Object - oriented databases for quality function deployment and Taguchi methods

In this paper, Object-Oriented Databases are proposed as being a new tool for Quality Function Deployment (QFD) and Taguchi Methods. Quality Function Deployment can help identify key product or process concerns with respect to customer requirements. Taguchi Methods, such as using Design of Experiments (DOE), can help identify what product or process relationships truly exist, their relative strengths and the nature of the relationship. In order to implement these two powerful quality control techniques for assuring that customer requirements are consistently met, a well organized information is required. Object-Oriented Databases are able to store, organize and manipulate both, the customer requirements and the product information for the performance of QFD and DOE.     

基于QFD理论的洗衣机界面的设计与研究

质量功能展开(QFD),即质量屋的建造,是在整合产品生命周期内对产品功能质量进行分析、展开的理论方法。综合考虑客户要求、技术要求、市场状况以及其相互间的作用关系对产品质量、功能的影响。着重阐述质量屋的生成过程。并以洗衣机为例,建立分析、评价模型,构造相关要素矩阵,形成洗衣机的设计流程以及方法。     

Cost engineering with quality function deployment

Conventional Quality Function Deployment (QFD) is technically one-sided. Prioritization of technical attributes, if carried out at all, attempts to maximize customer satisfaction without considering the costs incurred. However, product design is usually a techno-economic process, hence there is always a tradeoff between quality goals and limited budgets. Based on a prioritization method suggested by Wasserman [1], this paper integrates design costs into the QFD framework. This proposed approach enables designers to optimize product development resources towards customer satisfaction and conduct analytical investigations to facilitate decision making in product design and development.     

A fuzzy regression and optimization approach for setting target levels in software quality function deployment

With the rapid development of the software industry, improving the quality of software development has gained increasing importance. Software manufacturers have recently applied quality improvement techniques to software development to respond to the needs for software quality. Software quality function deployment (SQFD), as a technique for improving the quality of the software development process to create products responsive to customer expectations, is used to maximize customer satisfaction. This paper presents a fuzzy regression and optimization approach to determine target levels in SQFD. The inherent fuzziness of relationships in SQFD modeling justifies the use of fuzzy regression. Fuzzy regression is used to identify the functional relationships between customer requirements and technical attributes, and among technical attributes. Then, a mathematical programming model is developed to determine target levels of technical attributes using the functional relationships obtained by fuzzy regression. A search engine quality improvement problem is presented to illustrate the application of the proposed approach.     

软件质量功能展开法

质量功能展开作为对新产品开发进行质量保证的方法论在日本已被广泛应用。最近，在欧美也被相继引入，笔者们把质量功能开应用到软件开发中进行软件产品的质量保证。本文首先用质量展开的概念模型解释了质量功能展开的基本想法，其次，分析了软件质量保证的问题点；然后，介绍了软件质量功能展开法，最后，总结了软件质量功能展开法的应用效果和今后的课题。     

Business-oriented software process improvement based on CMMI using QFD

Software Process Improvement (SPI) has become the key to the survival of many software development organizations. As a follow-up of a previous paper on SPI for the CMM using Quality Function Deployment (QFD), a new SPI framework integrating QFD with the CMMI is developed. Similar to the earlier SPI framework for the CMM, the proposed SPI framework based on the CMMI using QFD aims to achieve three objectives: (1) to map process requirements, including business requirements, to the CMMI with the help of QFD; (2) to develop a method based on QFD for the integration and prioritization of requirements from multiple perspectives (groups); and (3) to be able to prioritize software process improvement actions based on process requirements.Process requirements from multiples groups of stakeholders (perspectives), including business goals, are integrated and prioritized. SPI actions are linked to these process requirements using QFD. Thus, the priorities of actions reflect the priorities of process requirements. By executing the actions with the highest priorities, the highest satisfaction level of process requirements can be achieved. One unique feature of the framework for the CMMI Continuous representation is that the priority values of these actions can be compared across PAs, even when the PAs attempt to reach different capability levels.     

基于QFD的软件质量保证模型

本文将ＱＦＤ应用到软件开发中，提出了一种软件的质量保证模型，并给出了应用实例。     

约束条件下顾客需求重要度计算方法

研究了企业在实际应用质量功能配置过程中由于资源约束条件,无法完全满足所有顾客需求重要度的问题。通过对传统的层次分析法进行改进,提出基于Monte Carlo-AHP方法的顾客需求重要性排序方法,对排序靠后的顾客需求项进行取舍以满足企业资源约束;然后采用数据包络分析（DEA）模型计算企业考虑竞争差异时的相对效率,根据相对效率与应用AHP方法计算得到的基本重要度,确定最终顾客需求重要度。最后,给出了该方法的应用实例。     

如何更好地保证软件项目的质量

软件企业更多的时候是在为客户提供服务而不是像买卖一件商品那么简单,改善客户满意度应该是一个着眼于未来的软件企业不断追求的目标。那么软件企业如何才能为用户提供高质量的产品呢?本文将从质量策略、质量管理过程、质量管理常用技术和工具、QA的工作等几个方面探讨如何更好地保证软件的质量。     

Group decision making to better respond customer needs in software development

Quality Function Deployment (QFD) is a well-known planning methodology for translating customer needs into relevant design and production requirements. The intent of applying QFD is to incorporate the voice of the customer into the various phases of the product development cycle for a new product, or a new version of an existing product. The traditional QFD structure requires individuals to express their preferences in a restricted scale without exceptions. In practice, people contributing to the process tend generally to give information about their personal preferences in many different ways, numerically or linguistically, depending on their background. Moreover, collaborative decision-making is not an emphasized issue in QFD even though it requires several people's involvement. In this study, we extend the QFD methodology by introducing a new group decision making approach that takes into account multiple preference formats and fusing different expressions into one uniform group decision by means of fuzzy set theory. An application on software development is supplied to illustrate the approach.     

Application of quality function deployment in the semiconductor industry: A case study

In quality function deployment (QFD), the voice of the customer (VOC) is the critical factor in developing and producing a product that will meet or exceed customer requirements. This study integrates quality function deployment (QFD), management techniques to optimise product-design investment, process improvement, and phase-into meet customer requirements and company goals. QFD uses systematic multi-level development and evaluation to translate customer requirements into the design of product characteristics and manufacturing processes that will satisfy the customer and minimise potential failure costs. ‘Process management’, which is one of the pivotal Six Sigma implementation criteria, is used to construct an ‘integrated product and process development’ (IPPD) model by product type to enhance the effectiveness of QFD. This model, combined with a company’s customer satisfaction strategy and QFD techniques, provides process management through built-in IPPD and appropriate changes in organisational culture. This paper presents a case study from the semiconductor industry to demonstrate the model’s applicability and suitability.     

Quality Function Deployment (QFD) processes in an integrated quality information system

A general design of an integrated total quality information system involving the Quality Function Deployment process is proposed in this paper. Data flow diagram is used to illustrate the structure of the information system. Within it, the Quality Function Deployment process is especially discussed in detail.     

A novel approach to software quality risk management

Software quality is very important in today's competitive business environment. It is a critical constraint on software projects. Software organizations’ major objectives are delivering products on time and achieving quality goals. Quality is directly dependent on software processes, which are inherently variable and uncertain, involving substantial risk. Managing quality risk is an important challenge. The conventional approach to quality risk management for ongoing software processes has two major deficiencies: static analytic models are used, and structured methodologies to enhance processes and improve quality are not systematically applied. This new practical method uses Six Sigma and Monte Carlo Simulation for ongoing quality risk management. DMAIC (Define, Measure, Analyse, Improve, Control) is systematically applied as a tactical framework to enhance the process and improve quality. Simulation predicts quality (reliability) at the expected process end and identifies and quantifies risk. DMAIC is a verified structured methodology for systematic process and quality improvements. Monte Carlo Simulation is superior to conventional risk models. These synergetic enhancements eliminate observed deficiencies. The method has been successfully proven and applied practically on real in‐house projects. Substantial savings, quality and customer satisfaction have been achieved. An application on an internal project and obtained results are presented. The method is simplistically elaborated on a published third‐party project answering key research questions from practical perspectives. This CMMI® compliant method offers important benefits including savings, quality and customer satisfaction. Copyright © 2013 John Wiley & Sons, Ltd.     

Use of ANP weighted crisp and fuzzy QFD for product development

Quality Function Deployment (QFD) is a popular planning method often used to transform customer demands/requirements into the technical characteristics of a new or improved product or service. In order to better capture (and represent) the multifarious relationships between customer requirements and technical characteristics, and the relative weights among customer requirements, in this study a hybrid analytic network process (ANP)-weighted fuzzy methodology is proposed. The goal is to synthesize renowned capabilities of ANP and fuzzy logic to better rank technical characteristics of a product (or a service) while implementing QFD. To demonstrate the viability of the proposed methodology a real-world scenario, where a new equipment to squeeze the polyethylene pipes to stop the gas flow without damaging the pipes, is developed. The ranking of technical characteristics of the product is calculated using both crisp and fuzzy weights for illustration and comparison purposes.     

Development of a strategic research plan for an academic department through the use of quality function deployment

Quality Function Deployment (QFD) is a popular approach for formalizing the process of listening to “the voice of the customer,” and assigning responsibilities to members of an organization in an effort to respond effectively to customer needs, QFD is being used by the Department of Industrial Engineering at Mississippi State University to help identify key customers for departmental research efforts, to identify and track the research needs of those customers, to fashion a comprehensive strategic plan for departmental research activities based on customer needs, to deploy various research functions and responsibilities to specific faculty members or groups, and to track research performance relative to goals. This approach appears to be an excellent means of formalizing the process of strategic research planning.     

QFD in the architecture development process

Quality function deployment ensures that the new design in an enterprise IT architecture project fully implements functional and nonfunctional requirements so that planned IT systems can support the business. In this paper, we outline an approach to designing architectures that fully support requirements, by leveraging a technique called quality function deployment. QFD is a systematic method for tying product and service design decisions directly to customer wants and needs. In the future, we plan to explore issues associated with defining and collecting architecture requirements, designing and collecting architecture requirements, designing efficient and elegant architectures, and creating architecture transition plans.     

A framework for software process deployment and evaluation

ContextSoftware Process Engineering promotes the systematic production of software by following a set of well-defined technical and management processes. A comprehensive management of these processes involves the accomplishment of a number of activities such as model design, verification, validation, deployment and evaluation. However, the deployment and evaluation activities need more research efforts in order to achieve greater automation.ObjectiveWith the aim of minimizing the required time to adapt the tools at the beginning of each new project and reducing the complexity of the construction of mechanisms for automated evaluation, the Software Process Deployment & Evaluation Framework (SPDEF) has been elaborated and is described in this paper.MethodThe proposed framework is based on the application of well-known techniques in Software Engineering, such as Model Driven Engineering and Information Integration through Linked Open Data. It comprises a systematic method for the deployment and evaluation, a number of models and relationships between models, and some software tools.ResultsAutomated deployment of the OpenUP methodology is tested through the application of the SPDEF framework and support tools to enable the automated quality assessment of software development or maintenance projects.ConclusionsMaking use of the method and the software components developed in the context of the proposed framework, the alignment between the definition of the processes and the supporting tools is improved, while the existing complexity is reduced when it comes to automating the quality evaluation of software processes.     

产品服务系统技术特征重要度确定方法研究

产品服务系统中在进行工程特征重要度确定时常采用质量功能配置方法。而质量功能配置(QFD)的传统思路忽略了专家评价信息中的模糊性和随机性可能。基于此,首先结合云模型正向云发生器来处理专家语义评价信息,将客户需求的定性表示转换为定量数据表达,并由此来求出技术特征的重要度。考虑到技术特征的竞争性,基于集对分析方法的建立技术特征的联系度矩阵,并由信息熵进行技术特征重要度的修正,进而确定技术特征的最终重要度。最后以某汽车产品服务系统技术特征重要度分析为例,验证了所提方法的有效性。     

两段式虚拟网络功能硬件加速资源部署机制

设计硬件加速机制,解决软件定义网络/网络功能虚拟化（SDN/NFV）架构中虚拟网络功能（VNF）的性能受限问题,成为当前的研究热点。在引入VNF硬件加速资源后,如何实现对加速资源的统一管理和部署,是亟待解决的问题。为此,首先提出了基于服务器端加速卡和OpenFlow交换机的VNF加速资源的统一管理架构;在此基础上,对加速资源部署问题进行建模,通过分析VNF加速资源对服务链映射的影响,提出了VNF加速资源部署策略的评价指标;最后,设计了两段式的加速资源部署算法求解该问题。实验结果表明,与只考虑节点单一属性的部署算法（SARD）和均匀部署算法（UARD）相比,所提机制能够优化部署加速资源,加速资源承载的流量和加速资源的利用率分别提升41.4%和14.5%。     

A novel method for determining the key customer requirements and innovation goals in customer collaborative product innovation

Customer collaborative production innovation (CCPI) has become a worldwide new product design trend. The essential step to implement CCPI is to clear customer requirements and innovation goals for products. Based on the integration of traditional competitive priority ratings of customer requirements method for quality function deployment and grey relational analysis, this paper proposes a novel hybrid competitive priority ratings of customer requirements method for CCPI to identify the key customer requirements and innovation goals for a product. The method takes the heterogeneity of customers into consideration and allows different types of customers to assess customer requirements in their preferred or familiar formats which reflect their uncertainty degree. The proposed hybrid competitive priority ratings of customer requirements method represents a general approach for CCPI, does not require any transformation of multiform customers’ assessments that would cause information loss or information distortion. Its potential applications in determining the key customer requirements and innovation goals for CCPI are illustrated with a case study of smart phone development.