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Abstract
In recent years, plastic injection molds are widely used for producing products in various areas, such as aerospace, automotive, medical, electronics, and toys. The quality of these products depends on correctly chosen molding parameters. In this study, a new package program (NPP)-Software that calculates various injection molding parameters was developed to mold plastic products obtained by plastic injection molding techniques using the model of artificial neural network (ANN). The Delphi programming language was used in the develop the (NPP)-Software. The developed (NPP)-Software was trained and tested using the Levenberg--Marquardt (LM) algorithm, the ANN. One-thousand three-hunderd pieces of data were collected, out of which 250 were used to train the network. The ANN is employed to find optimum molding parameters that enable minimum defects in the injection-molded part, such as volumetric shrinkage, injection time, and cooling time. The three parameters predicted, using the (NPP)-Software, were compared using experimental results.