Assembly dimensional variation modelling and optimization for the resin transfer moulding process

Abstract

The increasing demand for composite products to be affordable, net-shaped and efficiently assembled makes tight dimensional tolerance critical. Due to lack of accurate process models, resin transfer moulding (RTM) dimensional analysis and control are often performed using trial-and-error approaches based on engineers' experiences or previous production data. Such approaches are limited to specific geometries and materials and often fail to achieve the required dimensional accuracy in the final products. This paper presents an innovative study on the dimensional variation prediction and control for fibre reinforced polymeric matrix composites. A dimensional variation model was developed for process simulation based on thermal stress analysis and finite element analysis (FEA). This model was validated against experimental data, analytical solutions and data from the literature. Using the FEA-based dimensional variation model, the deformations of typical composite structures were studied, and a regression-based dimensional variation model was developed. By introducing the material modification coefficient, this comprehensive model can account for various fibre/resin types and stacking sequences. The regression based dimensional variation model can significantly reduce computation time by eliminating the complicated, time-consuming finite element meshing and material parameter defining process and providing a quick design guide for composite products with reduced dimensional variations. The structural tree method (STM) is proposed to compute the assembly deformation from the deformations of individual components as well as the deformation of general shape composite components. The STM enables rapid dimensional variation analysis/synthesis for complex composite assemblies when used along with the regression-based dimensional variation model. The work presented here provides a foundation to develop practical dimensional control techniques for composite products.