Using fuzzy non-linear regression to identify the degree of compensation among customer requirements in QFD
Using fuzzy non-linear regression to identify the degree of compensation among customer requirements in QFD
复制标题
利用模糊非线性回归识别QFD中客户需求之间的补偿程度
DOI：
10.1016/j.neucom.2014.01.053
复制
发表时间：
2014-10
期刊：
影响因子：
6
通讯作者：
Chen, Yizeng
中科院分区：
文献类型：
--
作者：
Liu, Yuanyuan;Zhou, Jian;Chen, Yizeng
质量功能展开（QFD）作为一种有效的顾客驱动方法，在产品初始设计和竞争分析过程中考虑了大量的顾客需求。这是一个传统的多属性决策问题，而客户满意度之间的权衡策略作为决策参数，对客户的整体满意度至关重要。虽然一般的权衡策略关注的重要性权重的CR，这是指定的各种方法，他们忽略了补偿程度的影响，其中。本文将顾客满意度的补偿度表示为一个对称三角模糊数，并将其嵌入到QFD中，建立了一个基于最小模糊数准则的模糊非线性回归模型来识别顾客满意度，最后通过一个实例说明了该建模方法的应用和性能。从实验结果可以证实，客户的整体满意度，以及产品的优先级的影响程度的补偿客户之间。同时，针对实例产品，证实了传统的加权和法所得到的总体顾客满意度是低估的。
As an effective customer-driven approach, the quality function deployment (QFD) takes numbers of customer requirements (CRs) into account in the process of the initial product design and the competitive analysis. It is a traditional multi-attribute decision making problem, and the trade-off strategy among CRs which is interpreted as decision parameters, is crucial for resulting the overall customer satisfaction. Although the general trade-off strategies concern about the importance weights of CRs, which are specified with a variety of methods, they ignore the influence of the degree of compensation among them. In this paper, we embed the degree of compensation among CRs into QFD, which is expressed as a symmetric triangular fuzzy number, and develop a fuzzy non-linear regression model using the minimum fuzziness criterion to identify it. Furthermore, an illustrative example is provided to demonstrate the application and the performance of the modeling approach. It can be verified from the experimental results that the overall customer satisfaction as well as the prioritization of products are affected by the degree of compensation among CRs. Meanwhile, against to the products in example, the overall customer satisfaction obtained with the traditional weighted-sum method is confirmed to be underestimated.
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DOI：
10.1002/9780470172261
发表时间：
1999-12
期刊：
--
影响因子：
--
作者：
M. Gen;Runwei Cheng
通讯作者：
M. Gen;Runwei Cheng
影响因子：
--
作者：
ZADEH, LA
通讯作者：
ZADEH, LA
影响因子：
1.8
作者：
Qin Wang;Xiaoguang Yang;Jianzhon Zhang
通讯作者：
Qin Wang;Xiaoguang Yang;Jianzhon Zhang
影响因子：
0.5
作者：
Qin Wang
通讯作者：
Qin Wang
影响因子：
6.4
作者：
Kim, KJ;Moskowitz, H;Koksalan, M
通讯作者：
Koksalan, M