Research On Numerical Control Machine Tool Energy Consumption Modeling And Energy-Saving Optimization Of Cutting Parameters

Machine tools, as the basic units of equipment manufacturing, are widely used in the manufacturing industry, which consume a massive amount of energy. With energy issues and environmental challenges more and more severe, energy consumption of machine tools is receiving extensive attentions from the international community. Aiming at the high energy consumption and low energy efficiency characteristics of numerical control (NC) machine tools, it is of significance to analyze energy consumption characteristics and seek energy-saving optimization methods of NC machine tools. Estimation and analysis of energy consumption of machine tools are the basis of energy-saving optimization. Therefore, the energy consumption model of NC machine tools is established from the beginning in this paper. Subsequently energy efficiency and energy-saving optimization of cutting parameters are studied. The major contributions are as follows.According to energy-consuming characteristics of NC machine tool components and the relevance of the components to the machining process, the energy consumption of NC machine tools is divided into four sections:no-load energy consumption of the main driving system; no-load energy consumption of the feed system; energy consumption of auxiliary systems; energy consumption of the machining process, including tool tip cutting energy consumption and additional energy losses. Each section is modeled on the basis of energy-consuming mechanism and experimental statistics, so as to form the general energy consumption model of the entirety. Then experiments are conducted on a vertical machining center to study energy consumption rules using the model. Results preliminarily show that the energy consumption model has good applicability, and can accurately predict the NC machine tool’s energy consumption.In order to investigate the relationship between the energy efficiency of NC machine tools and the cutting parameters, single-factor experiments and two-factor experiments are carried out to assess the effect of changing single cutting parameter or double cutting parameters on the energy efficiency of the NC machine tool. Results indicate as follows:The increase in any one of the cutting parameters results in an increase in the productivity and the energy efficiency of the machine tool; When the stiffness of the process system is insufficient, it is a priority to select higher milling speed, higher feed per tooth and larger width of cut from the perspective of energy saving of the machine tool; When the material removal rate remains constant and spindle speed is less than the absolute maximum point of no-load power consumption of the main driving system, decreasing milling speed and increasing any one of the other cutting parameters help to lower specific energy consumption (SEC); When the material removal rate remains constant, changing any two of feed per tooth, depth of cut and width of cut has the same approximate effect on SEC, but it’s recommended to increase feed per tooth or width of cut and decrease depth of cut in consideration of the stiffness and the strength of the process system; It is energy-inefficient and should be avoided to have the main spindle running around the absolute maximum point of no-load power consumption of the main driving system.A NC milling optimization mathematical model for energy saving and high productivity is established with cutting parameters as optimization variables. Then a fast elitist non-dominated sorting genetic algorithm (NSGA-Ⅱ) based on MATLAB is applied to resolve the model. Finally, a case study is given and its results demonstrate the feasibility and the effectiveness of the proposed model. The case study shows that in order to achieve lower energy consumption and higher productivity for given machining requirements and constraints, the maximum possible value of feed per tooth should be selected; the optimal combination of cutting parameters obtained from NSGA-Ⅱ yields lower energy consumption and higher material removal rate than the empirical one, thus, the proposed optimization method can provide support for cutting parameters optimization for energy saving and high productivity.