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.
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;
Conference_Titel :
IEEE Industrial Electronics, IECON 2006 - 32nd Annual Conference on
Conference_Location :
Paris
Print_ISBN :
1-4244-0390-1
DOI :
10.1109/IECON.2006.347597
