Multi-objective Optimization Of Milling Process Parameters For Green High Manufacturing

With the gradual reduction of global energy reserves and environmental pollution problems become increasingly prominent,the global manufacturing industry is facing great challenges from energy shortage and climate change.Machinery manufacturing industry is the basis for the development of various sectors of the national economy,which is shouldering the task of providing modern technology and equipment for all sectors of the national economy.The scale and level of machinery manufacturing industry is the important signs to reflect the strength of the national economy and the level of science and technology.Machine tool industry is the basis and important part of machinery manufacturing industry,the machine as the basic equipment of machinery industry,which directly affects the production technology level and economic benefits of other mechanical products.The number of global machine tools is large and the use of a wide range,however,the reference data show that the energy efficiency and processing efficiency of the machine tool are relatively low,and the environmental pollution is serious.The realization of high efficient green manufacturing of machine tools has become an urgent problem to be solved in the field of industry and academia and the key technology is also an urgent need to solve of the machine tool research.Based on the national high technology research and development plan project(project number:2014AA041504):research on the technical evaluation and application support system of typical machine tools' green production process,aiming at the problems of energy utilization,carbon emission and machining efficiency of typical machine tools,a multi-objective optimization of milling process parameters for green and high efficiency manufacturing is proposed.Firstly,the energy consumption characteristics of the whole machining process and the structure of the machine tool are analyzed,based on the energy consumption characteristics and the structure of the NC machine tool,the energy consumption of CNC machine tools is decomposed into energy consumption of modules,and the functional relationship between the energy consumption model and the process parameters of the NC machine tools is established.According to the existing theories,the energy efficiency and carbon emission process parameters optimization model for green manufacturing are obtained.Secondly,taking the typical four coordinate vertical machining center as an example,the energy consumption test platform of NC machine tool is set up,and the energy consumption data acquisition is carried out on the typical four axis vertical machining center.Through the analysis of the experimental data and the numerical regression fitting,the power function expression and energy consumption model of each module are obtained,thus the energy efficiency and carbon emission function areobtained.The energy efficiency and carbon emission function expression are verified and the effects of process parameters on energy efficiency and carbon emissions were analyzed by the experimental data obtained by test.The results show that the carbon emissions of milling machining center increase with the increase of spindle speed,and decrease with the increase of feed rate,milling depth and milling width;the energy efficiency increases with the increase of spindle speed,feed rate,milling depth and milling width.In the case of the same spindle speed,the larger feed rate,cutting depth and cutting width can effectively reduce the carbon emissions in the cutting process and improve the energy efficiency of the machine tool.Finally,the quantum genetic algorithm is used to solve the multi-objective optimization model of process parameters of green and high efficiency manufacturing.Comparing the experimental results with the existing parameters,the optimal parameter and two sets of optimization parameters,the results show that the optimal parameter and two sets of optimization parameters are better than those of the existing process parameters,which verifies the feasibility of the optimization method,and the differences between the optimization methods are analyzed.