Abstract
The process conditions have important influence on final part quality in injection molding, and how to get optimum process conditions is the key to improving part quality. Sinkmarks on the surfaces of injection-molded parts is one of the problems that limit the overall success of injection molding technology, and the presence of sinkmarks significantly impairs the surface quality of injection molded parts. A combination method of artificial neural network and genetic algorithms is proposed to optimize the injection molding process, and the processing parameters of a refrigeratory top cover are optimized using the combining method to minimize the sinkmarks on the part. The results indicate the combining method is an effective tool for the process optimization of injection molding.
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