Modeling of CNC Machine Tool Energy Consumption and Optimization Study Based on Neural Network and Genetic Algorithm

Dong Xie; Guo Rong Chen; Feng Wang; Jian Qu Zhu

doi:10.4028/www.scientific.net/AMM.195-196.770

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 195-196Modeling of CNC Machine Tool Energy Consumption...

Modeling of CNC Machine Tool Energy Consumption and Optimization Study Based on Neural Network and Genetic Algorithm

Abstract:

The issue of CNC machine tool energy consumption and environmental protection plays an important role on manufacturing technology research since CNC machine tool energy is consumed during motor racing or cutting process. The paper analyzes CNC machine tool energy consumption influence by cutting parameters of cutting speed, feed speed, cutting depth. Based on nonlinear mapping ability of neural network, the model of CNC machine tool energy consumption related to cutting parameters is established by using experimental data, and then the optimal combination of cutting parameters are searched by using global optimization of genetic algorithm, and verified in CNC machine tool cutting experiment. The proposed method provides a good energy control proposal for CNC machine tool roughing process. The experimental results show that the energy consumption is optimal.

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Periodical:

Applied Mechanics and Materials (Volumes 195-196)

Pages:

770-776

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.195-196.770

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Online since:

August 2012

Authors:

Dong Xie, Guo Rong Chen, Feng Wang, Jian Qu Zhu

Keywords:

Energy Optimization, Genetic Algorithm (GA), Machine Tool, Modeling, Neural Network (NN)

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