The quality forecasting of mass customization based on support vector machines

Author

Zhao, Xiaosong ; He, Zhen ; Gui, Fangfang ; Zhu, Pengfei ; Yu, Dainuan

Author_Institution

Sch. of Manage., Tianjin Univ., Tianjin

Volume

1

fYear

2008

fDate

12-15 Oct. 2008

Firstpage

647

Lastpage

649

Abstract

Mass customization is a new mode of production which meets modern technological development and needs of customers; in such a mode of production, the quality control methods for product manufacture are different from traditional methods in mass production. Given the complexity of mass customization and its characteristics, the problem of quality is comprehensive; quality forecasting and simulation, online quality control are good methods to solve the problem of quality in mass customization. In this paper, SVM (support vector machines) is combined with practical problems in MC to solve the deficiency of artificial neural network and grey theory in quality forecasting, the quality forecasting model based on SVM is constructed, and the superior performance of SVM is proved through comparing with GM (1, 1) model. Finally, the method is validated by an example.

Keywords

grey systems; mass production; neural nets; product customisation; production engineering computing; quality control; support vector machines; artificial neural network; grey theory; mass customization; mass production; product manufacture; quality control; quality forecasting; support vector machines; Artificial neural networks; Expert systems; Manufacturing; Mass customization; Mass production; Power system modeling; Predictive models; Quality control; Statistical learning; Support vector machines; Grey Forecasting; Mass Customization; Quality Forecasting; Statistical Learning Theory; Support Vector Machines;

fLanguage

English

Publisher

ieee

Conference_Titel

Service Operations and Logistics, and Informatics, 2008. IEEE/SOLI 2008. IEEE International Conference on

Conference_Location

Beijing

Print_ISBN

978-1-4244-2012-4

Electronic_ISBN

978-1-4244-2013-1

Type

conf

DOI

10.1109/SOLI.2008.4686477

Filename

4686477