Prediction of warpage in welded assemblies

Long glass fiber reinforced polypropylene (PP-LGF) is a material often used in semi-structural automotive components, such as front-end module carriers, door modules, dashboard carriers and hatch back doors. Main process for the production of these parts is injection molding, which generates complex glass fibre length and orientation distributions during processing. The fibre orientation resulting from the injection moulding process does not only influence local stiffness and strength properties but also the local shrinkage behaviour. The anisotropic shrinkage and the fact that fibre orientation varies within a part, will cause part warpage. In industrial application, warpage analysis in predictive engineering software, such as Moldflow, are often utilised to find a gating strategy that minimises part warpage. If multiple parts are to be assembled, current working practice is to minimise warpage of all parts individually. However, in the end the customer is interested in the shape of an assembled part and less in the shape of the individual parts.

This paper presents a predictive engineering method – validated by 3D measurements of a commercial instrument panel – to calculate warpage in welded assemblies using glass-filled thermoplastics. These materials offer good mechanical performance; however, anisotropic shrinkage can result in part warpage. This is especially a concern in an assembly, where shape deviations of individual parts can influence the final assembly shape. Predictive engineering can optimize gate locations and injection sequence, thereby minimizing part warpage.


The Author

Dr. Amin Sedighiamri
Application Development Engineer