Multithreading control framework for multi-arc parallel additive manufacturing of meter-scale lattice structures

Multi-arc parallel additive manufacturing (MAPAM) exhibits exceptional potential for the efficient and high-quality fabrication of meter-scale lattice structures. However, coordinating multiple arc-based heat sources introduces significant complexity and variability into the manufacturing process, which constrains the industrial application of MAPAM. To enhance manufacturing stability, the development of a multithreading control framework based on hardware-software co-design is presented in this study. The molten pool behavior, especially the arc length, served as an ideal diagnostic indicator for online monitoring. A set of customized vision-data processing algorithms were developed by integrating fabrication mechanisms with image features, providing stable feedback signals for closed-loop control. The parallel computing and multithreading architecture enabled the real-time coordinated control of multiple 3D printing units and vision-data streams, thereby achieving stable process control. Experiments demonstrated that parallel computing improved image processing speed by 97% compared with the single-threaded framework. The proposed control system reduced the arc length error by 51% compared to open-loop control, while maintaining stable arc length and uniform geometry. A large-format lattice structure (1.5 m × 3.5 m) comprising 420 lattice cells was automatically fabricated, achieving a 64% reduction in production time compared to the conventional single-arc method. This result demonstrated the excellent potential of MAPAM for industrial-scale applications. Furthermore, the multithreading control framework furnished a data-rich environment and established a robust foundation for developing advanced control algorithms, facilitating the transition from automated fabrication to autonomous additive manufacturing.