Selection of materials using compromise ranking and outranking methods

Selection of proper materials for different components is one of the most challenging tasks in the design and development of products for diverse engineering applications. Materials play a crucial and important role during the entire design and manufacturing process. Wrong selection of material often leads to huge cost involvement and ultimately drives towards premature component or product failure. So the designers need to identify and select proper materials with specific functionalities in order to obtain the desired output with minimum cost involvement and specific applicability. This paper attempts to solve the materials selection problem using two most potential multi-criteria decision-making (MCDM) approaches and compares their relative performance for a given material selection application. The first MCDM approach is ‘Vlse Kriterijumska Optimizacija Kompromisno Resenje’ (VIKOR), a compromise ranking method and the other one is ‘ELimination and Et Choice Translating REality’ (ELECTRE), an outranking method. These two methods are used to rank the alternative materials, for which several requirements are considered simultaneously. Two examples are cited in order to demonstrate and validate the effectiveness and flexibility of these two MCDM approaches. In each example, a list of all the possible choices from the best to the worst suitable materials is obtained taking into account different material selection criteria. The rankings of the selected materials almost corroborate with those as obtained by the past researchers.     

A novel hybrid multiple criteria decision making model for material selection with target-based criteria

In engineering design, the decision to select an optimal material for a particular product is a problem requiring multi-criteria decision analysis that involves both qualitative and quantitative factors. The evaluation of alternative materials may be based on imprecise information or uncertain data. Furthermore, there can be significant dependence and feedbacks between the different criteria for material selection. However, most existing decision approaches cannot capture these complex interrelationships. In response, this paper proposes a general framework for evaluating and selecting the best material for a given application. A novel hybrid multiple criteria decision making (MCDM) model combining DEMATEL-based ANP (DANP) and modified VIKOR is used to solve the material selection problems of multiple dimensions and criteria that are interdependent. Moreover, target-based criteria as well as cost and benefit criteria can be addressed simultaneously in the proposed model. Finally, an empirical case concerning the bush material selection for a split journal bearing is presented to illustrate the potential of the new model. The results show that the proposed method for material selection is effective and provides meaningful implications for designers and engineers to refer.     

Selecting suppliers using a new fuzzy multiple criteria decision model: the fuzzy balancing and ranking method

In this paper, we present a fuzzy multiple criteria decision making (FMCDM) model known as fuzzy balancing and ranking. In contrast to other MCDM models, our proposed model does not require the weights of decision making criteria. First, we appraise the performance of alternatives against criteria via linguistic variables which are expressed as triangular fuzzy numbers. The foregoing model obtains the alternative rankings through a four-stage process. Second, an outranking matrix is derived indicating that the frequency with which one alternative is superior to all other alternatives based on each criterion. Third, the outranking matrix is triangularised to obtain an implicit pre-ordering or provisional order of alternatives. Fourth, the provisional order of alternatives is subjected to various screening and balancing operations that require sequential application of a balancing principle to the so-called advantages–disadvantages table that combines the criteria with the pair-wise comparisons of alternatives. Additionally, to demonstrate the procedural implementation of the proposed model and its effectiveness, we apply it on a case study regarding the problem of supplier selection.     

Material selection for the tool holder working under hard milling conditions using different multi criteria decision making methods

Nowadays machining of materials in their hardened state, also called hard machining, is a challenge in production of tools and molds. It has some advantages such as lower process time and lower manufacturing cost when compared to conventional machining. In machining of hard workpiece materials, however, very high stresses act on the tool holder through the cutting tool. These stresses necessitate the tool holder to have some specific properties. Especially in hard milling, the tool holder should have high stiffness and should be able to dissipate the energy generated during interrupted cutting. Material cost of the tool holder is also important since lower costs provide a competitive advantage for manufacturers. The material selection for the tool holder should be conducted considering aforementioned requirements. To tackle the difficulty of the material selection with specific properties from a large number of alternatives, multi-criteria decision-making (MCDM) methods have been used. In this paper a decision model including extended PROMETHEE II (EXPROM2) (preference ranking organization method for enrichment evaluation), TOPSIS (technique for order performance by similarity to ideal solution) and VIKOR (VIšekriterijumsko KOmpromisno Rangiranje) methods were used for the selection of the best material for the tool holder used in hard milling. The criteria weighting was performed by compromised weighting method composed of AHP (analytic hierarchy process) and Entropy methods. The candidate materials were ranked by using these methods and the results obtained by each method were compared. It was confirmed that MCDM methods can be used for the solution of real time material selection problems. Tungsten carbide–cobalt and Fe–5Cr–Mo–V aircraft steel were found as the best materials for the tool holder production. The obtained results are found to be rather satisfactory and can be used in design stage of hard machining operations.     

Maintenance policy selection in manufacturing firms using the fuzzy MCDM approach

In manufacturing firms, there is a critical need for proper maintenance of manufacturing facilities. The maintenance process enhances customer satisfaction and reliability of the products, and increases the profit of the manufacturer. Therefore, a proper maintenance policy selection is a critical issue for manufacturers, as an inefficient maintenance policy affects not only the direct cost of the firm but also the other aspects. In the present study, maintenance policy selection at the level of the firm rather than the equipment level is shown, and for selection various criteria have been identified. The presented work not only provides the best alternatives but also provides an alternative ranking, which facilitates decision-makers in choosing alternatives according to their constraints. These selection criteria are different in nature, as some give a crisp value, whereas others are defined in linguistic terms. To select the appropriate maintenance policy, a distance-based fuzzy multicriteria decision-making (MCDM) approach has been employed. The proposed method provides the means for integrating the economic figure of merit with the strategic performance variables. The MCDM approach is efficient in incorporating data, in the form of linguistic variables, triangular fuzzy numbers, and crisp numbers, into the evaluation process of maintenance policy alternatives. A comprehensive example illustrates the application of the distance-based fuzzy MCDM approach.     

Materials selection using complex proportional assessment and evaluation of mixed data methods

Material selection is a very fast growing multi-criteria decision-making (MCDM) problem involving a large number of factors influencing the selection process. Proper choice of material is a critical issue for the success and competitiveness of the manufacturing organizations in the global market. Selection of the most appropriate material for a particular engineering application is a time consuming and expensive process where several candidate materials available in the market are taken into consideration as the tentative alternatives. Although a large number of mathematical approaches is now available to evaluate, select and rank the alternative materials for a given engineering application, this paper explores the applicability and capability of two almost new MCDM methods, i.e. complex proportional assessment (COPRAS) and evaluation of mixed data (EVAMIX) methods for materials selection. These two methods are used to rank the alternative materials, for which several requirements are considered simultaneously. Two illustrative examples are cited which prove that these two MCDM methods can be effectively applied to solve the real time material selection problems. In each example, a list of all the possible choices from the best to the worst suitable materials is obtained which almost match with the rankings as derived by the past researchers.     

不确定条件下基于TODIM的VFFS包装机选择方法

目的研究一种立式成型-充填-封口(Vertical Form-Fill-Seal,VFFS)包装机选择的不确定性多属性决策方法。方法通过对VFFS包装机选择的效益型指标和成本型指标进行分析,对VFFS包装机选择问题进行了形式化描述,构建了基于TODIM方法VFFS包装机选择的不确定性多属性决策模型,并以VFFS包装机选择实例进行了分析验证。结果直觉模糊加权平均(IFWA)算子处理了指标权重和定性指标的主观性和不确定性,考虑到决策者具有参照依赖和损失规避行为,给出了VFFS包装机选择的TODIM决策方法。结论利用IFWA算子和TODIM组合方法对模糊性、不确定性决策信息处理和对每个方案的全局价值求解,有利于从不同类型的VFFS包装机备选方案中进行选优。     

Application of fuzzy analytic network process for agile concept selection in a manufacturing organisation

Twenty-first century manufacturing organisations are capable of satisfying the varied requirements of modern customers called agile manufacturing (AM). AM enables an organisation to produce a variety of products within a short period of time in a cost-effective manner. Few researchers have brought out models for enabling organisations to improve their agility level. Total agile design system (TADS) is a model that is analogous to the technology integrated agile product development cycle. Concept selection is an important phase of TADS which is a multi-criteria decision-making (MCDM) problem. Selection of the best concept from agile perspective gains vital importance. Analytical network process (ANP) is a holistic approach that considers interactions and dependencies of various attributes and alternatives in a hierarchical framework used in MCDM problems. The concepts of fuzzy logic have been integrated with ANP in order to overcome the vagueness and uncertainty associated with opinions of the decision makers. Fuzzy ANP has been used to enable the selection of best concept. The case study has been carried out in an Indian traditional manufacturing organisation. The results of the validation indicate that fuzzy ANP is an effective approach for selecting best concept thereby improving agility of product development process.     

A comprehensive VIKOR method for material selection

In engineering design, material alternatives evaluate according to different criteria depending on the objectives of the problem. Performance ratings for different criteria are measured by different units, but in the decision matrix in order to have a valid comparison all the elements must be dimensionless. However, a lot of normalization methods have been developed for cost and benefit criteria, not only there has not been enough attention for engineering design situations in which approaching the target values are desirable but also the available methods have shortcomings. A new version of VIKOR method, which covers all types of criteria with emphasize on compromise solution, is proposed in this paper. The proposed comprehensive version of VIKOR also overcomes the main error of traditional VIKOR by a simpler approach. Suggested method can enhance exactness of material selection results in different applications, especially in biomedical application where the implant materials should possess similar properties to those of human tissues. Five examples are included to illustrate and justify the suggested method.     

Ranking alternatives via maximizing set and minimizing set based fuzzy MCDM approach

Abstract

This work suggests a maximizing set and minimizing set based fuzzy multiple criteria decision‐making (MCDM) model, where criteria are classified into cost and benefit criteria. The final fuzzy evaluation value of each alternative is developed based on the concept of subtracting the summation of weighted normalized benefit ratings from that of weighted normalized cost ratings. Using interval arithmetic of fuzzy numbers can develop the membership functions for the final fuzzy evaluation values. Chen's maximizing set and minimizing set is then applied to defuzzify all the final fuzzy numbers for ranking alternatives. Formulas for the membership functions and ranking procedure of the final fuzzy numbers are clearly presented. The suggested method provides an extension to the fuzzy MCDM techniques available. A numerical example demonstrates the computational process of the proposed method.     

Hesitant fuzzy integrated MCDM approach for quality function deployment: a case study in electric vehicle

Quality function deployment (QFD) is a product planning management instrument which has been used in a broad range of industries. However, the traditional QFD method has been criticised much for its deficiencies in acquiring experts’ opinions, weighting customer requirements (CRs) and ranking engineering characteristics (ECs). To overcome the limitations, an integrated analytical model is presented in this study for obtaining the importance ratings of ECs in QFD by integrating decision-making trial and evaluation laboratory (DEMATEL) technique and Vlsekriterijumska Optimizacija I Kompromisno Resenje (VIKOR) method under hesitant fuzzy environment. In particular, the hesitant fuzzy DEMATEL is used to analyse the interrelationships among CRs and determine their weights, and the hesitant fuzzy VIKOR is utilised to prioritise ECs. Finally, the feasibility and practicality of the proposed method are verified by an example regarding the product development of electric vehicle.     

An integration of a hybrid modified TOPSIS with a PGP model for the supplier selection with interdependent criteria

This paper deals with the supplier selection process when the criteria of selection are not independent. The primary aim is to illustrate that ignoring the interdependencies among these criteria leads to an unrealistic decision. Since supplier selection is a multiple-criteria decision-making (MCDM) process, the general structures of the relative methods are outlined in this paper. The proposed methodology then presents a comprehensive approach to find the best ranking among the alternative suppliers of a typical product. A hybrid modified TOPSIS is integrated with a preemptive goal programming model in this study and then compared to an analytical hierarchy process (AHP) to show the effect of considering interdependencies in the supplier selection process. The results indicate that the proposed methodology provides a higher total value of purchasing (TVP) than AHP while the total cost of purchasing (TCP) of both methods are equal. Empirical proof is offered based on a case study.     

Material selection based on ordinal data

Ranking and choosing the best material is one of most important stages in material selection process. Using linear assignment method, the multi-criteria decision making (MCDM) approach is proposed in decision-making process to rank the materials for a given engineering component with respect to several criteria. The proposed material selection procedure is relatively simple, and can be a useful approach when material selection problem includes qualitative properties or user-interaction aspects. The suggested approach also can be use for quantitative properties. Three examples are included to demonstrate the suggested method. Result of proposed approach showed good agreement with other methods.     

Hesitant fuzzy programming technique for multidimensional analysis of hesitant fuzzy preferences

The linear programming technique for multidimensional analysis of preferences (LINMAP) is the most representative method for handling the multiple criteria decision making (MCDM) problems with respect to the preference information over alternatives. This paper utilizes the main structure of LINMAP to develop a novel hesitant fuzzy mathematical programming technique to handle MCDM problems within the decision environment of hesitant fuzzy elements (HFEs). Considering the hesitancy of the decision maker, both the pair-wise comparison preference information over alternatives and the evaluation information of alternatives with criteria are represented by the HFEs. Based on the incomplete pair-wise preference judgments over alternatives, we propose the concepts of the hesitant fuzzy consistency and inconsistency indices. Furthermore, we construct a hesitant fuzzy mathematical programming model to derive the weights of criteria and the positive-ideal solution. In this hesitant fuzzy programming model both the objective function and partial constraints’ coefficients take the form of HFEs, and an effective approach based on the ranking method of HFEs is further developed to solve the new derived model. To address the incomplete and inconsistent preference structures of criteria weights, we introduce several deviation variables and establish the bi-objective nonlinear programming model. At length, we employ a green supplier selection problem to illustrate the feasibility and applicability of the proposed technique and conduct a comparison analysis to validate its effectiveness.     

An aggregation technique for optimal decision-making in materials selection

Materials selection is an onerous but very important activity in the design process. An inappropriate choice of material(s) can adversely affect the productivity and profitability and hence reputation of a manufacturing organization. The complexity of materials selection makes multi-criteria analysis an invaluable tool in the engineering design process. However, the application of various multi-criteria decision making (MCDM) methods can yield different results, especially when alternatives lead to similar performance. Therefore, an aggregation technique is proposed in this paper for optimal decision-making. In this approach, ranking orders obtained by various MCDM methods are used as the input of the suggested procedure and the outputs are aggregation rankings, which help designers and engineers to reach a consensus on materials selection for a specific application. An illustrative example is given to demonstrate the application of this procedure and its effectiveness in obtaining optimal materials selection.     

An integrated fuzzy approach for the selection of outsourcing manufacturing partners in pharmaceutical R&D

The selection of the outsourcing manufacturing partners (OMPs) is an important issue for research and development (R&D) in the pharmaceutical industry. The selection process considers several main criteria, as well as a few sub-criteria for each main criterion. Such problems can be formulated as hierarchical structures and can usually be resolved with multi-criteria decision-making approaches. This paper presents an integrated fuzzy approach for selecting a suitable OMP in pharmaceutical R&D. In the integrated approach, fuzzy concepts are used for decision-makers’ subjective judgments to reflect the vague nature of the selection process. Fuzzy AHP and fuzzy TOPSIS are included in the integrated approach. Fuzzy AHP is used to determine the fuzzy weights of criteria and sub-criteria because it can effectively determine various criteria's weights in a hierarchical structure. Fuzzy TOPSIS aims to find the OMP with the best performance with respect to the sub-criteria. We exemplify the integrated approach using a numerical application to demonstrate its feasibility.     

A novel approach for supplier selection based on the Kano model and fuzzy MCDM

This paper proposes a three-phase approach for supplier selection based on the Kano model and fuzzy Multi Criteria Decision-Making. Since the supplier selection problem involves different criteria, quality attributes have been assumed to denote the importance weight of the criteria for supplier selection. Furthermore, to consider the inherent vagueness of human thought, a fuzzy logic has been utilised. Initially, the importance weight of the criteria has been calculated using a fuzzy Kano questionnaire and fuzzy analytic hierarchy process. In the second phase, the Fuzzy TOPSIS technique has been used to screen out in capable suppliers. Finally, in the third phase, the filtered suppliers which are qualified, once again will be evaluated by the same approach for the final ranking. The proposed approach has also been examined in a case study.     

Vendor selection problem: a multi-criteria approach based on strategic decisions

Many factors in the current scenario have influenced manufacturing organisations to have a competitive edge by concentrating on entire supply chains. Sourcing decisions are one of the strategic decisions because they enable companies to reduce costs and improve profit figures. The main task in sourcing is vendor selection. Recent challenges such as shortened product life cycle, just-in-time environment, and the importance of strategic partnerships in upstream chains always influence companies to prioritise vendor selection. In addition, outsourced parts and components account for a significant contribution in the cost of finished goods. Thus evaluating and selecting the right vendor is the key to business. Vendors are selected merely on the basis of cost factors in the traditional approach. However, companies eventually have understood that their approach which emphasises costs as the sole criterion is inefficient and needs to be changed. To deal with the complex process of vendor evaluation, multiple criteria decision-making techniques have evolved. This study presents the integrated approach of multiple multi criteria decision making (MCDM) techniques such as fuzzy logic, strength-weakness-opportunity-threat (SWOT) analysis, and data envelopment analysis. The efficacy of the proposed approach is evident from the case study of an automotive component manufacturer involving 20 vendors, comprising of pre-qualification by fuzzy SWOT and final selection by DEA.     

An integrated linguistic MCDM approach for robot evaluation and selection with incomplete weight information

Nowadays selecting the most suitable robot is a difficult task for manufacturing firms due to increase in production demands and availability of various robot models. Robot evaluation and selection can be regarded as a multiple criteria decision-making (MCDM) problem and three key issues are the assessment of robots, the determination of criteria weights and the prioritisation of alternatives. This paper aims to propose an integrated model based on hesitant 2-tuple linguistic term sets and an extended QUALIFLEX approach for handling robot selection problems with incomplete weight information. The new model can not only manage uncertain and imprecise assessment information of decision-makers with the aid of hesitant 2-tuple linguistic term sets, but also derive the important weights of criteria objectively when the weight information is incompletely known. Moreover, based on the extended QUALIFLEX algorithm, the priority orders of robots can be clearly determined and a more reasonable and credible solution can be yielded in a particular industrial application. Finally, a robot selection case study is carried out, and comparative experiments indicate the practicality and effectiveness of the proposed integrated linguistic MCDM approach.     

Efficient MCDM Model for Evaluating the Performance of Commercial Banks: A Case Study

Evaluation of commercial banks (CBs) performance has been a significant issue in the financial world and deemed as a multi-criteria decision making (MCDM) model. Numerous research assesses CB performance according to different metrics and standers. As a result of uncertainty in decision-making problems and large economic variations in Egypt, this research proposes a plithogenic based model to evaluate Egyptian commercial banks’ performance based on a set of criteria. The proposed model evaluates the top ten Egyptian commercial banks based on three main metrics including financial, customer satisfaction, and qualitative evaluation, and 19 sub-criteria. The proportional importance of the selected criteria is evaluated by the Analytic Hierarchy Process (AHP). Furthermore, the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), Vlse Kriterijumska Optimizacija Kompro-misno Resenje (VIKOR), and COmplex PRoportional ASsessment (COPRAS) are adopted to rank the top ten Egyptian banks based on their performance, comparatively. The main role of this research is to apply the proposed integrated MCDM framework under the plithogenic environment to measure the performance of the CBs under uncertainty. All results show that CIB has the best performance while Faisal Islamic Bank and Bank Audi have the least performance among the top 10 CBs in Egypt.