problem, (2) location selection criteria are mostly cost, demand, environment, population, government, competition in the market, and distance to some important places, (3) the fuzzy structure is also preferred in addition to the MCDM structure depending on the crisp data type, and (4) the location selection criteria are mostly considered subjective. We pay attention to promising directions that can dominate future research in this field from a methodological or applicability perspective. This study shows the current views and opportunities for researchers and practitioners and acts as a guide to encourage more creative studies in this field.
AtıfScopus58WoS43OpenAlex71
İncele - Kitap BölümüYalnız künye2021Fine–kinney-based occupational risk assessment using interval-valued pythagorean fuzzy vikor
Gul, Muhammet; Mete, Suleyman; Serin, Faruk; Celik, Erkan
This chapter aims at the adaptation of the Fine–Kinney occupational risk assessment concept into the VIKOR multi-attribute decision-making method with an interval-valued Pythagorean fuzzy set. The classical fuzzy set theory has been improved by proposing a number of extended versions. One of them is the Pythagorean fuzzy set. It has been firstly developed by Yager (IEEE Transactions on Fuzzy Systems 22:958–965, [1]). In this chapter, we use this type of fuzzy set with VIKOR since it reflects uncertainty in occupational risk assessment and decision-making better than other fuzzy extensions. To demonstrate the proposed approach applicability, a case study regarding the activities of the surface treatment area in a chrome plating unit of a gun factory is performed. Some additional analysis to test the solidity and validity of the approach is executed. Finally, the Python codes in the implementation of the proposed approach are given for scholars and practitioners for usage in further studies.
AtıfScopus14OpenAlex5İncele - EditoryalYalnız künye2021Preface
Gul, Muhammet; Mete, Suleyman; Serin, Faruk; Celik, Erkan
AtıfScopus2İncele - Kitap BölümüYalnız künye2021Fine–kinney-based occupational risk assessment using interval type-2 fuzzy vikor
Gul, Muhammet; Mete, Suleyman; Serin, Faruk; Celik, Erkan
In this chapter, we improved Fine–Kinney occupational risk assessment approach with interval type-2 fuzzy VIKOR (IT2FVIKOR). VIKOR is a compromise multi-attribute decision-making method proposed by Opricovic (1998). Similar to other compromised solution-based approaches, it considers the solution which is closest to the ideal. In this chapter, we adapted the interval type-2 fuzzy sets (IT2FSs) into VIKOR as it reflects the uncertainty well in decision-making. IT2FVIKOR algorithm under the Fine–Kinney concept provides a useful and solid approach to the occupational health and safety risk assessment. In addition to proposing this new approach, a case study is performed in a gun and rifle barrel external surface oxidation and coloring unit of a gun factory. A validation and a sensitivity analysis is also attached to this study. Finally, the proposed approach is implemented in Python.
AtıfScopus4OpenAlex5İncele - MakaleAçık Erişim2021Scopus SJRQ2Metaheuristic Approaches Integrated with ANN in Forecasting Daily Emergency Department Visits
Pekel, Engin; Gul, Muhammet; Celik, Erkan; Yousefi, Samuel
The overall service quality level of Emergency Departments (EDs) can be improved by accurate forecasting of patient visits. Accordingly, this study aims to evaluate the use of three metaheuristic approaches integrated with Artificial Neural Network (ANN) in forecasting daily ED visits. To do this, five performance measures are used for evaluating the accuracy of the proposed approaches, including Bayesian ANN, Genetic Algorithm-based ANN (GA-ANN), and Particle Swarm Optimization algorithm-based ANN (PSO-ANN). The outputs of this study show that the PSO-ANN model provides the most dominant performance in both the training and testing process. The lowest error is obtained with a mean absolute percentage error (MAPE) of 6.3%, Mean Absolute Error (MAE) of 42.797, Mean Squared Error (MSE) of 2499.340, Root Mean Square Error (RMSE) of 49.933, and R-squared (R2) of 0.824 on the training dataset. The lowest error with an MAPE of 6.0%, MAE of 40.888, MSE of 2839.998, RMSE of 53.292, and R2 of 0.791 is also obtained on the testing process.
AtıfScopus7WoS5OpenAlex7İncele - 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 - Kitap BölümüYalnız künye2021Fine–kinney-based occupational risk assessment using fuzzy best and worst method (f-bwm) and fuzzy mairca
Gul, Muhammet; Mete, Suleyman; Serin, Faruk; Celik, Erkan
The best-worst method (BWM) proposed by Rezaei (Omega 53:49–57, [1]) is an MCDM method used to achieve the weights of the criteria by making fewer pairwise comparisons and using more consistent decision matrices. In this chapter, instead of crisp numbers, triangular fuzzy numbers that reflect the uncertainty well in real-world problems are used in integration with the BWM method (Guo and Zhao in Knowl Based Syst 121:23–31, [2]) in determining factor weights. Using the fuzzy best and worst method (F-BWM), a model based on Fine–Kinney occupational health and safety risk assessment method was developed for the first time in the literature. Three parameters of Fine–Kinney method are weighted by the mathematical models of F-BWM. Then, the risks are prioritized by fuzzy multi-attribute ideal real comparative analysis (F-MAIRCA). A case study was conducted to demonstrate the feasibility of the approach, and besides this case study, a comparative study was also conducted to test the validity of the proposed approach. This approach led to the conclusion that Fine–Kinney’s method, BWM, MAIRCA, and triangular fuzzy sets make the risk decision-making process more dynamic, taking into account the benefits of these methods individually or in integration.
AtıfScopus11OpenAlex12İncele - Kitap BölümüYalnız künye2021Fine–kinney-based occupational risk assessment using hexagonal fuzzy multimoora
Gul, Muhammet; Mete, Suleyman; Serin, Faruk; Celik, Erkan
Hexagonal fuzzy numbers (HFNs) can be used as a proficient logic to simplify understanding of ambiguity information. HFNs present the usual information in a comprehensive way and also the ambiguity section can be exemplified in a reasonable way. In this chapter, we proposed an improved Fine–Kinney occupational risk assessment approach using a well-known MCDM method Multi-Objective Optimization by Ratio Analysis (MULTIMOORA) using hexagonal fuzzy numbers. Since the mere MULTIMOORA has failed to handle uncertainty and vague information which usually exist in real world problems, we follow integration of HFNs and MULTIMOORA (HFMULTIMOORA). To show the applicability of the novel approach, a case study of risk assessment of a raw mill in cement plant was provided. Comparative analysis with using two aggregation tools as reciprocal rank method and dominance theory are carried out. Finally, the Python implementation of the proposed approach is implemented to be effective for those concerned in the future.
AtıfScopus7OpenAlex5İncele - MakaleYalnız künye2021Scopus SJRQ1Sustainable supplier evaluation and transportation planning in multi-level supply chain networks using multi-attribute- and multi-objective decision making
Lo, Huai-Wei; Liaw, Ching-Fang; Gul, Muhammet; Lin, Kuan-Yu
Supplier selection and transportation planning are essential tasks in managing supply chain networks (SCNs). The choice of a supplier has a significant influence on the transportation planning of SCNs, as the transportation routes will change. A limited number of studies in the literature have addressed the supplier selection and transportation planning issues simultaneously. This study proposes a two-stage multi-criteria decision-making (MCDM) approach for sustainable supplier evaluation and transportation planning in multi-level SCNs. Initially, a supplier evaluation framework is proposed using the modified indifference threshold-based attribute ratio analysis (ITARA) and the performance calculation technique of the integrated multiple multi-attribute decision-making (PCIM-MADM) to determine the supplier's performance index. Subsequently, a multi-level SCN model is established, and the sustainable supplier selection and transportation planning problem is solved by the fuzzy multi-objective linear programming (FMOLP) method. A set of real-world data provided by a smart audio manufacturing company has been used to demonstrate the proposed approach. Decision-makers understand the importance of criteria through the weights constructed by the modified ITARA. Moreover, the results of the PCIM-MADM can effectively determine the supplier's ranking and provide improving strategies for underperforming suppliers. The augmented max–min technique of the FMOLP can produce a single optimal solution of the transportation allocation. The results show that our approach can effectively evaluate sustainable supplier performance and optimize transportation planning in SCNs.
AtıfScopus67WoS56OpenAlex64İncele - 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 - Kitap BölümüYalnız künye2021Fine–kinney-based occupational risk assessment using intuitionistic fuzzy todim
Gul, Muhammet; Mete, Suleyman; Serin, Faruk; Celik, Erkan
This chapter applies a novel occupational risk assessment approach which merges TODIM with the Fine–Kinney method under the intuitionistic fuzzy set concept. Risk parameters of Fine–Kinney and OHS experts are weighted by an intuitionistic fuzzy weighted averaging (IFWA) aggregation operator. Hence, hazards are quantitatively evaluated and prioritized using the proposed approach. To illustrate the novel risk assessment approach, processes of the gun and rifle assembly line of a factory are handled. A comprehensive risk assessment is carried out to improve operational safety and reliability in the industry. We adapt intuitionistic fuzzy sets in the existing study since they reflect uncertainty with the aid of their membership and nonmembership functions in decision-making better than classical fuzzy extensions. An additional sensitivity analysis by changing the attenuation parameter of TODIM is performed to test the validity of the approach. Finally, the Python codes in the implementation of the proposed approach are given for scholars and practitioners for usage in further studies.
AtıfScopus5OpenAlex9İncele - Kitap BölümüYalnız künye2021Fine–kinney-based occupational risk assessment using single-valued neutrosophic topsis
Gul, Muhammet; Mete, Suleyman; Serin, Faruk; Celik, Erkan
Neutrosophic sets are initially recommended by Smarandache (First international conference on neutrosophy, neutrosophic logic, set, probability, and statistics. University of New Mexico, Gallup, NM, pp 338–353, 2002 [1]). These sets reflect uncertainty and vagueness in real-world problems better than classical fuzzy set theory. It takes into consideration three decision-making situations called indeterminacy, truthiness, and falsity. In Zadeh traditional fuzzy set theory, there is just membership function fuzzy set degree. But, in neutrosophic environment, it considers three membership functions. Unlike intuitionistic fuzzy sets, an indeterminacy degree is considered. In this chapter, we applied a special form of neutrosophic set as single-valued neutrosophic set (SVNs) with the technique for order preference by similarity to ideal solution (TOPSIS) under the concept of Fine–Kinney occupational risk assessment. Since the mere TOPSIS has failed to handle imprecise and vague information which usually exist in real-world problems, we follow the integration of SVNs and TOPSIS. To demonstrate the applicability of the novel approach, a case study of risk assessment of a wind turbine in times of operation was provided. Comparative analysis with some similar approaches and sensitivity analysis by changing the weights of Fine–Kinney parameters are carried out. Finally, the Python implementation of the proposed approach is executed to be useful for those concerned in the future.
AtıfScopus12OpenAlex9İncele - 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 - MakaleYalnız künye2021Scopus SJRQ2A modified failure modes and effects analysis using interval-valued spherical fuzzy extension of TOPSIS method: case study in a marble manufacturing facility
Gul, Muhammet; Ak, M. Fatih
Failure modes and effects analysis (FMEA) is a commonly used step-by-step approach to assess potential failures existing in a product or process design. In this paper, a modified FMEA model based on an interval-valued spherical fuzzy extension of technique for order preference by similarity to ideal solution (IVSF-TOPSIS) is proposed to cope with drawbacks of the traditional risk priority number (RPN) computation. Spherical fuzzy sets are the integration of Pythagorean fuzzy sets and neutrosophic sets. They provide more freedom to experts in decision making by including the degree of membership, non-membership, and hesitation of fuzzy sets. Therefore, initially, TOPSIS is merged with a special branch of spherical sets “interval-valued spherical fuzzy sets” to determine priorities of emerged failures. As a novelty to traditional RPN of FMEA, three parameters called cost, prevention, and effectiveness in addition to the existed parameters of severity, occurrence and detection are attached to the proposed approach. Weights of these parameters are determined via an interval-valued spherical weighted arithmetic mean operator (IVSWAM). As a demonstration, a case study in a marble manufacturing facility is provided to show the applicability of the novel model. Results show that the most crucial failure modes concern with the maintenance and repairing works of the factory and the lack of technical periodic checks of lifting vehicles regarding “block area: crane” failures. Some comparative and validation studies are also performed to test the solidity of the approach.
AtıfScopus108WoS93OpenAlex103İncele - MakaleYalnız künye2021Scopus SJRQ1Hazard identification, risk assessment and control for dam construction safety using an integrated BWM and MARCOS approach under interval type-2 fuzzy sets environment
Celik, Erkan; Gul, Muhammet
Undoubtedly, dams are one of the projects developed by people to make optimal water use and generate hydroelectric energy power. In addition to the importance of detailed project planning, faultless production, and optimal working conditions in dam constructions, it is equally important to identify and analyze the risks from the occupational health and safety (OHS) perspective that may arise during construction and operation. In this context, hazard identification, risk analysis, and control, which are the main issues of dam safety, have gained importance. In this study, a novel approach is developed for dam construction safety. Two newly proposed multi-criteria decision-making (MCDM) methods of “Best-Worst Method-BWM” and “measurement of alternatives and ranking to Compromise solution-MARCOS”, are merged under the context of interval type-2 fuzzy sets (IT2FSs). Severity and probability, two essential parameters of the risk score, have been weighted using BWM. Subsequently, the priority orders of hazards have been determined by the MARCOS. In implementing the approach to the blasting process in dam construction, several control measures are suggested for stakeholders. Some comparative works and sensitivity analyses are performed to test the approach's validity and solidity from the methodological viewpoint.
AtıfScopus140WoS113İncele - 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