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A distance-based methodology for increased extraction of information from the roof matrices in QFD studies

机译:在QFD研究中基于距离的方法来增加从屋顶矩阵中提取信息的方法

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摘要

Quality Function Deployment (QFD) is a process in which customer needs are operationalised into deliverable Technical Characteristics (TCs) at the design stage. A system of matrices known as the House of Quality (HOQ) works collectively to produce Final Weightings (FWs) for TCs, enabling prioritisation and focusing design activity. In prioritising TCs, QFD practitioners often fail to fully integrate the diverse information within the HOQ. In this article, we address the inclusion of 'Roof Matrix Correlations' (RMCs). We show that, while other heuristics have been developed to integrate RMCs, they each have limitations and only result in changes to the FW values. We present a methodology based on the Manhattan Distance Measure (MDM) that integrates RMC data into the FWs, but also measures the overall nature and level of intercorrelation within the matrix. This facilitates a more efficient selection of TCs because the MDM provides a consistent informational basis for substituting negatively correlated TCs with better alternatives, and reducing duplication of effort in cases of highly positively correlated TCs. Application of the method is illustrated through re-analysis of a well-known, published QFD example. Our approach can help practitioners to avoiding duplicating effort or to address contradictions between TCs in a timely fashion.
机译:质量功能部署(QFD)是一个过程,在该过程中,客户需求在设计阶段就被转化为可交付的技术特征(TC)。质量体系(HOQ)组成的矩阵系统共同为TC产生最终权重(FW),从而可以确定优先级并集中设计活动。在对TC进行优先级排序时,QFD从业人员常常无法将HOQ中的各种信息完全整合在一起。在本文中,我们解决了“屋顶矩阵相关性”(RoC Matrix Correlations,RMC)的问题。我们表明,尽管开发了其他启发式方法来集成RMC,但它们各自都有局限性,只会导致FW值发生变化。我们提出了一种基于曼哈顿距离测量(MDM)的方法,该方法将RMC数据集成到FW中,而且还测量了矩阵内互相关的整体性质和水平。这有助于更有效地选择TC,因为MDM为用更好的替代方法替代负相关的TC提供了一致的信息基础,并在高度正相关的TC的情况下减少了重复工作。通过重新分析一个已公开的著名QFD示例,说明了该方法的应用。我们的方法可以帮助从业者避免重复工作或及时解决TC之间的矛盾。

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