Adaptive toolpath for improved thermal management in additive manufacturing (AM)

Additive manufacturing (AM) processes, such as Fused Filament Fabrication (FFF) and Directed Energy Deposition (DED), are highly susceptible to heat accumulation and uneven cooling, leading to residual stresses, geometric inaccuracies, and compromised material properties. While the magnitude of these effects is far smaller in FFF, effective thermal management is essential to address these challenges in DED. This paper proposes a novel adaptive toolpath control strategy that dynamically adjusts the deposition path of the subsequent layer based on the thermal gradient of the previous layer. While DED is the primary focus for this implementation, initial experimentation leveraged FFF due to its cost-effectiveness and similar thermal characteristics to DED, allowing for efficient testing and validation of the proposed strategy. Four infill stacking patterns—SAME, FLIP, ROTATE SAME, and ROTATE FLIP—were tested, revealing that FLIP and ROTATE FLIP produced more symmetric thermal distributions. These results demonstrate the feasibility of adaptive toolpath strategies for improving thermal management in DED, with future work focused on advanced algorithms, thermal simulations, and validation in DED applications.