Research on customer requirements processing model of mass customization design

Author

Xi Tao ; Wang Lijing ; Shi Minghua

Author_Institution

Sch. of Mech. & Electr. Eng., Tianjin Polytech. Univ., Tianjin, China

fYear

2010

fDate

26-28 June 2010

Firstpage

6168

Lastpage

6171

Abstract

According to the actual characteristics of the customer requirements information in mass customization design, the requirements information processing model is established based on fuzzy set, rough set and Support vector machine theory of effective. Firstly, the discrete numerical processing of semantic attributes, fuzzy-based information and continuous values in customer demands are carried out with fuzzy set theory. Then the rough set theory is used to reduce attribute and extract rule for a large number of redundant information. Finally, the use of support vector machine theory, reduction properties of the requirements and functional characteristics of products are carried out regression analysis. Acustomization design case of engineering machinery equipment is developed to illustrate that the model can effectively handle the semantic, fuzzy-based and requirements information extraction and function quality mapping of redundancy information in customer requirements.

Keywords

customer satisfaction; fuzzy set theory; machinery production industries; mass production; product customisation; product design; production engineering computing; regression analysis; rough set theory; support vector machines; continuous values; customer demand; customer requirements processing model; discrete numerical processing; function quality mapping; fuzzy set theory; fuzzy-based information; machinery equipment engineering; mass customization design; reduction property; redundancy information; redundant information; regression analysis; requirements information extraction; requirements information processing model; rough set theory; rule extraction; semantic attributes; support vector machine; Data mining; Design engineering; Fuzzy set theory; Fuzzy sets; Information processing; Mass customization; Mechanical engineering; Power engineering and energy; Set theory; Support vector machines; customer requirements analysis; fuzzy set; mass customization design; rough set; support vector machine;

fLanguage

English

Publisher

ieee

Conference_Titel

Mechanic Automation and Control Engineering (MACE), 2010 International Conference on

Conference_Location

Wuhan

Print_ISBN

978-1-4244-7737-1

Type

conf

DOI

10.1109/MACE.2010.5536528

Filename

5536528