NC Process Parameter Optimization Approach In Multi-varieties And Small-batch Production For Low Carbon Consumption

The manufacturing industry is an important pillar industry of national economy.However,it has become the main source of energy consumption,material consumption and carbon emissions in the whole industry of China.It is imperative to be green and intelligent.Machine tools are the main carbon consumption equipment in the manufacturing industry.The proportion of numerical control(NC)machine tool in machine tool is increasing day by day.The NC machining system consisting of CNC machine tools,workpieces,cutting tools and various ancillary facilities is increasingly complex,and the control system is becoming more and more complex,and the auxiliary function system is increasing.The characteristics of carbon consumption are complex and changeable.There are many factors affecting it.There is a large space for energy saving and emission reduction.In addition,the demand for personalized and customized users is increasing,and many varieties and small batch production have become an important production mode in today's manufacturing industry.It is necessary to calculate the processing parameters frequently.It is impossible to obtain satisfactory processing results by relying solely on artificial experience.Compared with other production modes,it is more necessary using the process parameter optimization method.The more historical process cases are produced with the machining process,and how to effectively use the existing data to obtain reasonable processing parameters is a problem to be solved urgently.With the support of the National Natural Science Foundation of China(No.51575071)and the National High-Tech R&D Program of China(No.2012AA041306),the carbon consumption calculation model and the optimization of NC processing parameters under multi variety and small batch production mode are researched in this paper.First,the carbon consumption characteristics of the NC machining system are analyzed in detail.Based on the energy carbon,material carbon and waste carbon,a quantitative calculation model of carbon consumption for NC machining system is established.Then,the influence factors of carbon consumption of NC machining system are analyzed using design experiments.Secondly,the optimization of numerical control processing parameters is described under the model of multi variety and small batch production.The processing quality,processing time,processing cost and processing carbon consumption are taken as evaluation factors.A model for evaluating the effect of NC machining(MEENCM)is set up using the quantitative calculation model of carbon consumption.Based on multi variety and small batch production process,a numerical control process optimization model is established,which includes NC machining carbon consumption calculation module,NC machining effect evaluation module,supervised learning module and heuristic optimization method module.Thirdly,in view of the different processing sample size and the optimization target,three NC process parameters optimization methods are proposed.(1)To solve the low carbon optimization problem of NC machining parameters for multi varieties and small batch production and small process cases,a process parameter optimization approach is proposed using support vector regression(SVR),dragonfly algorithm(DA),machining process and machining evaluation.Including the generation of SVR parameter sets using DA,the generation of process parameters using SVR,CNC machining under the guide of process parameters and the calculation of the target values,four stages are implemented with small samples and MEENCM.The final optimal parameters are obtained.(2)To solve the multi-objective optimization problem of NC machining parameters for multi varieties and small batch production and small process cases,a process parameter optimization approach is proposed using multi-class support vector machine(McSVM),multi-objective ant lion optimizer(MOALO),machining process and machining evaluation.Including the generation of initial process parameter scheme using McSVM,the correction of process parameter scheme using MOALO,CNC machining under the guide of process parameters and the calculation of the target values and non dominated solutions using Pareto optimization method,four stages are implemented with small samples and MEENCM.The final optimal parameters are obtained.(3)To solve the multi-objective optimization problem of NC machining parameters for multi varieties and small batch production and large process cases,a process parameter optimization approach is proposed using improved back propagation neural network(IBPNN),multi-objective grey wolf optimizer(MOGWO),machining process and machining evaluation.Including the generation of initial process parameter scheme using IBPNN,the correction of process parameter scheme using MOGWO,CNC machining under the guide of process parameters and the calculation of the target values and non dominated solutions using Pareto optimization method,four stages are implemented with large samples and MEENCM.The final optimal parameters are obtained.Enterprises can select process parameters for subsequent machining according to the needs of processing targets.The feasibility and effectiveness of the approaches are verified by experiments.Finally,a CNC gear hobbing parameter optimization system is designed under the above methods.The application is implemented in many gear hobbing machine in the workshop of a gear manufacturer in Chongqing.On the basis of the information of machine tool,workpiece,tool and process sample,the optimization of NC process parameters in the multi variety and small batch production is completed.The diversified demand for processing quality,processing time,processing cost and processing carbon consumption is realized.The application data reveal that the system has achieved good results.