Research On Modeling And Parameter Optimization Of Cutting Process Energy Consumption In NC Lathe

With the development of resource-saving and environment-friendly society, the energy consumption problem caused by manufacturing has aroused widespread concern. However, with the acceleration of the process of modernization of CNC machine, which is applied widely, it caused a large amount of energy consumption and emission of carbon, which makes enormous impact on the environment. Therefore, under the condition of advocating the concept of sustainable development, as CNC machine is the main carrier of the energy consumption of the manufacturing industry, the reaserch on its energy-saving emission reduction is imminent and significant. Based on this, this article selects the typical numerical control lathe to carry on the research, the main work is summarized as follows:Firstly, the energy distribution of CNC lathe is studied, which leads to know the energy consumption sub-systems in different state of machine tool. Then, the cutting process which is affected significantly by cutting parameters wih high complexity and uncertainly is analyzed. The existing typical methods of energy consumption modeling are listed and analyzed.Secondly, based on the combination of the energy consumption model and the algorithm learning model, the total energy consumption prediction model of NC lathe is presented. For each part of the model, the different assessment and prediction methods are used to predict them, e.g. Smoothing filtering method is used to assess basic energy consumption, and multiple linear regression is used to forecast spindle and the feed axis energy consumption, and improved gene expression programming(GEP)is used to predict tool energy consumption and load power loss. In order to obtain an instance model, the typical CNC lathes CK60 equipped with Huazhong CNC system were used to do factorial experimental design. The power sensor is applied to obtain sufficient experimental data, and using the above mentioned modeling on the energy consumption of cutting process in CNC lathe is done to get the energy consumption prediction model based on GEP Algorithm. And the model is compared and analyzed, which shows that the model has good prediction accuracy.Then, according to the optimization problem of the cutting parameters in NC lathe, the model of energy consumption established is used as one of the objective function, and the time efficiency function of machining process is the other one. Subjected to performance constraints and practical constraints of the processing, the optimization model of cutting parameters based on processing energy and time efficiency is established. After that, an improved multi-objective Teaching-Learning-Based Optimization(TLBO) algorithm is designed to solve the model to get its Pareto front solution. And AHP is used to finally dcisde, which objectively selected better turning parameters.Again, the human-computer interaction interface of cutting parameters optimization system based on cutting parameters optimization model and solving method established above is designed. And it was validated in the typical lathe CK60, which is proved that it can provide decision support for the actual production and processing.Finally, based on the previous research work, the summary of the full text is made, and its in-depth study of the direction is analysized and outlooked.