Fibre-orientation-driven defect probability mapping for machining-induced delamination and burr minimisation in carbon fibre-reinforced polymer (CFRP) composites

Machining-induced burrs and delamination compromise the integrity of polymer composite components reinforced by chopped carbon tows. An image-based optimisation algorithm was therefore developed that locates the ideal hole centre within the preform allowance to minimise defect risk. High-resolution images, captured under multiple lighting conditions, are processed to generate a probability map of burr and delamination formation. Then, recursive convolution yielded a matrix whose minima identified the optimal hole position. First, edge trimming experiments were conducted to determine the arguments (critical fibre cutting angle and its range) of the developed algorithm. Up-milling was confirmed to outperform down-milling, yielding an order-of-magnitude smaller burr heights and a narrower defect-critical fibre cutting angle range. Then, based on the edge trimming results, holes were circular-milled, and demonstrated that the optimised “best-case” centre reduced average contour height by 64.99 % and contour-depth by 86.51 %, while burr- and delamination-area metrics improved by 84.90 % and 77.07 %, respectively, underlying the efficiency and importance of the proposed method. Implemented at TRL 4 with standard CNC equipment and open-source Python scripts, the method offers a practical framework for integrating burr- and delamination minimisation into CFRP component design and manufacturing process planning.