New paper out!
New paper published on end-to-end path planning for homogeneous temperature fields in additive manufacturing.
Path planning in deposition-based additive manufacturing with a focus on process-induced temperature fields, a critical aspect that is often overlooked. Our work introduces an innovative optimization pipeline that efficiently addresses the complex challenges of temperature prediction and path planning optimization.
Key contributions include:
1. Integration of a reduced order model (ROM) derived from finite volume method models, significantly reducing computational demands.
2. Utilization of the Laplace transformation for calculating the steady-state response to any given path.
3. Transformation of the optimization process into a sequential decision-making problem, efficiently approximated with Monte Carlo tree search.
Our approach not only advances the state-of-the-art in large and complex geometry management but also bridges the simulation to reality gap with validated computational and experimental results.
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