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工程设计学报
Chinese Journal of Engineering Design  2013, Vol. 20 Issue (2): 97-101    DOI:
    
The determination of the optimal clustering of customer demands for product family
 YANG  Qin, TANG  Wei
School of Machinery & Automobile Engineering， Hefei University of Technology， Hefei 230009， China
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Abstract  Under the environment of mass customization， to guide the planning of product families， a generalized clustering model of customers needs was established. Considering the relationship among attribute values， the information about customers needs was classified into graded type and equal type. Directing at current researches neglecting of the equal type of the information about customers needs， the fuzzy clustering algorithm was improved for customers needs clustering， which included both types of the information. This algorithm strengthened the ability of processing information. To realize the reasonable planning of product family， considering the satisfaction of customers and the cost of companies， a feasibility index was presented to determine the best customer needs clustering， which satisfied the customer demands and guarantees the enterprises loose capital chain. A case study was used to illustrate the application of this method.

Key words： customer demand      fuzzy clustering      feasibility index      optimal clustering     
Published: 28 April 2013
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YANG Qin
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Cite this article:

YANG Qin, TANG Wei. The determination of the optimal clustering of customer demands for product family. Chinese Journal of Engineering Design, 2013, 20(2): 97-101.

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https://www.zjujournals.com/gcsjxb/     OR     https://www.zjujournals.com/gcsjxb/Y2013/V20/I2/97


面向产品族的客户需求最佳聚类确定方法

以大规模定制为前提，为实现客户需求指导产品族规划的目的，建立了客户需求广义聚类模型．根据客户需求信息是否存在层次等级关系将其划分为递阶型和等价型，针对目前对递阶型客户需求聚类研究不能充分利用需求信息的问题，提出了基于模糊集的混合型客户需求聚类算法，增强了处理需求信息的能力．为实现产品族的合理规划，综合客户满意度和企业成本理想度建立可行性指标，提出了基于可行性确定客户需求最佳聚类的方法，并以最佳聚类方案指导产品族规划，在满足客户需求的同时保证了企业宽松的资金链．最后结合实例说明了该方法的实用性．

关键词： 客户需求,  模糊聚类,  可行性指标,  最佳聚类 
[1] CHENG Xian-fu, ZHU Jin, ZHOU Er-min. Research of the customer requirement model for product family based on conjoint analysis and fuzzy clustering[J]. Chinese Journal of Engineering Design, 2017, 24(1): 8-17,26.