Optimal fiber paths for robotically manufactured composite structural panels

Abstract

Robotic Automated Fiber Placement (RAFP) has revolutionized manufacturing of large aerostructures in recent years. From producing lower costing parts to reducing scrap, RAFP has also helped in manufacturing large parts with contours precisely, with repeatable production once the RAFP machine is programmed. RAFP manufacturing allows a designer to utilize curvilinear fiber paths specifically designed to optimize structural performance, for example, maximizing buckling loads, minimizing stress concentrations etc. At the same time, RAFP introduces unintended manufacturing imperfections. These, which can include overlaps and gaps, lead to thickness non-homogeneities in structural panels. In this paper, steered fiber paths for maximizing the buckling loads of RAFP panels while explicitly accounting for manufacturing imperfections is considered. A novel method to model fiber paths is introduced where each course of the lay-up can be explicitly modeled, including manufacturing artifacts of course width, admissible tow curvature, and control on unintended manufacturing deviations that can lead to gaps and overlaps. A machine learning based surrogate modeling technique in conjunction with Genetic Algorithm is used to derive the optimal solutions.