With the increasing demand for composite products to be affordable, net-shaped and efficiently assembled, tight dimension tolerance is critical. Due to lack of accurate process models, dimension analysis and control for resin transfer molding (RTM) processes are often performed using trial-and-error approaches based on engineers’ experiences or previous production data. Such approaches are limited to specific geometry and materials and often fail to achieve the required dimensional accuracy in the final products. This paper presents an innovative dimension variation prediction approach. First a dimension variation model was developed based on process simulation, the classical laminate theory (CLT) and finite element analysis (FEA). The FEA-based dimension variation model was validated against experimental data. The deformations of common features in typical composite structures were analyzed using the FEA-based dimension variation model. Design parameters were identified and the regression-based dimension variation model was developed. The model provides a fast, practical and proactive tool to predict and control dimension variations in RTM processes. The structural tree method (STM) is presented for design optimization and tolerance analysis/synthesis of composite assemblies.

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