Title :
Neural network model for product end-of-life strategies
Author :
Chen, Jahau Lewis ; Wu, Jun-Nan
Author_Institution :
Dept. of Mech. Eng., Nat. Cheng Kung Univ., Tainan, Taiwan
Abstract :
A neural network has the advantages of ease of use and feasibility for solving nonlinear problems with learning capability. The theory of end-of-life design advisor (ELDA) is selected as the basic structure of back-propagation neural network to determine the useful strategy. Furthermore, a self organized map neural network was selected to analyze the relation between each strategy. Hence, the trained neural networks can simulate the analysis mode of ELDA rapidly and offer the designer with an easy operation method in the relative research domain.
Keywords :
backpropagation; design for environment; learning (artificial intelligence); production engineering computing; recycling; self-organising feature maps; back-propagation neural network; design for environment; end-of-life design advisor; green product design; neural network model; product end-of-life strategies; recycling; remanufacture; self organized map neural network; trained neural networks; Analytical models; Costs; Design methodology; Green products; Manufacturing; Marketing and sales; Mechanical engineering; Neural networks; Product design; Recycling;
Conference_Titel :
Electronics and the Environment, 2003. IEEE International Symposium on
Print_ISBN :
0-7803-7743-5
DOI :
10.1109/ISEE.2003.1208066
