Control-oriented models for ink-jet 3D printing

Yijie Guo, Joost Peters, Tom Oomen, Sandipan Mishra

Research output: Contribution to journalArticleAcademicpeer-review

22 Citations (Scopus)
74 Downloads (Pure)


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.

Original languageEnglish
Pages (from-to)211-219
Number of pages9
Publication statusPublished - 1 Dec 2018


  • Additive Manufacturing
  • Ink-jet printing
  • Layer-to-layer model
  • Modeling


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