DocumentCode :
479615
Title :
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
Link To Document :
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