Strategy Of Products Quality Control For Rapid Heating Cycle Molding Process Based On The Agent Model

Quality control is the key of injection molding products.Only the continuous upgrading of the quality of products could maintain the industrial competitiveness.Rapid heat cycling molding could increase the rate of cavity replication due to the higher temperature of the mold cavity surface during filling processing,which realize high surface finish.Rapid heat cycling molding process is a typical nonlinear problem,The effect of multiple factors interaction on quality is difficult to control,therefore,the product quality control strategy research is imperative.At the same time,the products quality is extremely sensitive to the change of process parameters,such as high temperature and high pressure.So the optimization of process parameters becomes the key to improve the quality of products.However,the fitness of conventional optimization method on rapid heat cycling molding process is not clear.In this paper,the quality control strategy of rapid heat cycling products was researched.The broker model theory is introduced to model the fitness of evaluation system,and the genetic algorithm was used to optimize the agent model,so as to realize the quality control of products.The main research contents are as follows:(1)The effects of mold temperature on injection molding products.The difference between rapid heat cycling molding and traditional injection molding is the temperature of model.In this paper,the effects of mold temperature on the welded line and surface sinking of injection molding products were investigated.Considering the quality problems,the rapid heat cycling molding processing of a asymmetric porous panel was researched.(2)The control objectives and its factors of rapid heat cycling molding products were researched with finite element simulation test.And the comprehensive evaluation method is adopted to establish the comprehensive quality evaluation index.Besides,the orthogonal simulation test was utilized to establish the 1D/2D response relationship between quality index and influencing factors,which analyzed the influence of various factors on the quality index and determined the forming scope of each factor.(3)The formulation of the optimization strategy bases on the agent model fitness evaluation system and genetic algorithm.In order to determine the best fitness agent model of Rapid heat cycling molding process,the fitness evaluation system was established to evaluate four agent models(BP neural network,Kriging model,the response surface model and radial basis function).Moreover,the simulation was adopted to confirm the optimization.(4)Applied research of control strategy of rapid heat cycling molding products.The optimization control strategy which base on the agent model was adopted to manufacture the Bi-layered remote control's front cover.And a production testing was carried out to confirm the optimization results.