Control of Additive Manufacturing
Control of additive manufacturing (AM) processes involves delivery of material and energy to precise locations at prescribed times during the manufacturing process. While each process is distinct and thus the challenges associated with designing control algorithms are unique, motion control and process control are the two primary objectives in all AM processes. Standard motion control strategies are used to position nozzles, motion stages, and steering mirrors. Model-free feedback and feedforward design strategies such as PID and iterative learning control are often used for process control of low-level process variables. On the other hand, geometry and part-level control strategies are designed through physics-based in-layer and layer-to-layer models built on momentum, mass, and/or energy balance equations.
Keywords3D printing; Motion control; Process control; Model predictive control; Physics-based modeling; Gray-box modeling; Iterative learning control; 2D systems; Feedback linearization
- ASTM International (2012) Standard terminology for additive manufacturing technologies. Technical Report F2792-12aGoogle Scholar
- Craeghs T, Bechmann F, Berumen S, Kruth J-P (2010) Feedback control of layerwise laser melting using optical sensors. Phys Procedia 5:505–514; Laser assisted net shape engineering 6, Proceedings of the LANE 2010, Part 2. [Online]. Available: http://www.sciencedirect.com/science/article/pii/S1875389210005043
- Guo Y, Peters J, Oomen T, Mishra S (2018) Control-oriented models for ink-jet 3D printing. Mechatronics 56:211–219. [Online]. Available: http://www.science direct.com/science/article/pii/S0957415818300618
- Rawlings JB, Mayne DQ (2012) Model predictive control: theory and design. Nob Hill Publishing, MadisonGoogle Scholar
- Wassink MG, Bosch N, Bosgra O, Koekebakker S (2005) Enabling higher jet frequencies for an inkjet printhead using iterative learning control. In: 2005 IEEE conference on control applications (CCA). IEEE, pp 791–796Google Scholar