Design Of Water-Assisted Injection Molding System And Research On Parts Residual Wall Thickness

Water-Assisted Injection Molding(WAIM)technology developed from Gas-Assisted Injection Molding(GAIM) technology,which was a emerging fluid molding technology with the advantages of short molding cycle,high-quality products,low materials cost.WAIM got more and more attention with the market gradually higher requirement of the light-weight plastics.Molding equipment design,molding mechanism and process research for the WAIM had theoretical and practical value in a sense.This paper focused on equipment of WAIM design and residual wall thickness of plastics research,mainly contained the contents as the following:In Chapter 1,made a brief of introduction of research status of WAIM from the aspects of equipment,simulation and experiment research,application prospect and current application difficulties of WAIM were also introduced.In Chapter 2,based on the advantages and disadvantages of pure water hydraulic system of WAIM,designed oil and water hydraulic system of WAIM.The hydraulic schematic diagram,the key components,the key parameters and system structure layout were included.In Chapter 3,based on the PLC controller,control system of WAIM was designed,including electrical control circuit,PLC control system,PLC master program,fault detection subroutine,water temperature control subroutine,injection pressure control subroutine and HMI design.In Chapter 4,according to the flow characteristics of water and plastics melt during injection molding process,the two-phase flow CFD model of WAIM was established,and the residual wall thickness formation process was simulated.At the same time,the influence of injection method and delay time on the residual wall thickness was analyzed in combination of experimental results.In Chapter 5,based on the L-M algorithm,the residual wall thickness of products prediction model of BP neural network was established,and the residual wall thickness was predicted according to delay time,melt temperature and holding pressure.Firstly,the model was trained by using training samples,and then the error analysis was carried out.It was found that the prediction error meets the precision requirement,which proves that the model can be used to predict the residual wall thickness of products.In Chapter 6,made a conclusion of the research contents of the whole paper,and put forward the prospect of the next step.