DocumentCode
2364776
Title
Product Definition in Mass Customization Adopting Neural Network
Author
Zhaoxun, Chen ; Liya, Wang
Author_Institution
Dept. of Ind. Eng. & Manage., Shanghai Jiao Tong Univ.
fYear
2006
fDate
6-10 Nov. 2006
Firstpage
2633
Lastpage
2637
Abstract
Product definition is a process of understanding and translating customer needs into product specifications. In mass customization, this process involves tedious elaboration enacted between customers and engineers, which results in low response and high cost. A method with learning capability and inference mechanism is imperative. Neural network, manifesting its strength in learning, knowledge storing and parallel handling, is adopted in this research to facilitate product definition in mass customization. Elevator definition is selected as the study subject. The customer needs (CNs) and functional requirements (FRs) of elevators are analyzed. Back-propagation neural networks are constructed to learn the mappings from CNs to FRs. Then trained neural networks can be used to project customer voice to specific product specifications
Keywords
backpropagation; mass production; neural nets; product customisation; production engineering computing; back-propagation neural networks; customer needs; functional requirements; inference mechanism; learning capability; mass customization; product definition; product specifications; Artificial neural networks; Biological neural networks; Costs; Elevators; Engineering management; Industrial engineering; Inference mechanisms; Mass customization; Neural networks; Product design;
fLanguage
English
Publisher
ieee
Conference_Titel
IEEE Industrial Electronics, IECON 2006 - 32nd Annual Conference on
Conference_Location
Paris
ISSN
1553-572X
Print_ISBN
1-4244-0390-1
Type
conf
DOI
10.1109/IECON.2006.347597
Filename
4153042
Link To Document