Research On Multi-objective Optimization Of Injection Molding Machine Energy Consumption And Product Quality Based On Numerical Simulation

China’s manufacturing industry has developed rapidly and has become the largest manufacturing country in the world.However,on the one hand,based on China’s long-term and rapid development of industrialization,China’s manufacturing energy consumption is very large;On the other hand,the traditional industrial growth model characterized by high investment,high consumption,high pollution,low quality and low efficiency has brought a series of problems such as energy waste and environmental degradation.The plastic industry is developing rapidly,with increased demand,improved product types and quality requirements,and energy constraints.As the most widely used processing equipment in plastic production,the overall energy consumption of injection molding machine is very large.Therefore,in order to effectively promote the green development of China’s plastic manufacturing industry,for the purpose of the standard of "high yield,high quality and low consumption",under the condition that the plastic raw materials,injection molding machine model and mold are determined,how to achieve the energy-saving soft technology optimization of injection molding machine from the two aspects of energy consumption and injection quality is of great significance to China’s plastic industry.Aiming at the problems of high total energy consumption and unstable product quality of thermoplastic injection molding of injection molding machine,this thesis takes bs80-Ⅲinjection molding machine as the research object,and optimizes the process parameters of injection molding process energy consumption and product quality based on numerical simulation technology and multi-objective optimization algorithm.Firstly,according to the structural characteristics and working principle of the injection molding machine,and then from the perspective of production,analyze the impact of the three process characteristics of temperature,pressure and molding cycle on the energy consumption and quality of the production process,accurately and refine and extract the effective process parameters.In order to evaluate the energy consumption of the injection molding machine and product quality,the energy consumption model in the variable value stage of the injection molding process is established Volume shrinkage and weight deviation index on the basis of in-depth understanding of its working principle,.Secondly,the thermoplastic injection molding model is constructed based on numerical simulation technology.In order to ensure the reliability of the numerical simulation,the reliability of the thermoplastic injection molding numerical simulation model is verified by using the filling pressure data of the actual production process provided by the enterprise,and the dynamic time warping（DTW）is introduced to analyze the similarity of the numerical simulation results.Then,combined with the energy-saving and consumption reduction of injection molding machine,the evaluation index of product quality and the numerical simulation model,the comprehensive response value of each simulation experiment is solved,the significance analysis of orthogonal experiment is used to determine the parameters to be optimized,and the influence law of the three parameters to be optimized on the energy consumption and quality of injection molding machine is explored by single factor analysis,which lays the foundation for the energy consumption and quality modeling in the next chapter.Finally,the prediction model between the parameters to be optimized and energy consumption and quality is constructed based on the random forest model.The self adaptive differential evolution with neighborhood search（Sa NSDE）is used to iteratively search and optimize the multi-objective prediction model to obtain the best parameter combination.The main contents of this thesis are as follows:（1）In view of the problem that the energy consumption model in the previous research covers equipment parameters and soft parameters,there is an urgent need for an energy consumption model related to process parameters for soft technology energy conservation,this thesis proposes a variable value stage energy consumption modeling method based on the concepts of variable value and non variable value.According to the working cycle of the injection molding machine,certain energy consumption is consumed in each step of mold closing,plasticizing,filling,pressure maintaining,cooling,mold opening and thimble advance and retreat.Firstly,the energy consumption of the single cycle system is calculated,and then the energy consumption in the variable value stage is separated according to the impact of the change of process parameters on the energy consumption value.The energy consumption in this stage accounts for a significant proportion of the system energy consumption,so a reasonable energy consumption evaluation model of the injection molding machine is constructed.（2）In view of the difficulties in obtaining the quality evaluation indexes such as volume shrinkage,flow front temperature,wall shear pressure and volume flow rate,this paper constructs a thermoplastic injection molding simulation model based on numerical simulation technology,carries out mold flow analysis,and uses the dynamic time warping algorithm to analyze the similarity of injection molding process characteristics,so as to obtain the reliable information of the global flow state of the filler,Provide visual help for injection quality effect,and provide detailed process data in analysis for energy saving and consumption reduction.（3）Aiming at the problem of many process parameters and large input dimensions of thermoplastic molding,this thesis establishes a six factor four level orthogonal experiment,analyzes the significance of the process parameters of the injection molding machine by using the visual data of the thermoplastic injection molding simulation model and combined with the experimental results,and determines that the filling time,holding pressure and melt temperature are the process parameters to be optimized in this thesis.Finally,combined with the three evaluation indexes of energy consumption,volume shrinkage and weight deviation rate in the variable value stage,the single factor influence law of key process parameters on energy consumption and product quality is discussed and analyzed.（4）For the traditional optimization experiments are limited by long time-consuming and high computational complexity,a multi-objective optimization scheme of injection molding machine energy consumption and product quality based on neighborhood search adaptive differential evolution algorithm（Sa NSDE）is proposed in this thesis.Firstly,combined with the orthogonal experimental scheme and numerical simulation,the process data under multiple groups of working conditions are extracted,and the results are calculated according to the energy consumption and quality evaluation indexes.Then,with the process parameters to be optimized as the input and the energy consumption and quality evaluation indicators as the output,the prediction and regression model of energy consumption,volume shrinkage and weight deviation rate in the variable value stage is constructed based on the random forest algorithm.Finally,the optimization parameters are subject to range constraints.Taking the above three prediction regression models as the optimization function,the optimization model is iteratively searched and optimized based on Sa NSDE algorithm to obtain the optimal Pareto solution set.The optimization results are compared with the original scheme to prove the effectiveness of the optimization method.