Control-Oriented Spatio-Temporal Modelling and Identification for Workpiece Temperature in Additive Manufacturing

Additive manufacturing has attracted the attention of industry and academia, because of advantages like rapid prototyping and production of customized or complex-shaped parts in small batches. Some of the persisting problems in the additive manufacturing of metal parts are the assurance and consistency of product quality, on account of complex physical phenomena and the lack of appropriate closed-loop control, thus hindering its widespread adoption.

One of the decisive factors in the mechanical properties of metal parts is its temperature history during production. However, modeling such behavior is quite challenging, due to its spatial dependency, couplings between different physical phenomena and between in-layer and layer-to-layer dynamics, phase changes and temperature dependent parameters. On the other hand, using constant process parameters or lumped models to control only the melt pool for a constant temperature does not guarantee uniform morphology.

Aiming to fill these shortcomings, the focus of this project is to research modeling and identification approaches for the thermal history of additive manufactured parts under production that are suitable for control-oriented purposes. To this end, models are derived from physical equations and temperature data collected with an infrared camera during manufacturing are used to identify optimal model parameters.

M.Sc. Guilherme da Fonseca Pereira

Since March 2022

Land Hessen

• G. da F. Pereira, G. Jeličić, and A. Kroll, “Spatio-temporal LPV model of 2D workpiece temperature for Direct Laser Deposition,” IFAC-PapersOnLine, vol. 56, no. 2, pp. 6606–6611, Jan. 2023, doi: 10.1016/j.ifacol.2023.10.359.