DocumentCode
2788586
Title
Process plans decision-making based on BP neural network and Genetic Algorithm
Author
Wang, Zhong-bin ; Chen, Yu-Liu
Author_Institution
Coll. of Mech. & Electr. Eng., China Univ. of Min. & Technol., Xuzhou
Volume
3
fYear
2008
fDate
12-15 July 2008
Firstpage
1363
Lastpage
1368
Abstract
In order to improve intellectuality and performability of computer-aided process planning system, the status and capability of manufacturing resource in the job-shop should be considered, and the sequencing decision of process plans should be realized under the relevant constraints. In this paper, BP neural network was applied to select the manufacturing resources in the process of generating process plans. During sequencing process routes, the choices of the manufacturing operations, machines and cutters were decided at the same time, then the optimization decision for process plans was obtained by the operators of genetic algorithm, such as duplication, crossover and variation. The results showed that the selection of manufacturing resources and the optimization decision of process plans were implemented effectively by BP neural network and genetic algorithm, the optimal or sub-optimal process plan satisfied the production requirements was obtained. Based on an illustrative example, the process of selecting the interrelated machines and deciding the operations sequence was described in detail.
Keywords
backpropagation; computer aided production planning; decision making; genetic algorithms; neural nets; process planning; BP neural network; computer-aided process planning system; decision-making; genetic algorithm; job-shop; manufacturing operations; manufacturing resource capability; optimization decision; process plans; production requirements; sequencing process routes; Computer aided manufacturing; Cybernetics; Decision making; Genetic algorithms; Machine learning; Manufacturing automation; Manufacturing processes; Neural networks; Process planning; Production; BP Neural Network; Computer-aided process planning; Genetic algorithm; Operation sequence; Resource decision;
fLanguage
English
Publisher
ieee
Conference_Titel
Machine Learning and Cybernetics, 2008 International Conference on
Conference_Location
Kunming
Print_ISBN
978-1-4244-2095-7
Electronic_ISBN
978-1-4244-2096-4
Type
conf
DOI
10.1109/ICMLC.2008.4620617
Filename
4620617
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