| Gas-assisted injection molding process is a new technology which based on the traditional injection molding.The parameters in gas-assisted injection molding process is also very sensitive to forming quality,so forming quality is very difficult to control.But Gas-assisted injection mold CAE technology can solve this problem.It can predict the influence and trend of various factors,and avoid gas-assisted injection molding defect,find the best combination of parameters。The door handle was the research object in this paper. Numerical simulation was based on gas-assisted injection mold CAE technology and orthogonal test. The forming result which analyzed in the gas-assisted injection molding process of various parameters showed that gas can not penetrate at the boss. It was verified with the actual production.It indicated that the structual design of the door handels has defect.The structure of plastic parts was improved.Then the improved plastic was numerical simulated of gas-assisted injection molding process again.The results showed it can achieved the desired quality of molding in some technology conditions, and indicated structural improvement was reasonable. The factor which affect airway length successively were pre-injection volume, mold temperature, packing pressure control, gas injection delay time,meit temperature and gas pressure control. The best combination of production process was obtained by adjustment the optimal combination based on numerical simution.And with the actual production verification, gas penetration of the plastic was appropriate, no other defects.Neural network model was established based on the experimental data of numerical simulation. By comparison the simulation results predicted by the network of some proups combination with the numerical simulation results, the errors were below 10%. It proved the neural network model can predict the quality of gas-assisted injection molding of different process parameters combination. |
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