FEA-Guided Toolpath Compensation for Robotic Machining: An Integrated CAD/CAM/CAE Framework for Enhanced Accuracy

Industrial robots offer flexibility and cost advantages in machining applications but suffer from limited structural stiffness and dynamic instability, leading to significant positional errors. This study presents a simulation-driven framework for automated toolpath compensation in robotic machining, integrating computer-aided design, manufacturing, and engineering environments. Finite Element Analysis is employed to predict stress, deformation, and reaction forces during machining. These predictions guide dynamic adjustments to key process parameters, such as feed rate and spindle speed, to optimize performance and accuracy. An automated optimization procedure streamlines this process, enhancing toolpath efficiency and safety. The framework is validated through a case study involving the machining of an aluminum support bracket using a KUKA KR3 robot. Simulation results demonstrate significant improvements in path accuracy, shorter machining time and enhanced surface quality. The enhanced toolpath achieves a 10–15% reduction in non-cutting movements, a 5–10% improvement in surface finish and a 15–25% decrease in machining time compared to the initial configuration. This approach eliminates the need for hardware modifications or real-time sensors, providing a flexible and modular solution for achieving high precision outcomes in robotic machining. The work presents an automated methodology for compensating multi-source errors, bridging the gap between virtual analysis and physical execution.