QFD与航空运输服务设计

作为一个以顾客需求为基础、并将这种需求转化为不同阶段各种技术要求的系统,质量功能展开(QFD)在服务设计中起着越来越重要的作用.应用QFD,从顾客需求出发构建质量屋,并针对当前航空运输服务中的实际问题,探讨了在各个阶段对航空运输服务的全新设计.     

QFD中顾客需求重要度确定的一种方法

在质量功能配置(quality function deployment, QFD)的产品规划阶段,顾客需求最终重要度的确定对于技术特征值的确定乃至整个质量屋的优化决策以及下一阶段的配置决策有着重要的作用.文章分析了传统处理方法的不足,讨论了在质量功能配置中引入模糊集理论,在顾客需求的综合上考虑了语言值表达的多粒度多语义的情况;对于顾客需求重要度确定中卖点的确定引入熵的概念,一定程度上使得QFD中顾客需求重要度的确定更加客观、合理.     

QFD 中顾客需求重要度确定的一种方法

在质量功能配置(quality function deployment , QFD) 的产品规划阶段,顾客需求最终重要度 的确定对于技术特征值的确定乃至整个质量屋的优化决策以及下一阶段的配置决策有着重要 的作用. 文章分析了传统处理方法的不足,讨论了在质量功能配置中引入模糊集理论,在顾客 需求的综合上考虑了语言值表达的多粒度多语义的情况;对于顾客需求重要度确定中卖点的 确定引入熵的概念,一定程度上使得QFD 中顾客需求重要度的确定更加客观、合理.     

多心理账户下基于BPT的ISC优化设计

针对顾客有限理性引起的需求模糊性和动态性特征,引入行为金融于ISC(集成供应链)系统,以Friedman和Savage之谜为释例,指出了顾客的金字塔式心理账户结构,解释了因顾客需求非理性波动引致产生的诸多实证异象。以顾客满意为驱动力,基于QFD(质量功能展开)将顾客需求转化为对ISC各个环节的满意度评价,并利用模糊语言值优化了顾客对ISC各环节的需求重要度,确定了顾客满意度的自相关函数及其与ISC优化设计间的关联函数。在多心理账户条件下,基于行为证券组合理论(BPT)最终建立了一种具有机会约束属性的顾客满意度目标规划模型。     

MC 模式下基于顾客需求的产品配置优化分析

以大规模定制(MC) 模式为背景,论述了基于单个顾客的定制需求,对“理想产品”进行配 置优化的一个思路. 本文论述MC 模式的基本概念和思想、以及定制产品配置优化的含义及意 义,介绍了一种基于QFD 分析结果. 运用TOPSIS 法,提出了对顾客所需“理想产品”进行优化 配置的思路,并给出一个示例,验证“思路”的合理性.     

MC模式下基于顾客需求的产品配置优化分析

以大规模定制(MC)模式为背景,论述了基于单个顾客的定制需求,对"理想产品"进行配置优化的一个思路.本文论述MC模式的基本概念和思想、以及定制产品配置优化的含义及意义,介绍了一种基于QFD分析结果.运用TOPSIS法,提出了对顾客所需"理想产品"进行优化配置的思路,并给出一个示例,验证"思路"的合理性.     

基于模糊规划的QFD 系统参数确定方法

针对QFD 系统的内在模糊性,运用带有对称三角形模糊系数的模糊规划理论,提出了一 种确定QFD 系统参数的方法. 并通过工程特性目标值的规范化,定义产品开发总成本函数、工 程特性改进成本函数及改进成本系数等概念,建立了一个QFD 规划模型. 仿真结果表明,该模 型能够帮助开发人员在不确定的、模糊条件下有效确定关联函数及自相关函数,优化顾客需求 的满意水平,确定工程特性目标值,使新开发/ 改进的产品顾客满意度赶上或超过目标市场上 的竞争企业,并满足开发预算约束.     

风险管理理论应用于企业廉政风险防控工作中的探讨

将风险管理理论和现代质量管理方法引入反腐倡廉建设,是构建惩治和预防腐败体系的重要举措,本文就风险管理理论及其FMEA工具应用于企业廉政风险防控工作做一些探讨,以期对廉政风险防控工作能够有效推进和运行提供思路。     

顾客满意度的定量分析与应用

充分满足顾客的需求是企业生存和发展的根本,生产顾客满意的产品是企业经营的基本目标,企业产品开发活动开始于满足顾客的需要,企业只有了解顾客的需要才能开发出顾客满意的产品,只有了解顾客满意产生的背景、并对产品以及构成产品满意的各因素进行科学评价,才能把握产品调整和产品开发的方向,有效地提升企业在市场中的竞争力.     

考虑顾客感知效用的服务要素优化配置方法

针对服务设计中的服务要素优化配置问题,提出了一种考虑顾客感知效用的服务要素优化配置方法.运用质量功能展开理论中的质量屋方法确定各服务项的权重;依据确定的服务项和备选服务要素,采用调查问卷方式获得顾客群体对于各服务项的期望水平以及对各服务要素满足需求程度的评价值;然后基于失望理论刻画顾客的欣喜与失望的心理感知,并计算顾客感知效用;进一步通过建立和求解优化模型来确定服务要素配置方案.此外,以某航空公司头等舱服务设计为例,说明了方法的可行性与有效性.     

Incorporating cost and environmental factors in quality function deployment using data envelopment analysis

Quality function deployment (QFD) is an important tool available to organizations for efficient product design and development. 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. In this paper, data envelopment analysis (DEA) is suggested for the purpose. It is proved that the relative importance values computed by DEA coincide with traditional QFD calculations when only the ratings of DRs with respect to customer needs are considered, and when only one additional factor, namely cost, is considered. DEA provides a general framework facilitating QFD computations when more factors need to be considered. The calculations are explained using a step-by-step procedure and illustrations. The proposed QFD–DEA methodology is applied to the design of security fasteners for a Chinese company. Though traditional QFD calculations consider the ratings as cardinal numbers, DEA has the flexibility to treat the ratings as qualitative variables. This aspect is illustrated in a separate section.     

Coping with Group Behaviors in Uncertain Quality Function Deployment

Quality function deployment (QFD) is a planning and problem‐solving tool gaining wide acceptance for translating customer needs (CNs) into technical attributes (TAs) of a product. It is a crucial step to derive the prioritization of TAs from CNs in QFD. However, it is not so straightforward to prioritize TAs due to two types of uncertainties: human subjective perception and user variability. The main focus of this article is to propose a group decision‐making approach to uncertain QFD with an application to a flexible manufacturing system design. The proposed approach performs computations solely based on the order‐based semantics of linguistic labels to eliminate the burden of quantifying qualitative concepts in QFD. Moreover, it incorporates the importance weights of users and the concept of fuzzy majority into aggregations of individual fuzzy preference relations of different TAs in order to model the group behaviors in QFD. Finally, based on a quantifier‐guided net flow score procedure, the proposed approach derives a priority ranking with a classification of TAs into important and unimportant ones so as to provide a better decision‐support to the decision‐maker. Due to the easiness in articulating preferential information, our approach can reduce the cognitive burden of QFD planning team and give a practical convenience in the process of QFD planning.     

Fuzzy integrated QFD,FMEA framework for the selection of lean tools in a manufacturing organisation

Lean Manufacturing (LM) is a well-established system to improve performance of any manufacturing industry by eliminating wastes through globally accepted tools and techniques. Industries are trying to adapt lean principles in order to optimise the resources like people, equipment, material and schedule for being efficient in the competitive market. This paper proposes an integrated approach for selecting appropriate lean tools in reliable lean perspective to enhance these critical resources. The approach exercise a hybrid model which uses fuzzy QFD to prioritise the critical resources in relation with identified wastes and fuzzy FMEA to assess the risk associated with each sub elements to address lean implementation. For waste identification, plant layout and Value Stream Mapping are considered. The model is demonstrated based on the data collected from a manufacturing industry to illustrate the application. Significant improvements are quantified with the help of future state map and plant layout.     

Failure Modes and Effects Analysis: An Evaluation of Group versus Individual Performance

Failure modes and effects analysis (FMEA) is one of the most frequently used tools in process and product design: it is used in quality and reliability planning, and event and failure mode analysis. It has a long history of use and is a formally prescribed procedure by a number of prominent standards organizations. In addition, it's popular use has evolved as a less formal and widely interpreted tool in the area of Lean/Six Sigma (LSS) process improvement. This paper investigates one of the most important issues related to FMEA practice—the quality of individual vs. group performance in ranking failure modes. In particular, we compare FMEA rankings generated by: (i) individuals, (ii) group consensus, and (iii) non‐collaborative aggregation of group input (a synthesized group ranking). We find that groups outperform individuals and that synthetic groups perform as well as group consensus. We explain the implications of this result on the coordination of the design of products and processes amongst distributed organizations. The increasing distribution of product design efforts, both in terms of geography and different organizations, presents an opportunity to improve coordination using distributed synthetic group‐based FMEA.     

An Alternative FMEA Method for Simple and Accurate Ranking of Failure Modes

Failure modes and effects analysis (FMEA) is a methodology for prioritizing actions to mitigate the effects of failures in products and processes. Although originally used by product designers, FMEA is currently more widely used in industry in Six Sigma quality improvement efforts. Two prominent criticisms of the traditional application of FMEA are that the risk priority number (RPN) used to rank failure modes is an invalid measure according to measurement theory, and that the RPN does not weight the three decision criteria used in FMEA. Various methods have been proposed to mitigate these concerns, including many using fuzzy logic. We develop a new ranking method in this article using a data‐elicitation technique. Furthermore, we develop an efficient means of eliciting data to reduce the effort associated with the new method. Subsequently, we conduct an experimental study to evaluate that proposed method against the traditional method using RPN and against an approach using fuzzy logic.     

A Risk Analysis Model in Concurrent Engineering Product Development

Concurrent engineering has been widely accepted as a viable strategy for companies to reduce time to market and achieve overall cost savings. This article analyzes various risks and challenges in product development under the concurrent engineering environment. A three‐dimensional early warning approach for product development risk management is proposed by integrating graphical evaluation and review technique (GERT) and failure modes and effects analysis (FMEA). Simulation models are created to solve our proposed concurrent engineering product development risk management model. Solutions lead to identification of key risk controlling points. This article demonstrates the value of our approach to risk analysis as a means to monitor various risks typical in the manufacturing sector. This article has three main contributions. First, we establish a conceptual framework to classify various risks in concurrent engineering (CE) product development (PD). Second, we propose use of existing quantitative approaches for PD risk analysis purposes: GERT, FMEA, and product database management (PDM). Based on quantitative tools, we create our approach for risk management of CE PD and discuss solutions of the models. Third, we demonstrate the value of applying our approach using data from a typical Chinese motor company.     

Does applying design thinking result in better new product concepts than a traditional innovation approach? An experimental comparison study

Both practitioners and researchers have developed various approaches to support product development teams in their creative process of generating new and valuable product concepts. A key concern of all innovation approaches is to translate the needs, wants and aspirations of users and customers into product and service solutions that match the underlying needs. Many existing innovation approaches focus predominantly on the translation process itself by providing support for aggregating data and making trade-off decisions between user preferences traceable. For that reason, we label these approaches user preference-driven. In contrast, over the last two decades, design thinking (DT) has emerged as an approach that assumes knowledge of user needs information to be fuzzy and unreliable; it addresses this challenge by focusing on developing user experiences through empathic in-depth user research and iterative prototyping. Consequently, we label approaches such as DT user experience-driven. Although DT has generated particular interest among both practitioners and educators, the academic literature investigating the usefulness of DT remains scarce. To help close this gap, we study the performance implications of applying DT processes and tools in terms of new product concept creativity relative to applying a traditional innovation approach. Using an experimental design and collecting quantitative data from 53 teams and their projects, we find that teams applying DT outperform the control group that applies an alternative innovation approach, namely quality function deployment (QFD), in terms of the feasibility, relevance and specificity of concepts, but not the novelty. We discuss the implications of our findings for theory and practice.     

基于独特性需要调节作用的顾客参与研究

在有关顾客参与的研究中过于强调顾客参与对顾客满意的影响,以及企业对顾客参与结果的影响.但顾客参与的结果不仅取决于顾客外部因素,还取决于独特性需要这样的顾客内部因素.为揭示独特性需要对顾客参与过程的重要性,本文以独特性需要作为调节变量来考察它在顾客参与活动中对顾客价值创造和满意的影响.在此基础上,运用结构方程模型展开实证研究,研究结果表明,顾客参与对顾客价值的创造有显著正向影响;独特性需要对于顾客参与的价值创造结果确实存在着积极的调节作用.针对研究结论,本文提出了相应的管理对策和研究展望.     

在线B2C顾客物流服务感知及相关因素的实证研究

物流服务已成为B2C电子商务的重要组成部分,关注顾客的物流服务感知也日渐成为网络零售企业管理面临的新问题.本文分析了B2C电子商务环境下顾客物流服务感知以及与之相关的产品价值感知、商流过程感知和企业形象感知等因素及其这些因素与顾客满意度,顾客忠诚之间的相互关系,并在理论与文献研究的基础上建立了在线B2C顾客物流服务感知相关因素的假设模型.通过某中国大型在线零售商顾客的实际调研并结合结构方程模型的分析,实际数据验证了"在线B2C顾客企业形象感知对其物流服务感知具有显著的正面影响","在线B2C顾客物流服务感知对其网购满意度具有显著的正面影响"等假设.据此,本文分析认为网络零售商可选择两种实施路径以提升顾客满意度:其一,凭借其良好的企业形象将渠道控制能力自然延伸到物流服务领域,其二,参与供应商的产品质量管理甚至产品研发与上游供应商协作.