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.     

A fuzzy AHP-based simulation approach to concept evaluation in a NPD environment

The evaluation process of conceptual design alternatives in a new product development environment is a critical point for companies who operate in fast-growing markets. Various methods exist that are able to successfully carry out this difficult and time-consuming process. One of these methods, the Analytic Hierarchy Process (AHP) has been widely used to solve multiple-criteria decision-making problems (i.e., concept evaluation, equipment selection) in both academic research and in industrial practice. However, due to vagueness and uncertainty in the decision-maker's judgment, a crisp, pair-wise comparison with a conventional AHP may be unable to accurately capture the decision-maker's judgment. Therefore, fuzzy logic is introduced into the pair-wise comparison in the AHP to compensate for this deficiency in the conventional AHP. This is referred to as fuzzy AHP. In this paper, a fuzzy AHP method is used to reduce a set of conceptual design alternatives by eliminating those whose scores (or weights) are smaller than a predetermined constant value obtained under certain circumstances. Then, simulation analysis is integrated with the fuzzy AHP method, and the hybrid method is used to help the decision-makers (product engineers or managers) evaluate the remaining alternatives from the fuzzy AHP method. A real-life manufacturing system is used as the testbed for the proposed techniques. Finally, the results of both techniques, fuzzy AHP and simulation, are used for Preference Ratio analysis to reach to the final alternative.     

模糊理想解法在多准则群决策中的应用

将模糊数学理论引入到不确定环境下的多准则群决策问题中,利用模糊理想解法进行方案排序.用三角模糊数来描述模糊准则权重和模糊准则属性值,给出了使用模糊理想解法进行群决策问题求解的一般步骤;通过供应商选择这一实例验证了本方法的有效性.     

Determining the Importance Weights for the Customer Requirements in QFD Using a Fuzzy AHP with an Extent Analysis Approach

In the Quality Function Deployment (QFD) process, determining the importance weights for the customer requirements is an essential and crucial process. The Analytic Hierarchy Process (AHP) has been used to determine the importance weights for product planning, but this has occurred mainly in crisp (non-fuzzy) decision applications. However, human judgment on the importance of customer requirements is always imprecise and vague. To make up for this deficiency in the AHP, a fuzzy AHP with an extent analysis approach is proposed to determine the importance weights for the customer requirements. In the method, triangular fuzzy numbers are used for the pairwise comparison of a fuzzy AHP. By using the extent analysis method and the principles for the comparison of fuzzy numbers, one can derive the weight vectors. The new approach can improve the imprecise ranking of customer requirements inherited from studies based on the conventional AHP. Furthermore, the fuzzy AHP with extent analysis is simple and easy to implement to prioritize customer requirements in the QFD process compared with the conventional AHP. This paper uses an example of a hair dryer design to illustrate the proposed approach.     

基于区间二型模糊EDAS的多属性决策方法

针对多属性决策存在的复杂性和不确定性问题,提出基于区间二型模糊平均解距离法 (evaluation based on distance from average solution,EDAS) 的多属性决策方法。采用区间二型模糊集合 (interval type-2 fuzzy sets,IT2FS) 表达评价信息解决专家的偏好信息存在个体化差异问题,并纳入EDAS对备选方案进行排序。以区间二型模糊数表达评价信息构建决策矩阵,以计算得到的综合评价值的去模糊化结果作为最终的方案排序依据。针对EDAS中属性权重需要从外部获取的问题,采用区间二型模糊集合改进的最优最劣法 (best-worst method,BWM) 确定属性权重。最后,以某汽车制造企业选购新能源汽车云服务方案为例,验证所提方法的有效性。     

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.     

A fuzzy group decision making approach to new product concept screening at the fuzzy front end

Efficient new product concept screening plays an important role in new product development (NPD). Due to the inherent complexity, incompleteness and ambiguity in NPD, fuzzy approaches have been widely developed and used for new product concept screening. Because of the group behaviours (diversity of gate-team members and senior management’s preference), the new product concept screening is typical group decision-making problem. Moreover, it is usually more efficient to conduct the screening evaluation in a gate-team and make a screening decision outside the gate-team by senior management. Therefore, it is necessary to provide a result with a high degree of flexibility and credibility so as to better support the senior management to make a screening decision in NPD. Existing fuzzy approaches neglect these two issues. Towards this end, a three-stage fuzzy group decision-making approach is proposed to assist the senior management perform new product concept screening. A case study is borrowed from the literature to illustrate our proposed approach. Our approach is compared with two existing techniques from theoretical and empirical perspectives. The results show that the proposed approach can capture the group behaviours and present a relatively realistic and informative result which gives the senior management a high degree of flexibility and credibility in new product concept screening.     

An integrated approach for machine tool selection using fuzzy analytical hierarchy process and grey relational analysis

Selecting a proper machine tool is one of the important decisions a company has to make. Companies which fail to do so face many problems which negatively affect the firm's productivity, flexibility, precision and its responsiveness capabilities. Selection of a machine tool involves a lot of criteria to be simultaneously studied and so it requires a multi-criterion decision making (MCDM) method to solve it. Also the subjectivity involved in such decisions ask for the use of theories such as fuzzy and grey which are very effective in handling subjective inputs. This paper integrates the fuzzy analytic hierarchy process (AHP) and grey relational analysis approaches for the selection of a machine tool from a given set of alternatives. Fuzzy AHP is used to calculate the priority weights of the criteria. Subsequently grey relational analysis (GRA) is employed to rank the alternatives. A well known problem existing in literature has been picked up for the numerical illustration. The results obtained in this paper are better when compared with that existing in literature.     

一类灰色模糊决策问题的熵权分析方法

以灰色系统理论和模糊数学为基础，探讨了不确定型决策问题的特性，分析了一些相关成果中所给方法在直接处理灰色模糊数方面的优势与不足。运用优化理论和熵极大化准则，建立了基于灰色模糊关系的多属性群体决策方法，分别对属性权重向量已知和未知两种情况给出了简便实用的算法，通过算例说明了算法的合理性。     

Modified analytic hierarchy process to incorporate uncertainty and managerial aspects

The analytic hierarchy process (AHP) is a powerful multiple-criteria decision analysis technique for dealing with complex problems. Traditional AHP forces decision-makers to converge vague judgements to single numeric preferences in order to estimate the pairwise comparisons of all pairs of objectives and decision alternatives required in the AHP. The resultant rankings of alternatives cannot be tested for statistical significance and it lacks a systematic approach that addresses managerial/soft aspects. To overcome the above limitations, the present paper presents a modified analytic hierarchy process, which incorporates probabilistic distributions to include uncertainty in the judgements. The vector of priorities is calculated using Monte Carlo simulation. The final rankings are analysed for rank reversal using analysis of variance, and managerial aspects (stake holder analysis, soft system methods, etc.) are introduced systematically. The focus is on the actual methodology of the modified analytic hierarchy process, which is illustrated by a brief account of a case study.     

Analytic hierarchy prioritisation of new product development activities for electronics manufacturing

New product development (NPD) is a managerial process, performed by many activities. The purpose of this paper is to present the application of the analytic hierarchy process (AHP) to prioritise activities of NPD for manufacturing companies of electronic products. Mathematical modelling was the research method adopted. An electronics cluster located in the southeast region of Brazil was studied. Therefore, 10 of the 42 activities from an NPD model were suggested to be excluded for the electronics companies. These activities have less than 0.5% overall priority. The results from the AHP application were welcomed by the companies’ NPD experts.     

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 integrated fuzzy multi-criteria group decision-making approach for green supplier evaluation

Purchasing is one of the most vital functions within a company and supplier performance evaluation is one of the most important business processes of the purchasing function. Traditionally, companies have considered factors such as price, quality, flexibility, etc. while evaluating suppliers. However, environmental pressures urge them to consider green issues. This study proposes a decision model for supplier performance evaluation by considering various environmental performance criteria. An integrated, fuzzy group decision-making approach is adopted to evaluate green supplier alternatives. More precisely, a fuzzy analytic hierarchy process (AHP) is applied to determine the relative weights of the evaluation criteria and an axiomatic design (AD)-based fuzzy group decision-making approach is applied to rank the green suppliers. Finally, a case study is given to demonstrate the potential of the methodology.     

Multi-criteria outranking approach with hesitant fuzzy sets

As a generalization of fuzzy sets, hesitant fuzzy sets constrain the membership degree of an element to be a set of possible values between zero and one. Those sets are considered useful in handling decision problems defined under uncertainties where decision-makers hesitate among several values before expressing their preferences. Motivated by the idea of traditional ELECTRE methods, the dominance relations and the opposition relations for hesitant fuzzy sets are introduced in this paper. In addition, several desirable properties are studied. Then, a novel outranking relation is developed, based on systematic comparison of assessments given to alternatives for each criterion. An outranking approach for multi-criteria decision-making problems with hesitant fuzzy sets, similar to ELECTRE III, is proposed for ranking alternatives. Finally, an example is given to verify the developed approach and demonstrate its validity and feasibility.     

A methodology for augmenting sparse pairwise comparison matrices in AHP: applications to energy systems

Multiple-attribute decision making (MADM) techniques can be used to provide a systematic approach to selection problems in energy engineering and management. They may be used for selecting the best technologies or policies based on environmental, technical, and socio-economic criteria. Among the many available MADM techniques, the analytic hierarchy process (AHP) has become one of the most widely used due to its effective hierarchical decomposition of complex problems. However, AHP may be tedious due to the large number of pairwise comparisons needed in large problems. Furthermore, in many cases, relevant information may also be available for determining criteria weights based on past decisions that have proven satisfactory in retrospect. Thus, we propose a simple methodology for augmenting sparse pairwise comparisons in AHP through a non-linear programming model that extracts a set of consistent weights from a priori ranking of a subset of alternatives. Two case studies on the ranking of bioethanol feedstocks and of CO₂ storage sites are then shown to illustrate this technique.     

Influence of market orientation on performance: the moderating roles of customer participation breadth and depth in new product development

ABSTRACT

With a greater number of B2B firms integrating customers into the new product development (NPD) process, how to utilize customer involvement in NPD is an important decision because it may be a double-edged sword carrying both bright and dark sides. Utilizing a sample of 193 B2B firms across various industries, we validate previous research that suggests market orientation positively influences NPD performance and subsequently examine how this relationship may either be enhanced or diminished contingent upon how customers are utilized in the NPD process. The results show that the market orientation–NPD performance relationship is enhanced by having customers participate in a greater number of activities throughout NPD (customer participation breadth) and diminished when customers are involved at deeper levels (customer participation depth). This research suggests that the exact involvement of customers is a critical decision and has clear implications for the dialogues about customer involvement and management of customer relationships.     

An integrated multi-objective decision making process for the performance evaluation of the vendors

The objective of the study is to select the best performing supplier among the group according to the prioritisation of performance criterion through the application of techniques like MISM (modified interpretive structural modelling), MICMAC (impact matrix cross-reference multiplication applied to a classification), and AHP (analytical hierarchy process). To understand the interaction between the factors and to prioritise them, MISM technique has been applied by using which weights have been calculated for the performance factors and establishing a contextual relationship between the available factors and then ranking of the factors is done based on the results obtained. In the MICMAC analysis, performance criteria are classified into four clusters depending upon their driving power and dependence power. This helps to find out which criteria are influencing the supplier selection process. AHP is used to rank the supplier to find the best one from the group of suppliers. After ranking the suppliers, sensitivity analysis has been applied to determine the most critical criteria i.e. how sensitive is the ranking of the alternative to the change in weights of the criterion or the alternatives. A study was done in an automotive component manufacturing industry in the southern part of India. Finally, validation of the model is performed by the sensitivity analysis.     

基于模糊评价方法的新产品开发过程可靠性度量

针对新产品开发（new product development,NPD）过程难以获得所需的可靠性数据的问题,利用模糊打分法获取所需的可靠性数据。基于IDEF0（Integrated Definition for Function Modeling）建模的基础上,以模糊评价法为工具,构造了基于专家经验的模糊影响矩阵,以“输出”的质量作为过程的可靠性,在此基础上对新产品开发过程的可靠性作出评价。仿真结果表明本文提出的方法不仅可以有效地对过程可靠性作出评价,可以从定量的角度确定影响新产品开发过程可靠性的关键因素。      

Agricultural farming planning and water resources management under fuzzy uncertainty

In this study, a rank-based fuzzy optimization (RBFO) approach was provided for supporting agricultural farming planning under complex uncertainties. RBFO was built by linking feasibility-degree-based fuzzy programming with fuzzy ranking. First, the model was solved under different levels of violation risks to environmental or capacity constraints, leading to a group of cost-effective solutions; then, the ranking technique was used to help identify the most desirable solution from different alternatives, based on the trade-off analysis between the system benefit and risk. A farm planning case with water resources management consideration was used to demonstrate the applicability of RBFO. The study results indicate that the provided systems analysis approach could help decision makers to gain a deep insight into the complex interrelationships among agricultural economic development, pollution control and water resources conservation in a farm planning system, and to seek cost-effective production patterns with favourable deliberation of various factors.