Abstract
To address the manufacturing demands of large-scale aerospace composite components, this study systematically investigates the coordinated motion characteristics of multi-axis systems in fiber placement equipment. This investigation is based on the structural features and process specifications of the equipment. A comprehensive motion control scheme for grid-based fiber placement machines was developed using the Siemens 840D CNC system, integrating filament-winding and tape-laying functionalities on a unified control platform while enabling 10-axis synchronous motion. To mitigate thermal-induced errors, a compensation method incorporating a BP neural network optimized by a genetic algorithm with an enhanced fitness function (GA-BP) was proposed. Experimental results demonstrate significant improvements: the maximum thermal errors of the Z-axis and X3-axis were reduced by 36.7% and 53.3%, respectively, while the core mold placement time was reduced to 61% of the specified duration, with notable enhancements in trajectory accuracy and processing efficiency. This research provides a technical framework for the design of multi-axis cooperative control systems and thermal error compensation in automated fiber placement equipment, offering critical insights for advancing manufacturing technologies in aerospace composite applications. The proposed methodology highlights practical value in balancing precision, efficiency, and system integration for complex composite component production.