Incorporating cost and environmental factors in quality function deployment using data envelopment analysis
Incorporating cost and environmental factors in quality function deployment using data envelopment analysis
复制标题
DOI：
10.1016/j.omega.2007.12.003
复制
发表时间：
2009-06
影响因子：
6.9
通讯作者：
R. Ramanathan;Yunfeng Jiang
中科院分区：
文献类型：
--
作者：
R. Ramanathan;Yunfeng Jiang
质量功能展开(QFD)是组织有效进行产品设计和开发的重要工具。传统上，QFD根据客户需求对设计要求(DRS)进行评级，并将评级汇总以获得DRS的相对重要性分数。越来越多的研究强调，在计算DRS的相对重要性时，需要纳入其他因素，如成本和环境影响。然而，当考虑到其他几个因素时，缺乏推导出DRS相对重要性的方法。为此，本文提出了数据包络分析(DEA)方法。证明了DEA计算的相对重要值与传统的QFD计算结果一致，当只考虑DRS对客户需求的评价时，并且只考虑一个附加因素，即成本。当需要考虑更多因素时，数据包络分析提供了一个便于QFD计算的通用框架。这些计算是用一个循序渐进的程序和插图来解释的。将所提出的QFD-DEA方法应用于一家中国公司的安全紧固件设计。尽管传统的QFD计算将评级视为基数，但DEA可以灵活地将评级视为定性变量。这一方面将在单独的一节中进行说明。
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.