Control-oriented models for ink-jet 3D printing. (December 2018)

• Record Type: Journal Article
• Authors: Guo, Yijie; Peters, Joost; Oomen, Tom; Mishra, Sandipan
• Is Part Of: Mechatronics. Volume 56(2018)
• Page Start: 211
• Page End: 219
• Publication Date: 2018-12
• Subjects: Additive Manufacturing -- Ink-jet printing -- Modeling -- Layer-to-layer model; Computer integrated manufacturing systems -- Periodicals; Flexible manufacturing systems -- Periodicals; Mechatronics -- Periodicals; Productique -- Périodiques; Fabrication, Systèmes flexibles de -- Périodiques; Mécatronique -- Périodiques; Computer integrated manufacturing systems; Flexible manufacturing systems; Mechatronics; Periodicals; 629.89
• DOI: 10.1016/j.mechatronics.2018.04.002
• Languages: English
• ISSNs: 0957-4158

Abstract

Abstract: 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.