COLD: Control and optimization of layer deposition in large-scale additive manufacturing

Abstract Large-scale thermoplastic 3D printing is an emerging technology that enables cheaper and faster real-scale prototyping and rapid tooling. However, it still presents limitations that can lead to deformations in printed parts due to inadequate cooling conditions during the process. This study proposes COLD: a control and optimization of layer deposition system, based on temperature monitoring, to prevent print failures caused by excessive heat accumulation resulting from insufficient layer cooling time. A thermal camera was attached to a robotic printing system, and, after each layer is deposited, the average temperature of the regions where the next layer will be deposited is evaluated until it reaches a defined threshold. Conical thin wall parts were printed with and without COLD, and the results show that it can contribute significantly to the success of large-scale additive manufacturing. Future studies should focus on the integration of predictive and adaptive capabilities to actively prevent printing failure during the process.