Injection molding is a major method used in the manufacture of plastic parts in industry. Due to many reasons, including mold design, molding machine settings and many more, plastic parts can have different kinds of defects, among which warpage is usually the major concern. This research aims to reduce the warpage of plastic automotive fuse boxes by improving the mold designs and fine-tuning the machine settings.

Using an injection molding simulation software, design of experiment (DOE) and analysis of variance (ANOVA), several important parameters, including the runner diameter, packing pressure etc. were investigated to identify their effects on warpage. According to ANOVA, it is found that packing pressure, runner diameter, cooling time and injection time have significa...[ Read more ]

Injection molding is a major method used in the manufacture of plastic parts in industry. Due to many reasons, including mold design, molding machine settings and many more, plastic parts can have different kinds of defects, among which warpage is usually the major concern. This research aims to reduce the warpage of plastic automotive fuse boxes by improving the mold designs and fine-tuning the machine settings.

Using an injection molding simulation software, design of experiment (DOE) and analysis of variance (ANOVA), several important parameters, including the runner diameter, packing pressure etc. were investigated to identify their effects on warpage. According to ANOVA, it is found that packing pressure, runner diameter, cooling time and injection time have significant effects on warpage. Some mold design rules and machine setting guidelines were also proposed.

This optimization system can not only save the mold designers a lot of time, but also improve product quality by reducing the warpage at critical points of the plastic products. Future works of the research include continually collecting more data to enrich the Moldex3D, using an artificial neural network to analyze the data and identify the optimal mold design and molding process parameters, taking gate positions and cooling system into account when choosing key parameters, and further optimizing the infrastructure of the entire optimization system.