基于QFD的物流运输服务质量改进

基于QFD方法,在对物流运输流程及运输质量分析的基础上,从众多的顾客质量需求要素中,运用层次分析法确定物流运输服务关键质量需求,然后针对顾客的关键质量需求提出相应的改进措施,最后基于关键顾客需求与对应措施间关系,构建了物流运输服务质量屋,为物流企业提高运输服务质量、增强企业竞争力提供了一种理论方法.     

从VA/VE到QFD与魅力质量——VA/VE的二元新视野

分析了VA/VE(价值工程与价值分析)的历史与发展,到QFD(质量功能展开)和新近提出的"魅力质量",对三者的理论框架作了介绍并综述了三者的区别与联系。随着顾客需求的不断演变,我们将看到先代理论的不足,更贴近顾客、市场的新理论将会得到更大发展与应用。     

提高产品设计质量的质量功能展开法(QFD法)

质量功能展开(QFD)是现代质量工程的核心技术之一。本文介绍了该方法的基本内容 ,并基于质量屋的原理 ,将顾客的要求展开到递阶层次设计结构中去 ,利用AHP法确定相对重要性排序 ,从而把顾客的要求始终体现于设计过程 ,并用实例说明其展开过程     

QFD在连锁超市配送服务质量保证中的应用研究

以A连锁超市为研究对象,识别配送服务质量需求,利用QFD技术将配送质量需求向配送技术指标进行映射。结果表明,"配送车辆状态良好T1"及"配送管理软件完善T3"为关键质量技术指标;再将配送技术指标向技术保证措施进行映射,结果表明,该连锁超市配送中心需合理车辆调度、外租冷藏车辆以实现门店配送服务质量提升。     

基于QFD方法的服务型制造企业服务质量改进研究

构建基于QFD方法的服务型制造企业服务质量改进研究模型,通过SPSS软件,对实例Y公司顾客需求的权重进行主成分分析,在此基础上运用灰色理论和模糊数学相结合的灰色模糊方法对Y公司服务质量进行评价,然后结合测评结果运用QFD方法,找到Y公司应该着力加强的服务措施。研究结果表明,权重分数较高的服务措施要素是进行服务补救、信息系统、员工素质、办事效率和培训,即要Y公司满足客户质量需求必须关注的要素,这些要素的好坏,直接决定了企业客户需求是否得到了满足。这类研究方法,对类似的服务型制造企业服务质量改进的研究,同样有很大的借鉴意义。     

模糊QFD在提升港口服务质量中的应用

将质量功能展开(QFD)方法应用到提高港口服务质量中,通过构建港口服务质量屋模型,采用模糊层次分析法(FAHP)确定顾客需求权重,找出影响顾客对港口服务满意度的关键因素及存在的问题,以量化的方法决定所需要改进的关键服务措施与手段,从而为提升港口服务水平和竞争力提供有效的建议。     

基于顾客需求转换的QFD方法改进研究

在顾客需求转换中,质量功能展开(QFD)理论和方法的应用成就突出,但也暴露出许多缺陷和不足,文章针对传统QFD理论的局限性,相应提出了具体解决措施。     

模糊聚类方法在QFD中的应用——以汽车安全带为例

随着QFD应用的不断深入与发展,将模糊理论应用于QFD系统已成为QFD的重要研究方向之一。在获取顾客需求信息的基础上,重点研究模糊聚类方法在获得的顾客需求信息分类中的应用,使得所分的类别更加清晰地对应技术特性。通过把模糊聚类方法应用于汽车安全带设计开发顾客需求信息分类处理中,获得更加合理、科学的顾客需求分类,最大化地满足顾客对产品特性的需求。     

供应链环境下的质量机能展开应用研究

基于供应链环境下QFD的理论研究，从供应链上厂商集合体与终端顾客间的关系为切入点，对产品／服务组合的QFD进行了定性分析，并以手机产品的供应链为例，应用QFD进行了质量目标的设计，最后得出了在供应链竞争的环境下以产品／服务组合的QFD比单一节点的QFD更能适应市场竞争需要的结论。     

基于质量功能展开的顾客满意度研究

质量功能展开是基于顾客要求的结构化产品开发方法。把质量功能展开（Quality Function Deployment,QFD）方法引入顾客满意度研究中,建立了顾客满意度测评的质量屋模型。通过多阶段的QFD模型将总体顾客满意度逐步展开为易于顾客判断的指标,进而实施了顾客满意度指数的测评;并通过某家电企业的顾客满意度测评实例,说明了这种方法实施过程。     

基于QFD的汽车技术服务企业服务质量体系研究

本文首先介绍了基于质量功能展开(QFD)的汽车服务质量模型,并根据企业调研的客户需求和客户满意度,得出服务质量特性指标和重要度,将QFD运用到汽车技术服务企业服务质量的提升中。从该模型中找到汽车技术服务企业服务质量的薄弱环节并给出相应的提升服务质量的对策,帮助汽车技术服务企业提高服务质量。     

基于质量功能展开的顾客满意研究

把产品设计的质量功能展开(QFD)方法引入到顾客满意研究中,提出了顾客满意的质量屋模型,该模型从驱动顾客满意的产品质量功能特性角度,围绕质量屋的七大要素,给出了提升顾客满意度的基本方法,最后通过某品牌手机顾客满意评价的实例说明了这种方法的实施过程。     

用模糊层次分析法确定QFD中消费者要求权重

质量功能配置(QualityFunctionDeployment,QFD),是能在产品开发及生产的各个阶段,将顾客要求转化为合理的技术要求的整体概念。在实施QFD的过程中,确定消费者的要求权重是一个关键而不可缺少的步骤。本文将模糊一致矩阵引入层次分析中,通过建立模糊一致矩阵来确定QFD中消费者要求权重。由于模糊一致矩阵更符合人们在决策过程中的心理特性,因此,它能提高确定消费者的要求权重的准确性。最后,用一个实例阐述了这种方法在QFD中确定消费者的要求权重中的应用。     

A case study on the application of Fuzzy QFD in TRIZ for service quality improvement

The improvement of service quality so as to enhance customer satisfaction has been widely mentioned over the past few decades. However, a creative and systematic way of achieving higher customer satisfaction in terms of service quality is rarely discussed. Recently, TRIZ, a Russian acronym which means “Theory of Inventive Problem Solving,” has been proven to be a well-structured and innovative way to solve problems in both technical and non-technical areas. In this study, a systematic model based on the TRIZ methodology is proposed to generate creative solutions for service quality improvement. This is done by examining first the determinants of service quality based on a comprehensive qualitative study in the electronic commerce sector. Then the correlation between the imprecise requirements from customers and the determinants of service quality is analyzed with Fuzzy Quality Function Deployment (QFD) in order to identify the critical determinants relating to customer satisfaction. After which, the corresponding TRIZ engineering parameters can be effectively applied in the TRIZ contradiction matrix to identify the inventive principles. A case study is illustrated to demonstrate the effectiveness of our approach in an e-commerce company, and its results are presented to show the applicability of the TRIZ methodology in the e-service sector.     

Multi-layer quality function deployment (QFD) approach for improving the compromised quality satisfaction under the agency problem: A 3D QFD design for the asset selection problem in the shipping industry

The aim of this paper is to improve the quality function deployment (QFD) method by utilizing requirements of both the major customer and the service provider. The QFD method was first applied to the shipbuilding industry and the main goal of the method is to improve the production processes by using customer requirements in connection with the related technical measures of the product. However, one of the critical criticisms of the QFD is based on the lack of proper budget assessment and the satisfaction of the producer (or service provider). The multi-layer QFD design is proposed to collect responses from both customer and the service provider so as to ensure satisfaction of all parties including financial feasibility of the intended improvements. Hence, the agency problem between parties will be eliminated.     

Determination of an optimal set of design requirements using house of quality

Quality Function Deployment (QFD) has been used to translate customer needs and wants into technical design requirements in order to increase customer satisfaction. QFD utilizes the house of quality (HOQ), which is a matrix providing a conceptual map for the design process, as a construct for understanding Customer Requirements (CRs) and establishing priorities of Design Requirements (DRs) to satisfy them. Some methodological issues occurring in the conventional HOQ are discussed, and then a new integrative decision model for selecting an optimal set of DRs is presented using a modified HOQ model. The modified HOQ prioritization procedure employs a multi-attribute decision method for assigning relationship ratings between CRs and DRs instead of a conventional relationship rating scale, such as 1–3–9. The proposed decision model has been applied to an indoor air quality improvement problem as an illustrative example.     

A fuzzy group decision-making approach in quality function deployment

Quality function deployment (QFD) is comprised of two major group decision-making processes. One is to collect the customer requirements from a group of customers, whereas the other is to determine the relationship between customer requirements and technical measures by a cross-functional team. Generally, different and/or even subjective opinions are quite often in a group decision-making process due to the limitations of experience and impreciseness. Obviously, the importance of each customer requirement and the relationship between customer requirements and technical measures are determined by a group of people with imprecision and vagueness. Under such circumstances, a fuzzy group decision-making approach can be applied in QFD to deal with a group decision-making process when the information is imprecise and fuzzy. Moreover, an example is provided as well as the computational steps to show this fuzzy group decision-making approach can be effectively used in QFD to make decisions with imprecision and vagueness.     

A combination of QFD and imprecise DEA with enhanced Russell graph measure: A case study in healthcare

Quality function deployment (QFD) is a proven tool for process and product development, which translates the voice of customer (VoC) into engineering characteristics (EC), and prioritizes the ECs, in terms of customer's requirements. Traditionally, QFD rates the design requirements (DRs) with respect to customer needs, and aggregates the ratings to get relative importance scores of DRs. An increasing number of studies stress on the need to incorporate additional factors, such as cost and environmental impact, while calculating the relative importance of DRs. However, there is a paucity of methodologies for deriving the relative importance of DRs when several additional factors are considered. Ramanathan and Yunfeng [43] proved that the relative importance values computed by data envelopment analysis (DEA) coincide with traditional QFD calculations when only the ratings of DRs with respect to customer needs are considered, and only one additional factor, namely cost, is considered. Also, Kamvysi et al. [27] discussed the combination of QFD with analytic hierarchy process–analytic network process (AHP–ANP) and DEAHP–DEANP methodologies to prioritize selection criteria in a service context. The objective of this paper is to propose a QFD–imprecise enhanced Russell graph measure (QFD–IERGM) for incorporating the criteria such as cost of services and implementation easiness in QFD. Proposed model is applied in an Iranian hospital.