Temperature Control System And Thermoforming Process Optimization Of Blister Hot Forming

Today,with the rapid development of plastic industry,vacuum suction plastic thermoforming is considered to be a processing method with great development potential in the field of plastic processing.Blister thermoforming machine can form large size and complicated shape of the plastic products at one time.The advantages of low manufacturing cost and short development cycle make it widely used in transportation,packaging,building materials,medical equipment,household appliances and other areas of the industry.However,due to the unreasonable adjustment of the blister process parameters,especially the inaccurate heating temperature control,it is easy to produce defective products and cause waste.This thesis takes the blister molding machine as the research object,with the purpose of finding the best molding process parameters,and optimizes the temperature control system and key process parameters.The main contents are as follows:(1)For the purpose of accurately controlling the temperature of each heating brick,three temperature control schemes based on PLC are proposed,including the conventional PID control,fuzzy PID control scheme and the model prediction PID control scheme.The simulation is carried out in Matlab/Simulink environment.According to the simulation results,a fuzzy PID control scheme with excellent control performance is selected for experiments.The experimental results prove the correctness of the simulation and the superiority of the proposed control scheme.(2)Two kinds of heat transfer temperature distribution models for sheets are established.One is a multi-layer,multi-region mathematical mechanism model based on constant material properties,and the other is a finite element model based on variable material properties.Through experimental comparison,it is more appropriate to select the finite element model to analyze the temperature distribution of sheets.(3)In order to determine the optimal temperature distribution of a group of heating bricks from a random temperature range,the simulated annealing algorithm(SA)and the genetic algorithm(two improved algorithms GA1 and GA2)are introduced into the temperature setting optimization of heating bricks.The method of optimizing the temperature setting of heating bricks by minimizing the energy received between different areas of plastic sheet is studied.The optimization performance of the algorithms are compared,and GA2 with better performance is selected to be applied in the heating station of plastic blister hot forming.The finite element model is used to verify that the proposed algorithm can make the radiant energy received by the sheet more uniform.(4)In view of several process parameters that have great influence on the forming quality in blister hot forming,the significance analysis method is used to find the best combination of process parameters at the selected factor level.On the basis of orthogonal experiment,the prediction model of wall thickness mean value and mean variance based on PSO-BP neural network is established.The optimal combination of process parameters is obtained through the significance analysis of mean value and mean variance of wall thickness,and it is verified by experiment and prediction model.It also show that the prediction model is helpful to guide the optimization of process parameters of blister hot forming.There are 77 figures,34 tables and 91 references in this thesis.