Advanced allowance planning of CFRP composites exploiting the pattern of chopped carbon fibre reinforcement clusters

Abstract

Conventional allowance planning of carbon fibre-reinforced polymer composite plates that must be mechanically machined is based on mainly the analysis of the precision of composite manufacturing technologies. This approach neglects the impact of randomly oriented and positioned chopped fibre reinforcement clusters leading to unpredictable fibre cutting angles and inconsistent quality during machining. To address this issue, we developed an innovative allowance planning method for polymer composites reinforced with chopped fibres. Our approach optimizes the size of the non-uniform allowance to minimize machining-induced burrs on the machined edges by detecting fibre reinforcement clusters on the composite surface through digital image processing and employing a convolution-based optimization of geometric feature patterns. Validation through drilling experiments demonstrated that our method improved the average burr factor by 50% compared to a conventional allowance planning technique. Although the proposed method is recommended to be improved to manage the effects of three-dimensional fibre clusters on burr occurrence, it encourages a novel direction in allowance planning of composites having non-defined directional reinforcements.