Predictive Molding Capabilities in Automotive Lighting Products: A Correlated and Repeatable Process 2003-01-0988
Two primary focuses of the automotive industry have been cost reduction and lead time reduction. At the same time, automobiles have grown in complexity. An effect of this is Tier One suppliers must be able to provide less costly and higher quality products faster. In this light, many Tier One suppliers have employed virtual simulation techniques in order to support these OEM efforts.
One of the primary tools used for faster development is a molding simulation. Most automotive lighting products are made of plastic components from injection molding tools. These tools often have long lead times for production and are costly. It is imperative that the injection molding tool be able to produce quality parts at the start of production of any given product. Mold filling simulation provides lighting suppliers with a predictive tool to make changes to virtual data prior to the injection molding tool fabrication. In order to satisfy OEM requirements, commercially available software has been blended with highly experienced analysts, tooling engineers, and molding technicians to produce a correlated and repeatable process for predicting injection-molding capabilities. The simulations include the abilities to predict molding defects such as air traps, burns, sinks, and knit lines. These predictions allow for adjustments of gate location, part design, and tool design to minimize the debug process at tool start-up.
The intent of this publication is to show how this simulation process can predict plastic injection molding behavior in complex automotive lighting tools (including multi-color injection processes). Furthermore, these methods will be shown to be repeatable and useful in reducing development time and costs.