UBC Theses and Dissertations

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UBC Theses and Dissertations

A numerical model for predicting and optimizing the temperature profile in multi-stage roll forming of thermoplastic composites Schuetze, Dylan Daniel Carl


The thermal profile through a product’s thickness and over the duration of the forming process on polymer matrix composites can have a significant effect on ensuing undesired deformation modes, such as spring-in or spring forward. The following thesis describes the development of a comprehensive thermal finite element model (FEM) of a multi-stage roll forming process for a commingled glass-fibre and polypropylene (PP) woven composite. Over the progression of developing the model, as the process of roll forming when applied to this thermoplastic composite material is relatively new, many previously unavailable properties and characteristics needed to be quantified and described. The developed model can provide the manufacturer with the ability to predict the crystallization point of the composite under alternative forming conditions and therefore, optimize the rolling schedule of the process. Also, when used in conjunction with a similar “simplified” mechanical model, it can estimate the undesired end product deformations such as spring-in. In particular, it is shown that the combination of simple thermal and mechanical models can provide an accurate description of the manufacturing process without the need for computationally expensive, fully coupled 3D models. Furthermore the FEM allows the manufacturer to investigate the robustness of the forming process and the effect of modifications to processing parameters. The ability to predict the thermal profile under varying process conditions henceforth provides a designer the ability to create accurate tooling geometry in order to compensate for final product spring-in and optimize the roll schedule according to the crystallization region of the material, while avoiding or greatly reducing the costly and time consuming trial and error methods otherwise required for such process optimization.

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Attribution-NonCommercial-NoDerivatives 4.0 International