基于E/HOQ/TRIZ 的人机产品创新方法研究

为了快速准确地进行设计阶段的人机产品创新,开发了E/HOQ/TRIZ 集成模型并 描述了具体步骤,提出了基于人体工程学(E)的人机用户需求三维分类的需求获取方式;通过质 量屋(HOQ)确立人机设计关键问题与关键人机设计区域;利用发明问题解决理论(TRIZ)分析人 机设计关键问题中的冲突类型,借助TRIZ 发明原理消除冲突。E/HOQ/TRIZ 集成模型有效弥补 了单一设计理论与方法的局限性,并发挥三种理论与方法的优势,实现人机产品创新设计。通 过人机洗浴设施创新设计,论证了所提出E/HOQ/TRIZ 集成模型与方法的可行性。     

Application of a new combined intuitionistic fuzzy MCDM approach based on axiomatic design methodology for the supplier selection problem

Evaluating and selecting a suitable supplier is a complex problem which involves a number of different criteria. In literature, there are various multi-criteria decision making (MCDM) methods available with their own characteristic features. The focus of this study is intuitionistic fuzzy (IF) MCDM methods which have attracted much attention from academics and practitioners in recent years. IF sets are widely used to tackle imprecise and uncertain decision information in decision making due to their capability of accommodating the hesitation in human decision processes. This study proposes a new integrated methodology that is used for the first time in the literature. This approach consists of intuitionistic fuzzy analytic hierarchy process (IFAHP), an MCDM technique, for determining the weights of supplier evaluation criteria, and the concept of intuitionistic fuzzy axiomatic design (IFAD) principles for ranking competing supplier alternatives with respect to their overall performance. Decision makers’ assessments and opinions are extended to the IF environment in this approach and furthermore, the group decision making (GDM) approach is utilized in order to overcome uncertainties and vagueness, minimize the partiality of decision process and to avoid bias. This study contributes to supplier selection and IF sets literature by providing a combined framework based on IFAHP and IFAD methodology for the first time. To assess the validity of the proposed integrated IF MCDM approach, a case study from Turkey is provided. This study can be useful to researchers in better understanding the supplier selection problem theoretically, as well as to organizations in designing better satisfying supplier evaluation systems.     

An integrated approach for rating engineering characteristics’ final importance in product-service system development

Product-service system (PSS) approach has emerged as a competitive strategy to impel manufacturers to offer a set of product and services as a whole. A three-domain PSS conceptual design framework based on quality function deployment (QFD) is proposed in this research. QFD is a widely used design tool considering customer requirements (CRs). Since both product and services influence satisfaction of customer, they should be designed simultaneously. Identification of the critical parameters in these domains plays an important role. Engineering characteristics (ECs) in the functional domain include product-related ECs (P-ECs) and service-related ECs (S-ECs). ECs are identified by translating customer requirements (CRs) in the customer domain. Rating ECs’ importance has a great impact on achieving an optimal PSS planning. The rating problem should consider not only the requirements of customer, but also the requirements of manufacturer. From the requirements of customer, the analytic network process (ANP) approach is integrated in QFD to determine the initial importance weights of ECs considering the complex dependency relationships between and within CRs, P-ECs and S-ECs. In order to deal with the vagueness, uncertainty and diversity in decision-making, the fuzzy set theory and group decision-making technique are used in the super-matrix approach of ANP. From the requirements of manufacturer, the data envelopment analysis (DEA) approach is applied to adjust the initial weights of ECs taking into account business competition and implementation difficulty. A case study is carried out to demonstrate the effectiveness of the developed integrated approach for prioritizing ECs in PSS conceptual design.     

An integrated approach to machine selection problem using fuzzy SMART-fuzzy weighted axiomatic design

In respond to new market requirements and competitive positioning of manufacturing companies selecting optimal machines that are consistent with manufacturing goals is of crucial importance. As it involves multiple conflicting criteria and inherent ambiguity and vagueness, election of a suitable machine can be regarded as a fuzzy multi-criteria decision making problem. In this study, for the first time in the literature, an integrated approach consisting of fuzzy simple multiattribute rating technique (SMART) approach and fuzzy weighted axiomatic design (FWAD) approach is proposed to determining the optimal continuous fluid bed tea dryer for a privately owned tea plant operating in Turkey. The weights of the evaluation criteria are calculated via fuzzy SMART and then FWAD is utilized to rank competing machine alternatives in terms of their overall performance. In the FWAD application phase, five experts have determined functional requirements (FRs) and have rated alternatives. Therefore, individual fuzzy opinions were required to be aggregated in order to set up a group consensus. A group decision analysis, referred to as the least squares distance method is used to aggregating the ratings of FRs and alternatives. It is concluded that the proposed hybrid methodology is a robust decision support tool for ranking machine alternatives under fuzzy environment and furthermore, it can be exploited for other fuzzy decision making problems, as well.     

基于足部数字化模型的拇外翻矫形器定制设计

为了提高矫形器快速定制的精准性与匹配性,建立了一种基于足部数字化模型的 拇外翻矫形器定制设计与评价模型以及具体方法流程。利用人机工程学用户需求三维分类与访 谈法获取拇外翻患者用户需求,通过层次分析法确立用户需求优先度;利用 TRIZ 冲突解决理 论获取矫形器创新设计方向;借助 3D 扫描技术得到足部点云模型,通过三阶段式数据处理与 偏差分析确保足部数字化模型的精准性。构建基于足部数字化模型的拇外翻矫形器基础模型, 并结合创新设计方向产生矫形器设计方案;通过偏差平均值与标准差评价设计方案匹配度,结 合方案可视化评价,确保最终设计方案的精准性。最后,通过拇外翻矫形器定制设计实例论证 了所建立模型与具体方法流程的可行性。     

Customer-driven product design and evaluation method for collaborative design environments

Product concept generation and evaluation in a product development environment has been identified as the two major activities needed for obtaining an optimal design scheme. Product conceptual design is of critical importance in design through customer involvement for the systematic and simultaneous consideration on the impact of design decisions on manufacturing and assembly leads to repeated and excessive changes in design and processes. This paper introduces a novel knowledge support approach for the organization and ranking of design feature knowledge towards an integrated product model that incorporates a feature-based representation scheme targeted to evaluate the impact of design on subsequent activities in the conceptual design phase, taking into account the presence of design information and user preferences. An uncertain linguistic multi-attribute decision-making evaluation model is proposed and discussed for obtaining an optimal design scheme during the evaluation and selection of product design alternatives in conceptual design. The focus of this paper is on the development of a knowledge-intensive support design scheme and a comprehensive systematic fuzzy evaluation methodology for product conceptual design generation, evaluation, and selection. A case study and the corresponding scenario of knowledge support for design alternatives generation, evaluation and selection are provided for illustration.     

An integrated QFD framework with multiple formatted and incomplete preferences: A sustainable supply chain application

Merging sustainable development with the business, and taking goals into account from its three dimensions (i.e., economic, environmental and social) which are derived from customer and stakeholder requirements have been a potential source of competitive differentiation for firms. Academic and corporate interest in sustainable supply chain (SSC) management has also risen considerably in recent years. This paper examines the components and elements of SSC management and how they serve as a foundation for an evaluation framework. By using quality function deployment (QFD) as a product/system planning and improvement tool, an effective SSC structure can be obtained. QFD uses a matrix called the “House of Quality” (HoQ), and constructing the HoQ is a critical step in the application of QFD as it translates customer requirements into engineering characteristics. However, participants of HoQ construction sessions tend to provide information about their individual judgments in multiple formats such as numerically or linguistically depending on their different knowledge, experience, culture and circumstance. Furthermore, they can generate incomplete preferences which are challenging to assess in a consistent way. Therefore, the objective of this study is to apply an extended QFD methodology in SSC by introducing a new group decision making (GDM) approach that takes multiple preference formats and incomplete information into account and fusions different formats of expressions into one uniform group decision by means of the fuzzy set theory. To assess the validity of the proposed approach, a case study conducted at HAVI Logistics-Turkey is also presented in the paper.     

A combined fuzzy AHP-simulation approach to CAD software selection

In this paper, a combined approach, where the fuzzy analytic hierarchy process (AHP) and simulation come together, is presented to select the best computer-aided design (CAD) software out of the available options in the market. The fuzzy AHP is used due to the vagueness and uncertainty of the judgements of a decision maker(s), because the crisp pair-wise comparison in the conventional AHP seems to be insufficient and imprecise to capture the right judgements of the decision maker(s). In this study, first the fuzzy AHP is used to reduce a possible number of alternatives for the CAD system to an acceptable level for further study, simulation analysis. Secondly, a simulation generator as an integrated part of the fuzzy AHP is used to try the remaining alternatives, on the generated model of a real-life product organisation in which the final alternative will be used. The results of simulation experiments are obtained, and then evaluated to reach to the ultimate CAD alternative.     

区间值模糊随机多准则决策方法

针对不完全信息的区间值模糊随机多准则决策问题,提出了两种求解方法。第一种方法利用离差最大化构建区间参数线性规划,通过区间数运算法则和定位规划求得最优准则权重向量、状态集结值区间决策矩阵与期望值区间决策矩阵,根据决策者风险偏好水平得到各方案的期望集结值从而确定排序。第二种方法将区间值模糊数决策矩阵转化为直觉模糊数决策矩阵,利用不完全的准则权重,通过规划模型求解,获取各方案在各自然状态下的加权记分函数值与加权精确函数值的区间,利用不完全的状态概率,得到各方案的记分函数期望值与精确函数期望值的区间,根据决策者风险偏好水平,求得各方案的记分函数与精确函数的期望集结值,进而确定方案的排序结果。算例分析验证了两种方法的有效性和可行性。     

Logistics tool selection with two-phase fuzzy multi criteria decision making: A case study for personal digital assistant selection

Efficient logistics and supply chain management are enabled through the use of efficient information technologies (IT). The mobile logistics tools represent the IT interface in the supply chain. This paper aims to aid decision makers to identify the most appropriate mobile logistics tools and to achieve this aim, several evaluation criteria are identified to evaluate logistics tools, and a fuzzy axiomatic design (FAD) based group decision-making method is adopted to perform the evaluation in two phases. In the first phase of pre-assessment, alternatives that cannot meet basic requirements and the defined threshold are eliminated. In the second phase of selection, the remaining alternatives are more meticulously evaluated. Criteria weights are determined using fuzzy analytic hierarchy process (AHP) and another fuzzy multi-criteria decision-making (MCDM) technique, namely fuzzy technique for order preference by similarity to ideal solution (TOPSIS), is applied in the second phase to compare the outcome of FAD. A case study is provided in order to demonstrate the potential of the proposed methodology. Personal digital assistants (PDAs) with integrated barcode scanner that are available in the Turkish market are evaluated.     

基于QFD/TRIZ/FUZZY集成技术的微摩擦测试仪力传感器设计

基于QFD/TRIZ/FUZZY集成技术,建立了用户需求和设计需求的关系.利用产品创新设计方法解决设计中的技术矛盾,得到创新问题的最优原理解.研究MEMS器件微摩擦测试仪力传感器的质量屋,选取材料强度和材料变形作为创新设计的主要技术矛盾,按照TRIZ方法给出解决冲突的原理解集合,应用模糊层次分析法对各原理解进行评价,得到最优设计方案,验证了该集成方法的可行性.     

Fuzzy group decision-making for multi-format and multi-granularity linguistic judgments in quality function deployment

As a customer-driven tool, quality function deployment (QFD) is widely used in product planning or improvement to achieve higher product performance and customer satisfaction. QFD uses a matrix called the house of quality (HoQ) to translate customer requirements (CRs) into engineering characteristics (ECs). Constructing the HoQ, which includes determining the importance weights of CRs, the correlation matrix among ECs and the relationship matrix between CRs and ECs, is an important issue in the application of QFD. However, decision-makers (DMs) participating the construction of HoQ tend to give their individual judgments in multi-format or multi-granularity depending on their different knowledge, experience, culture and circumstance. Furthermore, these judgments are more difficult to assess with the precise quantitative forms due to the vagueness and uncertainty existed in the early stage of new product development. In this paper, a group decision-making approach incorporating with two optimization models (i.e. logarithmic least squares model and weighted least squares model) is proposed to aggregate these multi-format and multi-granularity linguistic judgments. Fuzzy set theory is utilized to address the uncertainty in the decision-making process. The proposed method is illustrated with a real-world case of horizontal directional drilling machine. The application indicates that the group decision-making method may be a promising tool for constructing the HoQ.     

Fuzzy MCDM approach for selecting the best environment-watershed plan

In the real word, the decision-making problems are very vague and uncertain in a number of ways. Most of the criteria have interdependent and interactive features, so they cannot be evaluated by conventional measure method. Such as the feasibility, thus, to approximate the human subjective evaluation process, it would be more suitable to apply a fuzzy method in the environment-watershed plan topic. This paper describes the design of a fuzzy decision support system in multi-criteria analysis approach for selecting the best plan alternatives or strategies in environment watershed. The fuzzy analytic hierarchy process (FAHP) method is used to determine the preference weightings of criteria for decision makers by subjective perception (natural language). A questionnaire was used to find out from three related groups comprising 15 experts, including 5 from the university of expert scholars (include Water Resources Engineering and Conservation, Landscape and Recreation, Urban Planning, Environment Engineering, Architectural Engineering, etc.), 5 from the government departments, and 5 from industry. Subjectivity and vagueness analysis is dealt with the criteria and alternatives for selection process and simulation results by using fuzzy numbers with linguistic terms. It incorporated the decision-makers’ attitude towards the preference; overall performance value of each alternative can be obtained based on the concept of fuzzy multiple-criteria decision-making (FMCDM). This research also gives an example of evaluation consisting of five alternatives, solicited from an environment-watershed plan work in Taiwan, is illustrated to demonstrate the effectiveness and usefulness of the proposed approach. The result is useful for destination planning and the sustainability of watershed tourism resources as well.     

Parting curve selection and evaluation using an extension of fuzzy MCDM approach

Parting curve selection and evaluation plays an important role in mold design. Multiple criteria decision-making (MCDM) is an effective tool for evaluating and ranking problems involving multiple criteria. In order to select suitable parting curve, several criteria need to be taken into account. Therefore, this paper proposes an extension of fuzzy MCDM approach to solve parting curve selection problem. In the proposed model, the ratings of alternatives and importance weights of criteria for parting curve selection are expressed in linguistic terms. The membership functions of the final fuzzy evaluation value in the proposed model are developed based on the linguistic expressions. To make the procedure easier and more practical, the normalized weighted ratings are defuzzified into crisp values by using a new maximizing set and minimizing set ranking approach to determine the ranking order of alternatives. An example of parting curve evaluation and selection is given. The results show that the proposed approach is very effective in selecting the optimal parting curve for the molded part. Finally, this paper compares the proposed approach with another fuzzy MCDM approach to demonstrate its advantages and applicability.     

属性权重未知picture模糊多属性决策方法及其应用

针对属性权重未知的picture模糊多属性决策问题,提出一种基于picture模糊熵和picture模糊加权对称交叉熵的多属性决策方法.首先,基于余弦函数提出一类新的picture模糊熵,并验证该熵值满足picture模糊熵的公理化定义;其次,针对标准化处理后的picture模糊决策矩阵,以picture模糊熵确定各属性权重,同时确定正、负理想方案;再次,分别计算各方案与正、负理想方案的picture模糊加权对称交叉熵,考虑决策者的主观评价倾向以模糊折中值得到各备选方案的排序结果;最后,将所提多属性决策方法应用于河南自贸试验区郑州片区创新型项目遴选,并通过对比分析验证该决策方法的有效性与合理性.     

Adaptive consensus model with multiplicative linguistic preferences based on fuzzy information granulation

An adaptive consensus model based on fuzzy information granulation (fuzzy IG) is presented for group consensus decision-making problems with multiplicative linguistic preference relations (MLPRs). Firstly, a granular representation of linguistic terms is concerned with the triangular fuzzy formation of a family of information granules over given Analytical Hierarchy Process (AHP) numerical scales. On this basis, the individual consistency and group consensus measure indices using fuzzy granulation technique are constructed, respectively. Then, the optimal cut-off points of fuzzy information granules are obtained by establishing a multi-objective optimization model together with a multi-objective particle swarm optimization (MOPSO) algorithm. A novel group consensus decision-making approach where consensus reaching process (CRP) is achieved by adaptively adjusting individual preferences through the optimization of the cut-off points is proposed. After conflict elimination, the obtained group preference gives the ranking of the alternatives. Finally, a real emergency decision-making case for liquid ammonia leak is given to illustrate the application steps of the proposed method and comparative analysis with the existing GDM methods. Comparative results demonstrate that the proposed method has some advantages in aspects of avoiding information loss or distortion and improving consensus performance.     

A neuro-fuzzy hybrid scheme for design and simulation of human machine systems

In this article, a new neuro-fuzzy hybrid approach to human workplace design and simulation is proposed. Problems related to human workplace design such as human-machine modeling, measurement and analysis, workplace layout design and planning, workplace evaluation and simulation are discussed in detail. The complex human-machine interactions in workplace design are described with human and workstation parameters within a comprehensive human-machine system model. Based on this model, procedures and algorithms for workplace design, ergonomic evaluation, and optimization are presented in an integrated framework. With a combination of individual neural and fuzzy techniques, the neuro-fuzzy hybrid scheme implements fuzzy if-then rules block for workplace design and evaluation by trainable neural network architectures. For training and test purposes, simulated assembly tasks are carried out on a self-built multiadjustable laboratory workstation with a flexible PEAK Motus motion measurement and analysis system. The trained fuzzy neural networks are capable of predicting the operator's posture and joint angles of motion associated with a range of workstation configurations. They can also be used for design/layout and adjustment of manual assembly workstations. The developed system provides a unified, intelligent computational framework for human-machine system design and simulation. In the end, case studies for workplace design and simulation are presented to validate and illustrate the developed neuro-fuzzy design scheme and system.     

Research on multi-objective decision-making under cloud platform based on quality function deployment and uncertain linguistic variables

With developments in cloud computing and big data, the term “cloud” has become a household name owing to its characteristics of smartness and connectedness. Cloud-based platforms are associated with people. However, multi-objective decision-making problem in cloud platforms has not been extensively studied. There is no consensus on the reasonable and effective implementation of the decision-making model to select the optimum design scheme in a cloud platform and its establishment to objectively evaluate its significance. In this study, to efficiently and accurately realize the optimal selection of design scheme, a fuzzy evaluation mechanism in handling the vagueness and uncertainty is established, with the advantage of quality function deployment and strength Pareto evolutionary algorithm in decision analysis. A case study is provided to validate the proposed approach in cloud platforms. To reveal the advantages of the proposed method, it was compared with other methods such as the requirement-scenario-experience evaluation framework and a rough number-based integrated method. MATLAB programming was used for this comparison and accuracy certification. The result shows that the proposed model is more efficient and dynamic and provided users with multidimensional evaluation based on open and distributed resources system.     

A quality evaluation model for the design quality of online shopping websites

Design quality of websites is known to have a positive impact on user attention. Although there are lots of papers that investigate design qualities of websites in the literature, none of them takes into account interactions among design characteristics. The main objective of this study is to evaluate the perceived design quality of websites while considering the interactions among design characteristics. For this purpose, a new approach named the quality evaluation model (QuEM), which includes fuzzy set theory, the decision-making trial and evaluation laboratory method (DEMATEL), and generalized Choquet integral techniques, is proposed. The critical design characteristics of websites are determined based on interactions among them by using DEMATEL. Then, the degrees of importance are utilized in the generalized Choquet integral to evaluate the perceived design quality of website designs. Fuzzy set theory is utilized to cope with ambiguity in the linguistic evaluation of the different design characteristics and supports the analysis of the collected data. Finally, the proposed method is applied for the evaluation of the quality of the most used shopping websites in Turkey.     

基于前景理论的信息不完全的模糊多准则决策方法

针对准则权重不完全确定且方案的准则值为梯形模糊数的多准则决策问题,提出一种基于前景理论的模糊多准则决策方法.该方法将决策者的风险心理因素引入多准则决策,根据前景理论及模糊数距离公式,定义梯形模糊数的前景价值函数,并以此构建方案综合前景值最大化的非线性规划模型,求解模型得出最优权向量,最终确定出方案的排序.最后通过实例说明了该方法的有效性和可行性.