A Data and Model Hybrid Driven Cutting Parameter Energy-efficiency Optimization Method for Flexible Machining Process Considering Cutting Tool Flexibility
The change of machining tasks leads to frequent replacement of cutting tools in the flexible machining process.The current studies mainly focus on cutting parameter energy-efficiency optimization based on fixed cutting tool,which cannot cope with the dynamic change of cutting tools.To meet the demand of energy efficiency optimization under the condition of multiple cutting tools,a data and model hybrid driven cutting parameter energy-efficiency optimization method considering cutting tool flexibility is proposed.Specifically,the correlation between the energy consumption and cutting parameters under the condition of multiple cutting tools is analyzed,and a data and model hybrid driven cutting parameter optimization model is formulated.Then,the cutting parameter energy-efficiency optimization method considering cutting tool flexibility is proposed based on Markov Decision theory and Advantage actor-critic algorithm.Finally,the proposed method is demonstrated by extensive comparative experiments,and the results show that the proposed optimization method can effectively carry out cutting parameter optimization adapted to the dynamic change of cutting tool.
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