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.     

Selection of porous materials in marine system design: The case of heat exchanger aboard ships

Porous materials are processed in various areas of material science and manufacturing. Furthermore, the varieties of porous materials ensure great advantages to designers. This paper proposes a decision aid mechanism based on fuzzy axiomatic design (FAD) to select adequate form of porous materials in marine systems design. It enables elimination and choice of suitable material alternatives in respect to two sets of attributes: generic material selection attributes (GMSA) and specific material selection attributes (SMSA). Furthermore, the paper specifically addressed use of porous materials in plate type heat exchanger design to demonstrate the proposed model. It is expected that the paper ensures a novel procedure for marine engineers and naval architectures in conceptual design process of marine systems.     

A formal method for subjective design evaluation with multiple attributes

This paper contributes toward a more formal theory and methodology for design by mathematically modeling the functional relationships between design decisions and the ultimate overall worth of a design. The conventional approach to design evaluation is limited in two respects. First, the direct measurement of attribute performance levels does not reflect the subsequentworth to the designer. Second, ad hoc methods for determining the relative importance or priority of attributes do not accurately quantify beneficial attribute tradeoffs. This information is critical to the iterative redesign process. A formal Methodology for the Evaluation of Design Alternatives (MEDA) is presented which resolves these problems and can be used to evaluate design alternatives in the iterative design/redesign process. Multiattribute utility analysis is employed to compare the overall utility or value of alternative designs as a function of the levels of several performance characteristics of a manufactured system. The evaluation function reflects the designer's preferences for sets of multiple attributes. Sensitivity analysis provides a quantitative basis for modifying a design to increase its utility to the decision-maker. Improvements in one or more areas of performance and tradeoffs between attributes which would increase desirability of a design most are identified. A case study of materials selection and design in the automotive industry is presented which illustrates the steps followed in application of the method.     

基于不确定语言信息的物流供应商选择

为解决传统供应商的选择与评价过程中专家评判的模糊性和不确定性问题,提出了一种基于不确定语言信息的物流服务供应商选择方法。该方法以不确定语言变量来表征专家的评判从而避免了决策信息的丢失。继而建立了物流服务质量评价属性的权重优化模型,并构造拉格朗日函数来求解该模型,得到评价属性的最优权重。接着利用不确定语言加权几何平均（ULWG）算子集结专家评判信息,则得到供应商的优先排序。给出了基于不确定语言信息的供应商选择的算法步骤和应用实例。     

Model for negotiating the price and due date for a single order with multiple suppliers in a make-to-order environment

The nature of the business of a make-to-order company complicates its procurement activities. This paper is concerned with the development of a model for price and due-date negotiations between a manufacturer and its multiple suppliers in fulfilling a single order from a customer in a make-to-order environment. The developed negotiation model incorporates several established negotiation theories: aspiration level, limit level, natural forces acting on a negotiator and effective alternatives. Instead of presenting a single alternative for an offer in the current round of negotiation, we apply the Interactive Weighted-Tchebycheff method to generate a set of effective alternatives for presentation to the decision-maker in each round of the negotiation process. By giving a set of alternatives, we provide a degree of freedom to incorporate the decision-maker's preference in making offers and counter-offers during the negotiation process.     

An integrated approach to evaluating conceptual design alternatives in a new product development environment

As many companies have demonstrated over time, a conceptual design for a new product contributes greatly to an improvement in competitiveness, because it permits a reduction of costs, an increase in quality, and, often, a shortening of the time necessary to get the product on the market. That is why the evaluation of conceptual design alternatives created in a new product development (NPD) environment has long been very vital and a critical point for the future success of companies in fast-growing markets. These alternatives can be evaluated using the analytic hierarchy process (AHP), one of the most commonly used multiple criteria decision making (MCDM) techniques. This technique is used to reduce the number of conceptual design alternatives after ranking them using the scores obtained from the process. Furthermore, another technique, simulation analysis integrated with the AHP, is also used to help decision makers (product engineers or managers) perform economic analyses of the AHP's high-score alternatives using data from the generated simulation model of a real-life manufacturing system in which the final alternative is produced. In short, the objectives of this research are: first, to use the AHP technique to evaluate conceptual design alternatives in a NPD environment; second, to use a simulation generator integrated with this technique in order to perform economic analyses for the AHP's high-score alternatives. Finally, the results of both techniques, simulation and AHP, are used in a benefit/cost (B/C) analysis to reach a final decision on the conceptual design alternatives.     

On the valuation of goods and selection of the best design alternative

A platform is the set of elements and interfaces that are common to a family of products. In this paper, the design of a platform-based product family is formulated as an optimization problem. This optimization is then transformed into a two-step process amenable to industrial product design processes. The first step involves designing the technical aspects of the product family, optimizing an objective (or a set of objectives) subject to technical constraints, with external uncertain factors fixed. We have previously presented such a method for designing product families based on platforms that optimizes performance and cost metrics, using variables and a system model. That approach allows a team of engineers to design and evaluate candidate platforms, given perfect understanding of the designs and requirements. The second step is to quantify the value to the firm for each identified design alternative, while here accounting for external uncertain factors of the product family development. In this paper we present a model to perform this second step of the overall approach. Real options concepts are introduced to model the risks and delayed decision benefits present during product development due to uncertainty in technologies, funding, etc. We develop a quantitative measure of the value to the company for different family designs, and apply it to select the most appropriate design from the possible alternatives. An application to the design of platform-based families of spacecraft is shown. Electronic Publication     

基于证据理论的产品包装方案综合成本测度

目的研究不确定信息背景下产品包装方案的综合成本测度,实现产品包装方案的优选。方法对产品包装方案综合成本测度指标体系进行层次化建模;采用隶属度的方法对测度指标的初始评分值进行规范化处理,引入权重来实现对各测度指标重要程度的区分;将备选包装方案视为辨识框架中的焦元,计算各测度指标下所有焦元的加权基本概率分配值,并进行两阶的Dempster合成,最后基于信任区间进行备选包装方案综合成本的测度。结果通过某小型电气控制柜包装方案综合成本测度的案例应用,识别出最优的包装方案,验证了所提出方法的有效性和可行性。结论所提出方法能够为专家评分含有不确定信息时的产品包装方案综合成本测度提供了一种解决思路。     

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.     

AN OVERVIEW OF TAGUCHI METHOD AND NEWLY DEVELOPED STATISTICAL METHODS FOR ROBUST DESIGN

Robust Design is an important method for improving product quality, manufacturability, and reliability at low cost. Taguchi's introduction of this method in 1980 to several major American industries resulted in significant quality improvement in product and manufacturing process design. While the robust design objective of making product performance insensitive to hard-to-control noise was recognized to be very important, many of the statistical methods proposed by Taguchi, such as the use of signal-to-noise ratios, orthogonal arrays, linear graphs, and accumulation analysis, have room for improvement. To popularize me use of robust design among engineers, it is essential to develop more effective, statistically efficient, and user-friendly tech niques and tools. This paper first summarizes the statistical methods for planning and analyzing robust design experiments originally proposed by Taguchi; then reviews newly developed statistical methods and identifies areas and problems where more research is needed. For planning experiments, we review a new experiment format, the combined array format, which can reduce the experiment size and allow greater flexibility for estimating effects which may be more important for physical reasons. We also discuss design strategies, alternative graphical tools and tables, and computer algorithms to help engineers plan more efficient experi ments. For analyzing experiments, we review a new modeling approach, die response model approach, which yields additional information about how control factor settings dampen the effects of individual noise factors; this helps engineers better under stand die physical mechanism of the product or process. We also discuss alternative variability measures for Taguchi's signal-to-noise ratios and develop methods for empirically determining the appropriate measure to use.     

Using FANP approach on selection of competitive priorities based on cleaner production implementation: a case study in PCB manufacturer,Taiwan

The aim of this paper is to identify and discuss some of the important and critical decision criteria including cleaner production implementation of an efficient system to prioritize competitive priorities. Fuzzy analytic network process (FANP) based methodology is discussed to tackle the different decision criteria involved in the selection of competitive priorities in current business scenario. FANP is an efficient tool to handle the fuzziness of the data involved in deciding the preferences of different decision variables. The linguistic level of comparisons produced by the professionals and experts for each comparison are tapped in the form of triangular fuzzy numbers to construct fuzzy pairwise comparison matrices. The implementation of the system is demonstrated by a problem having four stages of hierarchy which contains different criteria, attributes and alternatives at wider perspective. The proposed model can provide a hierarchical framework for the cleaner production implemented organization to select on its competitive priorities.     

Fuzzy analytic hierarchy process (FAHP) for multi-criteria selection of microalgae harvesting and drying processes

Microalgae are considered to be a promising source of biomass compared with first and second generation feedstocks. However, the high energy requirement for harvesting and drying of the algal biomass poses challenge to commercialization due to implications on both carbon footprint (CF) and cost. In this work, we propose a systematic methodology for the multi-criteria evaluation of alternatives for the harvesting and drying processes. A fuzzy analytic hierarchy process (FAHP) approach is used, where the pairwise comparison of the multiple criteria and alternatives were done to prioritize the best harvesting and drying method within the fuzzy bounds of the value judgment that satisfies the consistency index. FAHP also allows the degree of confidence of the expert to be quantified. A case study of four alternatives each for the harvesting and drying process is used to demonstrate the process. Technology capability, cost and environmental impacts (comprised CF, land footprint and water footprint) are identified as the selection criteria for harvesting and drying process, respectively. Results show that flotation is the best alternative for harvesting process, while sun drying is the best among the drying alternatives. Sensitivity analysis is used to give insights on the robustness of the decision model and enables the understanding of critical criteria that would significantly influence the ranking of the alternatives. The proposed FAHP approach therefore can effectively deal with the uncertainty of judgment in the decision-making process in the evaluation of microalgae harvesting and drying processes.     

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.     

基于AHP-TOPSIS方法的儿童安全座椅设计方案评价研究

目的 解决儿童安全座椅设计方案评价过程中的主观性和片面性等问题,获得科学的设计方案。方法 依据文献研究和用户与专家问卷找出消费者选购产品时考虑的需求点和问题点,初选出儿童安全座椅评价指标;采用合理性测评筛除低效用指标,确定儿童安全座椅评价指标体系的科学构建。提出一种结合层次分析法（AHP）和逼近理想解排序法（TOPSIS）的综合评价方法,对3款儿童安全座椅的设计方案进行综合评价优选,确定第2种设计方案为获得分数最高的优选方案。结论 AHP-TOPSIS模型应用于儿童安全座椅设计方案的优选可以消减决策者对设计方案评价的片面性与主观性,实现相对科学的儿童安全座椅设计方案的评价。该方法在其他产品开发过程中处于设计阶段的方案评价与优选具有一定的通用性。     

Materials selection and multi-attribute utility analysis

Summary Multi-attribute utility analysis (MAUA) has emerged as a powerful tool for materials selection and evaluation. An operations research technique, MAUA has been used in a wide range of engineering areas, of which materials science and engineering is one of the more recent. Utility analysis affords a rational method of materials selection which avoids many of the fundamental logical difficulties of many widely used alternative approaches. However, MAUA has traditionally been used in materials selection problems only, in which there is certainty regarding the attribute levels of the alternatives. For many new technologies this is not the case. Another operations research technique, subjective probability assessment (SPA), can be used to address this issue. SPA makes it possible to measure a probabilistic distribution describing the confidence of the decision maker in the levels of attributes for which there is a high degree of uncertainty. These probability distributions can be used in conjunction with MAUA to provide a consistent framework for making materials selection decisions. Furthermore, the use of these techniques extends beyond the problem of materials selection into the more speculative areas of materials competitiveness and market demand in cases involving new, unproven technologies.     

Demonstration of probabilistic ordinal optimization concepts for continuous-variable optimization under uncertainty

A very general and robust approach to solving optimization problems involving probabilistic uncertainty is through the use of Probabilistic Ordinal Optimization. At each step in the optimization problem, improvement is based only on a relative ranking of the probabilistic merits of local design alternatives, rather than on precise quantification of the alternatives. Thus, we simply ask the question: “Is that alternative better or worse than this one?” to some level of statistical confidence we require, not: “HOW MUCH better or worse is that alternative to this one?”. In this paper we illustrate an elementary application of probabilistic ordinal concepts in a 2-D optimization problem. Two uncertain variables contribute to uncertainty in the response function. We use a simple Coordinate Pattern Search non-gradient-based optimizer to step toward the statistical optimum in the design space. We also discuss more sophisticated implementations, and some of the advantages and disadvantages versus other approaches to optimization under uncertainty.     

Robust multiattribute decision making under risk and uncertainty in engineering design

In this article, the problem of choosing from a set of design alternatives based upon multiple, conflicting, and uncertain criteria is investigated. The problem of selection over multiple attributes becomes harder when risky alternatives exist. The overlap measure method developed in this article models two sources of uncertainties—imprecise or risky attribute values provided to the decision maker and inabilities of the decision-maker to specify an exact desirable attribute value. Effects of these uncertainties are mitigated using the overlap measure metric. A subroutine to this method, called the robust alternative selection method, ensures that the winning alternative is insensitive to changes in the relative importance of the different design attributes. The overlap measure method can be used to model and handle various sources of uncertainties and can be applied to any number of multiattribute decision-making methods. In this article, it is applied to the hypothetical equivalents and inequivalents method, which is a multiattribute selection method under certainty.     

A COMPARISON OF THE ANALYTIC HIERARCHY PROCESS WITH MULTIATTRIBUTE UTILITY THEORY: A CASE STUDY

This paper presents the results of a study in which two prominent multicritena methodologies were used to evaluate a discrete set of technological alternatives. The first is Saaty's Analytic Hierarchy Process (AHP), and the second is Keeney and Raiffa's Multiattribute Utility Theory (MAUT). A case study designed to select the next generation of rough terrain cargo handlers for the U.S. Army provided the backdrop. Three alternatives were identified and ultimately ranked using the two methodologies. The intent was to detennine the strengths and weaknesses of each, and to characterize the conditions under which one might be more appropriate than the other.

The evaluation team consisted of five program managers and engineers from the Belvoir Research, Development & Engineering Center. The objective hierarchy used in both cases contained twelve attributes. In general, the AHP was found to be more accessible and conducive to consensus building. Once the attributes were defined, the decision makers had little difficulty in furnishing the necessary data and discussing the intermediate results. The same could not be said for the MAUT analysis. The need to juggle twelve attributes at a time produced a considerable amount of frustration among the participants. In addition, the lottery questions posed during the data collection phase had an unsettling effect that was never satisfactorily resolved.     

Attributes of Engineering Graduates and Their Impact on Curriculum Design

This paper presents the findings of an Engineering Curriculum Task Force of the College of Engineering and Applied Sciences at Arizona State University. The Task Force's charge was to explore changes that would better prepare baccalaureate-level engineers for the practice of their profession in the next decade. The generic data developed in the process used by the Task Force are given here. For example, a set of ten important attributes deemed desirable for newly graduated engineers and produced by education, is presented. Also, the rankings by industry, alumni, students, and faculty, of the relative importance of each of these ten attributes and the performance of new graduates in each, are given. Generic curriculum features necessary for successful generation of these attributes are discussed. Finally, the results of an alumni survey are presented which show the overwhelming support for a broad-based undergraduate program by graduates of all degree programs.     

Commercial-Off-The-Shelf Selection Process

Abstract:

This article presents a Commercial-Off-The-Shelf (COTS) evaluation and selection process that utilizes a weighted scoring model to facilitate the comparison of COTS components relative to a number of pre-established evaluation criteria. The application of a COTS evaluation methodology will enable project teams responsible for designing complex systems to take advantage of potential economic leverage and performance advantages COTS technology presents. More importantly, this approach provides a mechanism for careful evaluation of the candidate COTS components to ensure engineers developing COTS-intensive systems give appropriate consideration to critical COTS attributes such as operational requirements, risk, cost, technology maturity, and supplier viability.