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.     

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.     

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.     

A tool for meaning driven materials selection

There are several tools used in materials selection processes by designers. However, they are mostly engineering based tools, which are dominated by numerical (or technical) material data that is mostly of use in embodiment or detailed design phases of new product development. On the other hand, product designers consider certain aspects such as product personality, user-interaction, meanings, emotions in their material decisions. In this regard, existing tools and methods do not fully support designers in their materials selection processes. This paper describes the development of a new materials selection tool holding the idea of [meaning driven materials selection]. In addition, the paper consists of a study conducted to create data for a dummy application.     

A decision making methodology for material selection using an improved compromise ranking method

An ever increasing variety of materials is available today, with each having its own characteristics, applications, advantages, and limitations. In choosing the right material, there is not always a single definite attribute of selection and the designers and engineers have to take into account a large number of material selection attributes. This paper presents a logical procedure for material selection for a given engineering application. The procedure is based on an improved compromise ranking method considering the material selection attributes and their relative importance for the application considered. Two examples are included to illustrate the approach.     

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.     

A subjective and objective integrated multiple attribute decision making method for material selection

The selection of an optimal material for an engineering design from among two or more alternative materials on the basis of two or more attributes is a multiple attribute decision making (MADM) problem. The selection decisions are complex, as material selection is more challenging today. There is a need for simple, systematic, and logical methods or mathematical tools to guide decision makers in considering a number of selection attributes and their interrelations and in making right decisions. This paper proposes a novel MADM method for material selection for a considered design problem. The method considers the objective weights of importance of the attributes as well as the subjective preferences of the decision maker to decide the integrated weights of importance of the attributes. Furthermore, the method uses fuzzy logic to convert the qualitative attributes into the quantitative attributes. Three examples are presented to illustrate the potential of the proposed method.     

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.     

Application of fuzzy VIKOR and environmental impact analysis for material selection of an automotive component

Material selection is a complex process, since the process includes many criteria, determination of criteria weight and the most important factor is that the selection of appropriate criterion. The last factor indicates that the criterion must be selected in a manner, such that the selection based upon the known material parameters and the requirements of the application. Therefore the material selection can be done using MCDM (Multi Criterion Decision Making) methods. Since the inputs provided by the decision maker in linguistic manner, there is a possible chance of getting incomplete problems. So in order to overcome the problem, the inputs could be provided as fuzzy numbers. Since fuzzy set represents the uncertainty in human perceptions. In this paper, VIKOR (VlseKriterijumska Optimizacija I Kompromisno Resenje in Serbian, means Multicriteria Optimisation and Compromise Solution) has been used a MCDM tool for the selection of alternate material for instrument panel used in electric car and in order to evaluate this selection process in fuzzy environment, fuzzy based VIKOR is used. In addition to the fuzzy VIKOR method, the environmental impacts are also considered and compared for the four materials. The results achieved in both the assessment, showed that Polypropylene could be an alternate material for the instrument panel. The objective of this study is to develop a rational method to select the best material for an application based upon known material parameters and the requirements of the application.     

A Comparative Study for Material Selection of Sensor Element Using Analytic Hierarchy Process

Material selection is crucial for sensor elements. Because of the numerous material alternatives available in the market, systematic methods must be employed to select the most suitable sensor material that satisfies technical, metrological and economic criteria. In this study, analytic hierarchy process (AHP) is employed for the selection of sensor material. Twenty common materials are classified in three groups according to their elasticity modulus, and then the best sensor material in each group is determined then the AHP rankings of the materials are calculated. The results show that AISI 4340 steel and CuBe alloy are the most suitable materials within the high- and lower-modulus groups, respectively, and Ni-Span-C is another good alternative sensor element.     

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.     

基于相对关联度的工程选材决策模型及应用

 根据灰色关联度反映候选材料的理想解之间曲线形状的相似性,在综合考虑正、负理想解影响的基础上,通过构造相对关联度,建立工程选材决策模型.以低温存储罐材料选择为例,根据专家评分得到所选8种评价指标的权重,确定理想解和负理想解,继而分别计算10种候选低温材料的相对关联度,进行选材决策.结果表明：全硬态301型不锈钢的相对关联度最高,是最佳的低温存储罐材料,这与实际应用和加权性质分析法得出的选择结果一致,而且所得其他候选材料的测评效果排序也更加合理.该模型同时反映候选材料的理想解和负理想解之间曲线的相似性,物理含义更加明确,分析问题更加全面、客观,是工程选材决策的有力工具.     

应用规范化公式的MCDM保序研究

规范化公式的应用会破坏方案之间的独立性，导致逆序的产生。提出了两种改进规范化公式的方法以消除逆序，并以加权算术平均（WAA）集结算子的多属性决策分析(MCDM)为例验证了所提出方法的合理性和有效性。改进后的规范化公式不仅可以应用于WAA算子，还可以应用到其他类似的决策算子中。改进后规范化公式的应用可以降低和消除规范化公式对无关方案独立性的影响，使得MCDM决策过程更加合理、科学。     

Study of the compatibility between criteria in a set of materials requirements: Application to a machine tool frame

This contribution to materials selection theory aims at developing methodological methods and tools to analyse a complex set of material requirements with the objective of forecast whether there are materials that can fulfil it, or alternatively, if multi-materials selection is more likely to provide a solution. This “pre-analysis” of requirements examines the two main reasons which may prevent a single material solution: nonuniformity of materials space filling, or intrinsic contradiction between properties.A variety of statistical tools is used, based on Multivariate Analysis Methods as Principal Component Analysis (PCA) and the estimation of density distribution in the materials space. These tools allow to evaluate the “statistical compatibility” between the requirements and the available materials, and provides an estimate of the likelihood to find a single material solution or not. The methodology is applied to the research of a material for a machine tool frame.     

A novel multiple attribute material selection approach with uncertain membership linguistic information

In engineering design, the decision to select an optimal material has become a challenging task for the designers, and the evaluation of alternative materials may be based on some multiple attribute decision making (MADM) methods. However, the current methods for material selection may induce the information losing and cannot represent the real preference of decision maker precisely. Therefore, in this paper, inspired by the idea of the intuitionistic linguistic variables, we define a new fuzzy variable called uncertain membership linguistic variable (UMLV) which composes two linguistic variables and membership degrees of elements to the linguistic variables. Meanwhile, the operational laws, score function, accuracy function and comparison rules of the UMLV are defined. Then, some aggregation operators are developed for aggregating the uncertain membership linguistic information such as the uncertain membership linguistic weighted average (UMLWA) operator, the uncertain membership linguistic weighted geometric (UMLWG) operator, the uncertain membership linguistic ordered weighted average (UMLOWA) operator and the uncertain membership linguistic ordered weighted geometric (UMLOWG) operator, and some desirable properties of these operators are discussed. Based on the proposed operators, an approach is proposed for material selection problems under uncertain membership linguistic environment. Finally, two numerical examples for material selection are given to illustrate the application of the proposed approach.     

Filtration in materials selection and multi-materials design

Materials selection methods by free searching consist in four steps: translation, filtration, classification and documentation. The second step, limiting the field of solutions, must be analysed accurately when the constraints are related with free design parameters. This paper describes methods to deal with this filtration step in the cases of materials selection and multi-materials design. The classical filtration in single materials selection is extended to cases with several free geometric parameters. Then, a filtration approach for multi-materials design with undefined number of components and free geometric parameters is proposed. Finally, a case study concerning the design of a pipe material for offshore oil extraction is presented. The application of this work allows a preliminary elimination of unsuitable materials in the definition of multi-materials components, so it will be useful to avoid long numerical studies.     

Methodology selecting packaging materials combined multi-sensory experience and fuzzy three-stage network DEA model

Materials selection involves thousands of material types and evaluation parameters. Considering multisensory experience for packaging materials selection is an important trend but a difficult duty that involves uncertainty due to the subjectivity of humans. The main aim of this study is to establish a model to determine the consumer sensory experience of packaging materials as a function supporting packaging material selection development. When the consumer interacts before and after opening the packaging, vision and tactility are the foremost sensory feedback types, which are difficult to measure for fuzziness and uncertainty. Thus, given the consumer senses of vision and tactility, this paper addresses the relationship between sensory experience and packaging material properties. This is creatively formulated in three stages from the physical properties and the psycho-physical to the affective levels. The proposed approach that combines fuzzy theory and three-stage network data envelopment analysis (DEA) is used to rank 12 toning lotion bottle packaging materials. It is validated that this model allows a clear decision-making basis for material selection in packaging design, and physiological signal tests provided key data to support material selection. Moreover, it realized the function of predicting physiological signal according to material properties by backpropagation neural network (BPNN).     

Extreme Energetic Materials at Ultrahigh Pressures

Owing to their extremely high energy density, single-bonded polymeric nitrogen and atomic metallic hydrogen are generally regarded as the ultimate energetic materials. Although their syntheses normally require ultrahigh pressures of several hundred gigapascals (GPa), which prohibit direct materials application, research on their stability, metastability, and fundamental properties are valuable for seeking extreme energetic materials through alternative synthetic routes. Various crystalline and amorphous polymeric nitrogens have been discovered between 100 and 200 GPa. Metastability at ambient conditions has been demonstrated for some of these phases. Cubic-gauche and black-phosphorus polymorphs of single-bonded nitrogen are two particularly interesting phases. Their large hystereses warrant further application-inspired basic research of nitrogen. In contrast, although metallic hydrogen contains the highest-estimated energy density, its picosecond lifetime and picogram quantity make its practical material application impossible at present. “Metallic hydrogen” remains a curiosity-driven basic research pursuit focusing on the pressure-induced evolution of the molecular hydrogen crystal and its electronic band structure from a low-density insulator with a very wide electronic band gap to a semiconductor with a narrow gap to a dense molecular metal and atomic metal and eventually to a previously unknown exotic state of matter. This great experimental challenge is driving relentless advancement in ultrahigh-pressure science and technology.     

非金属纳米材料及其应用

介绍了非金属纳米材料的制备、分类、特点、性质及其在生物医学、环境、化学、材料和电子、电气等领域的应用研究情况 ,并对其发展方向予以展望     

Hybrid Data-Driven and Mechanistic Modeling Approaches for Multiscale Material and Process Design

The world’s increasing population requires the process industry to produce food, fuels, chemicals, and consumer products in a more efficient and sustainable way. Functional process materials lie at the heart of this challenge. Traditionally, new advanced materials are found empirically or through trial-and-error approaches. As theoretical methods and associated tools are being continuously improved and computer power has reached a high level, it is now efficient and popular to use computational methods to guide material selection and design. Due to the strong interaction between material selection and the operation of the process in which the material is used, it is essential to perform material and process design simultaneously. Despite this significant connection, the solution of the integrated material and process design problem is not easy because multiple models at different scales are usually required. Hybrid modeling provides a promising option to tackle such complex design problems. In hybrid modeling, the material properties, which are computationally expensive to obtain, are described by data-driven models, while the well-known process-related principles are represented by mechanistic models. This article highlights the significance of hybrid modeling in multiscale material and process design. The generic design methodology is first introduced. Six important application areas are then selected: four from the chemical engineering field and two from the energy systems engineering domain. For each selected area, state-of-the-art work using hybrid modeling for multiscale material and process design is discussed. Concluding remarks are provided at the end, and current limitations and future opportunities are pointed out.