Control-oriented models for ink-jet 3D printing

摘要

This paper proposes two control-oriented models to describe the layer-to-layer height evolution of the ink-jet 3D printing process. While the process has found wide applicability, as with many industrial 3D printing systems, ink-jet 3D printers operated in open loop, even when sensor measurements are available. One of the primary reasons for this is the lack of suitable control-oriented models of the process. To address this issue, two control oriented models are proposed in this paper, the first is based on droplet geometry superposition, while the other is based on a graph-based characterization of local flow dynamics. The superposition model ignores the flow of the deposited liquid material, while the graph-based dynamic model is able to capture this phenomenon. These two models are compared with an existing flow-based empirical model and validated with experimental results, with the graph-based dynamic model demonstrating between 5 and 14% improvement in layer height prediction. Both the superposition model and the graph-based dynamic model are suitable for closed-loop control algorithm design (as they are discrete layer-to-layer state-space models). We envision that these control-oriented models will ultimately enable the design of model-based closed-loop control for high resolution ink-jet 3D printing.