Control-Oriented Modeling and Layer-to-Layer Spatial Control of Powder Bed Fusion Processes
Xin Wang, Bumsoo Park, Robert G. Landers, Sandipan Mishra, and Douglas, A. Bristow

TL;DR
This paper introduces a novel layer-to-layer spatial control model for Powder Bed Fusion, enabling thermal regulation and improved process consistency through a spatial iterative learning controller, even with changing geometries.
Contribution
It develops a control-oriented thermal model for PBF that captures spatial effects and enables layer-to-layer control without temporal delays, advancing process regulation techniques.
Findings
The spatial ILC effectively regulates temperature across the entire part.
The model captures spatial thermal effects and supports voxel-level monitoring.
The controller maintains thermal stability even with changing geometries.
Abstract
Powder Bed Fusion (PBF) is an important Additive Manufacturing (AM) process that is seeing widespread utilization. However, due to inherent process variability, it is still very costly and time consuming to certify the process and the part. This has led researchers to conduct numerous studies in process modeling, in-situ monitoring and feedback control to better understand the PBF process and decrease variations, thereby making the process more repeatable. In this study, we develop a layer-to-layer, spatial, control-oriented thermal PBF model. This model enables a framework for capturing spatially-driven thermal effects and constructing layer-to-layer spatial controllers that do not suffer from inherent temporal delays. Further, this framework is amenable to voxel-level monitoring and characterization efforts. System output controllability is analyzed and output controllability…
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Taxonomy
TopicsAdditive Manufacturing and 3D Printing Technologies · Additive Manufacturing Materials and Processes · Injection Molding Process and Properties
