Prioritising technical attributes in QFD under vague environment: a rough-grey relational analysis approach

This study aims at improving the effectiveness of Quality function deployment (QFD) in handling the vague, subjective and limited information. QFD has long been recognised as an efficient planning and problem-solving tool which can translate customer requirements (CRs) into the technical attributes of product or service. However, in the traditional QFD analysis, the vague and subjective information often lead to inaccurate priority. In order to solve this problem, a novel group decision approach for prioritising more rationally the technical attributes is proposed. Basically, two stages of analysis are described: the computation of CR importance and the prioritising the technical attributes with a hybrid approach based on a rough set theory (RST) and grey relational analysis (GRA). The approach integrates the strength of RST in handling vagueness with less priori information and the merit of GRA in structuring analytical framework and discovering necessary information of the data interactions. Finally, an application in industrial service design for compressor rotor is presented to demonstrate the potential of the approach.     

QFD optimization using linear physical programming

A new approach to quality function deployment (QFD) optimization is presented. The approach uses the linear physical programming (LPP) technique to maximize overall customer satisfaction in product design. QFD is a customer-focused product design method which translates customer requirements into product engineering characteristics. Because market competition is multidimensional, companies must maximize overall customer satisfaction by optimizing the design of their products. At the same time, all constraints (e.g. product development time, development cost, manufacturing cost, human resource in design and production, etc.) must be taken into consideration. LPP avoids the need to specify an importance weight for each objective in advance. This is an effective way of obtaining optimal results. Following a brief introduction to LPP in QFD, the proposed approach is described. A numerical example is given to illustrate its application and a sensitivity analysis is carried out. Using LPP in QFD optimization provides a new direction for optimizing the product design process.     

基于质量功能配置的绿色产品设计与优化

 根据绿色产品的设计特点,建立绿色产品的质量屋(house of quality,HoQ).在传统质量屋的基础上增加了环境需求,并对传统的三角形屋顶结构进行改进.分析了质量屋中环境需求的获取过程以及环境需求权重的计算方法.综合考虑了绿色产品设计过程中的顾客需求、环境需求以及成本约束,并在质量屋的基础上建立产品优化的目标函数及约束条件.最后,以吹风机设计为实例对所提出的方法进行了验证和分析.     

Fuzzy expected value modelling approach for determining target values of engineering characteristics in QFD

Quality function deployment (QFD) is a planning and problem-solving tool that is renowned for translating customer requirements into the technical attributes of a product. To deal with the imprecise elements in the development process, fuzzy set theory is incorporated into QFD methodology. A novel fuzzy expected value operator approach is proposed in this paper to model the QFD process in a fuzzy environment, and two fuzzy expected value models are established to determine the target values of engineering characteristics in handling different practical design scenarios. Analogous to stochastic programming, the underlying philosophy in the proposed approach is based on selecting the decision with maximum expected returns. Furthermore, the proposed approach considers not only the inherent fuzziness in the relationships between customer requirements and engineering characteristics, but also the correlation among engineering characteristics. These two kinds of fuzzy relationships are aggregated to give the fuzzy importance of individual engineering characteristics. Finally, an example of a quality improvement problem of a motor car design is given to demonstrate the application and performance of the proposed modelling approach.     

A fuzzy expected value-based goal programing model for product planning using quality function deployment

Product planning is one of four important processes in new product development using quality function deployment (QFD), which is a widely used customer-driven approach. In this article, a hierarchical framework for product planning using QFD is developed. To tackle the fuzziness in functional relationships between customer requirements and engineering characteristics (ECs) in product planning, the least squares method is incorporated into fuzzy regression to investigate those functional relationships, by which a more central tendency can be obtained. Furthermore, a fuzzy expected value-based goal programing model is proposed to specify target values of ECs. Different from some fuzzy product planning approaches for QFD, the proposed programing model has unambiguous interpretations. An illustrated example of a quality improvement problem of emulsification dynamite-packing machine design is given to demonstrate the application and performance of the proposed approach.     

基于PDM的纺织企业QFD系统设计

QFD方法是实现产品需求用户化的有力工具.本文以PDM为基础形成逻辑统一平台,分析并建立纺织企业质量屋,完成了系统的构成和各项功能模块的设计,开发出的QFD系统与纺织企业相适应,运行效果良好.     

QFD: The problem of comparing technical/engineering design requirements

An approach based on multiple-criteria decision aid (MCDA) methods has been introduced for the prioritization of technical/engineering design requirements during the quality function deployment (QFD) process. The proposed method allows the avoidance of the rigid procedure under which the relationship matrix coefficients are turned from an ordinal into a cardinal scale. A comparison analysis is carried out between the traditional approach and the proposed one. A numerical example is also provided so as to highlight the main differences between the two methods.     

An evaluation framework for product planning using FANP,QFD and multi-choice goal programming

Technological innovation and satisfaction of customer needs are the keys to survival and success for firms, especially in global competitive high-tech industries. Since new products are usually a source of new sales and profits, the success of new product development (NPD) is essential to maintain a competitive edge and to make a decent profit in a longer term. Therefore, how to develop products that deliver the quality and functionality customers demand while generating the desired profits becomes an important task for the manufacturers. In this paper, a framework with two phases is constructed for facilitating the selection of engineering characteristics (ECs) for product design. In the first phase, quality function deployment (QFD) is incorporated with the supermatrix approach of analytic network process (ANP) and the fuzzy set theory to calculate the priorities of ECs with the consideration of the interrelationship among factors and the impreciseness and vagueness in human judgments and information. In the second phase, multi-choice goal programming model is constructed by considering the outcome from the first phase and other additional goals, such as NPD cost and manufacturability, in the attempt to select the most suitable ECs. A case study of the product design process of backlight unit (BLU) in thin film transistor liquid crystal display (TFT-LCD) industry in Taiwan is carried out to verify the practicality of the proposed framework.     

Robot selection using an integrated approach based on quality function deployment and fuzzy regression

The decision-makers have been experiencing difficulties in determining the most suitable robot alternative due to the increase in number of robots and the diversity in their application areas. A robust decision framework for robot selection should consider multiple and conflicting criteria and the dependencies among them. This paper introduces a decision model for robot selection based on quality function deployment (QFD) and fuzzy linear regression. The proposed approach benefits from the fact that QFD focuses on delivering value by taking into account the customer requirements and then by deploying this information throughout the development process, and applies this perspective to robot selection. Fuzzy linear regression is considered as an alternative decision aid for robot selection problems where imprecise relationships among system parameters exist. An example robot selection problem is presented to illustrate the proposed decision-making approach.     

Uncovering differences and similarities among quality function deployment-based methods in Design for X: Benchmarking in different domains

The ability for a product or a service to meet customer needs and requirements efficiently before its market launch is a key-point in design and development activities. Quality Function Deployment (QFD) represents one of the most powerful design methods to achieve such a goal. This study investigates the QFD-based methods proposed in the last two decades, whose use in different ambits of Design for X (DfX) is reported to be effective. We selected most common QFD-based methods, analyzing how designers can implement and coordinate them in design activities effectively throughout their application to an identical case study.     

基于QFD和TRIZ的高龄辅助阅读产品设计策略研究

目的 消极的老化态度使高龄者产生生理、心理等多方面的负面感受。高龄辅助阅读产品能够帮助高龄者自主阅读,助力终身学习,维持新知获取。在学习中养老,来保持高龄者与社会链接。方法 在质量功能展开(QFD)的研究中,利用网络爬虫收集商品评价数据(京东商城/约30 000条,亚马逊商城/约15 000条),形成评价词汇库。再结合情景假设分析,确定高龄辅助阅读产品的顾客需求项目,并转换为设计要求项目。其次,经 KJ法分类顾客需求和设计要求,通过调查60岁以上高龄者的104份有效问卷,以计算顾客需求重要度;再由独立配点法将顾客需求重要度转换为设计要求重要度,构建产品质量屋。最后,引入创造性解决任务理论(TRIZ)的物理矛盾、技术矛盾,以及物-场模型对产品深入分析,经分离原理、发明原理、标准解系统对产品设计矛盾求解。结果 经QFD-TRIZ模型提出高龄辅助阅读产品的设计策略和实践方案。结论 整合QFD-TRIZ关联模型,围绕高龄辅助阅读产品研究分析,为未来的高龄辅助阅读产品设计提供了具体指标,拓展了QFD-TRIZ方法在高龄者产品设计研究范畴,并构建了逻辑性和系统性的设计研究模型。     

Strategic evolution of eco-products: a product life cycle planning methodology

This paper presents a methodology and a software tool to establish an eco-design concept of a product and its life cycle by assigning appropriate life cycle options to the components of the product. The product life cycle planning (LCP) methodology provides the following systematic procedures. First, the medium- or long-term production and collection plan for the product family is clarified. Next, target values for the product and its life cycle are set in the process of determination of customer-oriented specification and eco-specification. Then, eco-solution ideas to realize reasonable resource circulation are generated by using various life cycle option analysis charts. Finally, an eco-design concept which involves eco-solution ideas is evaluated for decision-making at early stages of product development. A design support tool was made for efficiently planning product life cycles by using quality function deployment and life cycle assessment data. Based on case studies, it was verified that the proposed methodology and tool are useful for developing multi-generational eco-products.     

A scheme to randomly generate surface dust points for the 3D complex variable boundary element method (CVBEM)

A scheme to randomly generate dust points on the surface of a three-dimensional (3D) object is proposed. This scheme will potentially eliminate the bias of a density of points which are approximately equally spaced on the surface, as well as eliminate possible weighting requirements for areas of higher density. This method has the potential to reduce computational effort, as fewer points might be required to define the surface area. The global trial function vector can be assigned to these dust points and then entered into the complex variable boundary element method (CVBEM) commercial code. This scheme can be applied to each piece of a system that is comprised of a connected multiple geometry. A noticeable benefit of this approach is that the same problem can be studied several times, using a new random distribution of surface points each time. The smallest error can then be determined and that run selected. The Mathematica code used to generate the scheme is attached as an appendix.     

Analysis of groundwater quality using fuzzy synthetic evaluation

This paper reports the application of fuzzy set theory for decision-making in the assessment of physico-chemical quality of groundwater for drinking purposes. Methodology based on fuzzy set theory used to express the quality of water in the imprecise environment of monitored data and prescribed limits given in a non-probabilistic sense. Fuzzy synthetic evaluation model gives the certainty levels for the acceptability of the water based on the prescribed limit of various regulatory bodies quality class and perception of the experts from the field of drinking water quality. Application of fuzzy rule based optimization model is illustrated with 42 groundwater samples collected from the 15 villages of Ateli block of southern Haryana, India. These samples were analysed for 16 different physico-chemical water quality parameters. Ten parameters were used for the quality assessment using this approach. The analysis showed that four samples were in "desirable" category with certainty level of 35-58%, 23 samples were in "acceptable" category whose certainty level ranged from 37 to 75% and remaining 15 samples were in "not acceptable" category for drinking purposes with certainty levels from 44 to 100%. This concludes that about 64% water sources were either in "desirable" or "acceptable" category for drinking purposes.     

Delamination modelling of GLARE using the extended finite element method

In this paper, an application of the Extended Finite Element Method (XFEM) for simulation of delamination in fibre metal laminates is presented. The study consider a double cantilever beam made of fibre metal laminate in which crack opening in mode I and crack propagation were studied. Comparison with the solution by standard Finite Element Method (FEM) as well as with experimental tests is provided. To the authors’ knowledge, this is the first time that XFEM is used in the fracture analysis of fibre metal laminates such as GLARE. The results indicated that XFEM could be a promising technique for the failure analysis of composite structures.     

Reliability-based design optimization of knuckle component using conservative method of moving least squares meta-models

This paper discusses reliability-based design optimization (RBDO) of an automotive knuckle component under bump and brake loading conditions. The probabilistic design problem is to minimize the weight of a knuckle component subject to stresses, deformations, and frequency constraints in order to meet the given target reliability. The initial design is generated based on an actual vehicle specification. The finite element analysis is conducted using ABAQUS, and the probabilistic optimal solutions are obtained via the moving least squares method (MLSM) in the context of approximate optimization. For the meta-modeling of inequality constraint functions, a constraint-feasible moving least squares method (CF-MLSM) is used in the present study. The method of CF-MLSM based RBDO has been shown to not only ensure constraint feasibility in a case where the meta-model-based RBDO process is employed, but also to require low expense, as compared with both conventional MLSM and non-approximate RBDO methods.     

场景理论视域下地铁列车旅客界面需求研究

目的 为了提高乘客在地铁车厢内的乘车体验,优化地铁列车旅客界面的合理性与便捷性。方法 以场景理论为基础,采用问卷调查和用户访谈等方法,收集现有地铁乘客的用户需求,提炼客观场景。运用Kano模型明确地铁旅客界面设计的用户需求权重,基于对用户需求权重的考量及QFD质量屋展开,功能需求被转化为产品特征,用以分析用户需求与产品特征之间的关系。结果 归纳了典型地铁乘车场景,构建地铁列车乘客界面的用户需求与产品特征之间的关联矩阵,并以此为基础分别从车厢布局、信号灯提示、扶握系统和导视系统四个方面,提出了地铁列车旅客界面的配置策略。结论 从场景分析的角度结合多重定量、定性分析方法,验证场景理论对挖掘地铁乘车需求具有一定指导作用,并提出地铁列车旅客界面在提升旅客乘车体验方面的初步建议。