Study on the Structured Processing of Unstructured Personalized Customer Requirement for Mass Customization

Qinglie Wu; Yu Guo

doi:10.3969/j.issn.1000-0801.2013.12.002

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Study on the Structured Processing of Unstructured Personalized Customer Requirement for Mass Customization

research and development | 更新时间：2024-06-05

- Study on the Structured Processing of Unstructured Personalized Customer Requirement for Mass Customization
- Telecommunications Science Vol. 29, Issue 12, Pages: 9-15(2013)
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- DOI：10.3969/j.issn.1000-0801.2013.12.002
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- Published Online：2013-12，
  
  Published：20 December 2013
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Qinglie Wu, Yu Guo. Study on the Structured Processing of Unstructured Personalized Customer Requirement for Mass Customization[J]. Telecommunications science, 2013, 29(12): 9-15.
DOI：

Qinglie Wu, Yu Guo. Study on the Structured Processing of Unstructured Personalized Customer Requirement for Mass Customization[J]. Telecommunications science, 2013, 29(12): 9-15. DOI： 10.3969/j.issn.1000-0801.2013.12.002.

摘要

大规模定制客户个性化服务需求往往具有非结构化特征，准确获取并分析真实客户需求是大规模定制成功实施的关键。首先讨论大规模定制客户非结构个性化需求的内涵和判定方法，针对非结构个性化需求特点构建大规模定制客户非结构个性化需求结构分析框架，然后设计三元组映射规则，对QFD进行扩展应用，实现非结构个性化客户需求向结构化产品需求的转换，最后举例说明结构化方法的具体应用。方法具有普遍适用性，对云计算等IT个性化服务定制具有指导意义。

Abstract

Mass customization is a new model of manufacturing and services. Customers' personalized service requirement in mass customization often have the unstructured characteristics

and obtaining and analyzing customers' real requirements accurately is the key to successful implementation of mass customization. The definition and determination methods of unstructured personalized customer requirements were proposed

and an analysis framework of unstructured personalized customer requirement in mass customization was built according to their characters. Then mapping rules and extended QFD were designed for the transformation from unstructured personalized customer requirement to structured product requirements. Finally the validity of the method was verified by an example and the method can be helpful to provide personalized cloud service.

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references

约瑟夫·派恩．大规模定制：企业竞争的新前沿．北京：中国人民大学出版社， 2014

Tormod N , Elin K , Hanne S . Identifying and interpreting market segments using conjoint analysis . Food Quality and Preference , 2001 , 12 （ 2 ）: 133 ～ 143

Kuo R J , Ho L M , Hu C M . Cluster analysis in industrial market segmentation through artificial neural network . Computers＆ Industrial Engineering , 2002 , 42 （ 2-4 ）: 391 ～ 399

Sineenard P . A mobile information service adapted to vague and situational requirements of individual . Proceedings of the 7th International Conference on Mobile Data Management , Nara,Japan , 2006

Lai X . Ranking of customer requirements in a competitive environment . Computers ＆ Industrial Engineering , 2008 （ 54 ）, 202 ～ 214

经有国，但斌，张旭梅等． MC半结构化客户需求信息表达与处理方法 . 管理科学学报， 2011 , 14 （ 1 ）: 78 ～ 85 .

李桥兴，刘思峰，张旭梅　　　　等．基于区间距和区间侧距的初等关联函数构造 . 哈尔滨工业技术学报， 2006 , 38 （ 7 ）: 1097 ～ 1100 .

Prasad B . Review of QFD and related deployment techniques . Manufacture Syst , 1998 （ 17 ）: 221 ～ 234

Ettlie J E , Johnson M D . Product development benchmarking versus customer focus in applications of quality function deployment . Marketing Lett , 1994 （ 15 ）: 107 ～ 116

陈少威，郭连水，顾子平．产品需求分析中需求映射方法的研究与实现 . 计算机辅助工程， 2002 （ 2 ）: 11 ～ 16 .

梁樑，周俊，罗彪． MC 模式下基于顾客需求的产品配置优化分析 . 管理科学学报， 2003 , 6 （ 3 ）: 52 ～ 56 .

Qi Z F , Ruan M Y Y . The study of coupling degree of manufacturing cluster . International Conference of Artificial Intelligence and Computational Intelligence （AICI） , Sanya, China , 2010 : 458 ～ 462

唐方成，马骏，席酉民．和谐管理的耦合机制及其复杂性的涌现 . 系统工程理论与实践， 2004 （ 11 ）: 68 ～ 75 .

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