Abstract: The growing attention of the recycling of WEEE led to the making of critical studies on how to manage this process such as to determine one of the most appropriate outsourcing firms. In the recent years, the determination of the most suitable firm to be managed for the recycling of WEEE for private and public institutions is a critical decision that has high level importance in terms of environmental, economic, social and even technological. For this aim, we try to determine the best alternative outsourcing firm for management of WEEE process for Municipality of Eyüp which is a district located…in European side of Istanbul by using suggested MCDM methodology based on HFS. In this paper, a multi criteria decision making (MCDM) methodology based on hesitant fuzzy enveloped TOPSIS that gives experts extra flexibility in using linguistic terms to give their assessments has been proposed to determine the best outsourcing firm for Waste of Electrical and Electronic Equipment (WEEE). We have developed a mechanism based on hesitant fuzzy sets (HFS) for enabling decision makers to be easier in evaluation process of WEEE management.
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Keywords: Hesitant fuzzy sets (HFSs), outsourcing, waste of electrical and electronic equipment (WEEE)
Abstract: Process capability indices (PCIs) are mainly used in industry in order to measure the capability of a process to produce products meeting specifications. Traditionally, the specifications are defined as crisp numbers. Sometimes, specification limits can be expressed as linguistic terms. Traditional PCIs can not be applied for this situation. In this paper, PCIs are analyzed under fuzzy environment. The fuzzy process capability analyses are developed when the specifications limits are represented by triangular and trapezoidal fuzzy numbers. The developed approaches are applied to teaching processes and the fuzzy PCIs are compared based on two different fuzzy ranking methods.
Keywords: Process capability indices, fuzzy specification limits, ranking methods
Abstract: Although traditional acceptance sampling plans (ASPs) need certain mass quality characteristics, it is not easy to define them as crisp value in some real case problems. The fuzzy set theory (FST) is one of the popular techniques to model uncertainties of the process and therefore fuzzy ASPs have been offered in the literature. Fuzzy set extensions have been proposed recently for better modeling of the uncertainties having different sources and characteristics. One of these extensions named neutrosophic sets (NSs) can be used to increase the sensitiveness and flexibility of ASPs. The ASPs based on NSs can give ability to classify…the items as defective, non-defective and indeterminate. Since the operator can become indecisive for slightly defective items, these plans can provide a good representation of human evaluations under uncertainty. In this study, single and double ASPs are designed based on NSs by using binomial and poisson distributions that are also re-analyzed based on NSs. For this aim, some characteristics functions of ASPs such as probability of accepting a lot (P a ), average outgoing quality (AOQ ), average total inspection (ATI ) and average sample number (ASN ) have also been analyzed based on NSs. Numerical examples are presented to analyze the proposed plans.
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Abstract: As a combining concept of Pythagorean fuzzy sets (PFSs) and linguistic fuzzy sets (FSs), linguistic PFSs (LPFSs) has been suggested in the literature to deal with the uncertain and inconsistent information in multi-criteria decision making (MCDM) process. The LPFSs based procedure has been built by assuming that the experts make assessments suitable with PFS. It does not provide a mechanism to ensure the suitability of the assessments with theory of PFSs but there are other type of non-standard fuzzy sets such as Neutrosophic sets (NSs) used for modeling with inconsistent information. The main motivation of this study is to offer…an assessment collection method to guarantee that the input statements will be Pythagorean fuzzy linguistic expressions. As a second motivation, it is aimed to extend the PFS method for the fuzzy modeling of the other type of decision-making problems apart from MCDM which do not require aggregation and comparison operations and continue with precise fuzzy modeling (PFM). The third motivation of this study is to offer enhancements on the LPFSs method to increase the sensitivity of the modeling while protecting the interpretability. For these purposes, a new methodology based on LPFSs has been proposed and applied on a decision-making problem in a comparative way.
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Keywords: Fuzzy modifiers, fuzzy sets, linguistic terms, linguistic 2-tuple statements, pythagorean fuzzy sets
Abstract: Defectiveness of items is generally considered as a certain value in acceptance sampling plans (ASPs). It is clear that, it may not be certainly known in some real-case problems. Uncertainties of the inspection process such as measurement errors, inspectors’ hesitancies or vagueness of the process etc. should be taken into account to obtain more reliable results. The fuzzy set theory (FST) is one of the best methods to overcome these problems. There are some studies in the literature formulating the ASPs with the help of FST. Deciding the right membership functions of the fuzzy sets (FSs) has a vital importance…on the quality of the uncertainty modeling. Additionally, the fuzzy set extensions have been offered to model more complicated uncertainties to achieve better modeling. As one of these extensions, type-2 fuzzy sets (T2FSs) gives an ability to model uncertainty in situations where it is not possible to determine exact membership function parameters. In this study, single and double ASPs based on interval T2FSs (IT2FSs) have been designed for binomial and Poisson distributions. Thus, it becomes possible to make more flexible, sensitive and descriptive sensitivity analyzes. The main characteristic functions of ASPs have been derived and the suggested formulations have been illustrated on a comparative application from manufacturing process. Results allowing for more comprehensive analysis as against to the traditional and T1FSs based plans have been obtained.
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Abstract: Process capability analysis (PCA) is an important stage to check variability of process by using process capability indices (PCIs) that are very effective statistics to summarize process’ performance. Traditional PCIs can produce some incorrect results and declare misinterpretation about process’ quality if the process includes uncertainties. Additionally, definitions of process’ parameters with exact values is not possible when there are uncertainty caused by measurement errors, sensitivities of measuring instruments or quality engineers’ hesitancies. Although the fuzzy set theory (FST) has been successfully used in PCA, it is the first time to use of Pythagorean fuzzy sets (PFSs) to model uncertainties…of process more than traditional fuzzy sets in PCA. Since the PFSs has two-dimensional configurations by defining membership and non-membership values, they also have a huge ability to model uncertainty that arises from the human’s thinking and hesitancies, and has brought flexibility, sensitivity and reality for PCA. In this paper, specification limits (SLs), mean (μp ), standard deviation (σ ) and target value (T ) main parameters of PCIs have been analyzed by using PFSs and Pythagorean fuzzy process capability indices (PFPCIs) for two well-known PCIs such as ( C ˜ pm ) and ( C ˜ pmk ) have been derived. The Pythagorean ( C ˜ pm ) and ( C ˜ pmk ) indices have also been applied and tested on some numerical examples based on real case applications from manufacturing industry. The obtained results show that PFPCIs provide wider knowledge about capability of process and to obtain more realistic results. As a result of considering all possibilities about the process, it has been concluded that the process is incapable. In light of this information, the results obtained using different fuzzy set extensions for (C pm ) and (C pmk ) indices can be compared.
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Keywords: Process capability analysis, process capability indices, flexible parameters Pythagorean fuzzy sets
Abstract: Nowadays, more companies are trying to implement blockchain technology (BT) that enables to increase the quality of the products/services to their supply chains in order to improve their performance. BT can be applied to different sectors according to their specific needs. Evaluation of BT with respect to sectors needs considering several factors and it can be considered as a multi criteria decision making (MCDM) problem. In this paper, the appropriateness of BT in Supply Chain Management (SCM) according to different sectors has been evaluated by using a MCDM methodology based on hesitant fuzzy sets (HFSs). The suggested MCDM methodology consists…of Delphi method, hesitant fuzzy Analytic Hierarchy Process (HF-AHP) and Hesitant Fuzzy Technique for Order Preference by Similarity to Ideal Solution (HF-TOPSIS) methods. In the first stage, the criteria and sub-criteria utilized for performance evaluation of BT in supply chain management have been determined by using Delphi method. The weights of main and sub-criteria have been obtained through HF-AHP method and finally, the alternative sectors have been ranked according to results of HF-TOPSIS method. For this aim, a hierarchical MCDM problem that consists of 5 main and 17 sub-criteria has been created and the alternative sectors have been evaluated. As a result, medicine/drug and jewelry sectors have been respectively determined as the most and the least suitable alternatives in order to implement BT by means of the proposed HFSs based methodology. Finally, a sensitivity analysis has been conducted to show the importance of the main criteria weights on ranking of alternatives.
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