Experimental Optimization Of Injection Molding Process And Its Application

The plastic materials have more and more widely applications nowadays, with higher demands on molding quality. It is increasingly urgent to study the injection molding process optimization technology for optimal process conditions.In order to avoid the blindness of injection molding design, an optimization method adopting twice orthogonal experiments is proposed, together with signal to noise ratio analysis, range analysis, variance analysis and CAE simulation, so that the sufficient and exact experimental information is obtained with the significantly reduced experiment times. The optimal injection molding process parameters is then acquired by analyzing and comparing the experimental information. Excellent products are accordingly manufactured in actual process.The main work and results are:1. Filling time, mold temperature, melt temperature, packing time and pressure are selected as process optimization objects based on the flow nature analysis of polymer melt.2. Two different types of orthogonal experiments are consequently introduced. The injection molding process parameters are refined and then the optimal parameters are achieved conveniently by considering the interaction and importance of process parameters.3. As for a mass of experimental data, the error of single set of data is controlled through signal to noise ratio analysis, the error of entire experiment data sample is controlled through variance analysis, and the quality trend of the molded parts along with the process parameters is obtained through range analysis.4. To improve further the prediction speed of injection molding process parameters, the neural network method is introduced. After training the obtained good experimental sample, prediction error of neural network for corresponding process parameters is smaller. Therefore the neural network can be used for trend prediction, but not suitable for quantitative prediction.5. The corresponding molds should be completed before practical molding tests, so the improper molds with structural defect must be repaired. CAE technology and experimental optimization techniques are applied to optimize the injection molding process, so that the process optimization precedes and directs the mold manufacturing. Hence optimal injection molding process parameters are obtained keeping away from the molds with serious defects.6. An injection molding process query system is tentatively studied aiming to store the optimized parameters and provide references for later optimization work, in view of many kinds of plastic parts, various molding process and an initial value in optimizing the process parameters.7. The proposed optimization method is exemplified to be of certain guiding significance in practical injection molding technology. In the future research, computer technology applied to injection molding process optimization should be lucubrated based on the demand of manufacturing information engineering and the injection molding process research should be integrated with mold manufacture for better research results.