Modeling and identification of thermal systems in additive manufacturing
Brief description
The BiTWerk consortium is researching the biological transformation of technical materials. The entire life cycle of a product is considered holistically and optimized with regard to better use of resources. The aims of this project are to research new methods for the production of novel material or layer systems. The focus is on increasing the functionality of individual components through chemical and physical modifications.
Additive manufacturing is considered a suitable process for the BiTWerk project due to its versatility. However, the physical processes that take place and their parameters, which influence the material properties and quality of the product, are not fully known. The Department of Measurement and Control Engineering has been working for many years on the data-driven modeling (system identification) of such manufacturing processes. This results in mathematical models that enable the analysis, control and optimization of complex dynamic processes.
As part of the BiTWerk project, the temperature environment during the additive manufacturing of a component is to be investigated using a thermal camera in order to design a model for controlling the process.
The manufacturing process is characterized by temperature-dependent material properties, unknown emissivities, phase change of the material and complex mass and energy transfer phenomena. The analysis is carried out using a grey-box approach, whereby physically-based theoretical models are supplemented with experimental data. In this subproject, the manufacturing process is modeled with finite elements in order to select a suitable model structure for system identification. With a good model structure, the identification leads to accurate or better interpretable models. Measurement data is available from preliminary work and can also be obtained through experiments on the LMD² device.
The aim is to create compact models for controller design.
Main research areas
- Additive manufacturing (direct laser deposition, 3D printing)
- Modeling (white-box & grey-box)
- Signal processing, system identification
Person in charge
Goran Jelicic, Ph.D.
Period
September 2022 - December 2025
Promotion
State of Hesse
Publications and talks
- Guilherme da Fonseca Pereira, Goran Jelicic, Andreas Kroll: Spatio-temporal LPV model of 2D workpiece temperature for Direct Laser Deposition, IFAC-PapersOnLine, vol. 56, no. 2, pp. 6606-6611, 22nd IFAC World Congress, https://doi.org/10.1016/j.ifacol.2023.10.359
- Guilherme da Fonseca Pereira, Goran Jelicic, Andreas Kroll: Spatio-temporal temperature models for growing 2D workpieces during DLD with emissivity compensation for thermal imaging, 2024 IEEE Conference on Control Technology and Applications (CCTA), pp. 310-315, Newcastle, UK, https://doi.org/10.1109/CCTA60707.2024.10666539
- Massimiliano Pandolfo, Guilherme da Fonseca Pereira, Andreas Kroll: Control-Oriented Spatio-Temporal Grey-Box Temperature Models for DLD Processes: Two Case Studies, Fifth International Conference on Simulation for Additive Manufacturing (Sim-AM 2025), Pavia, IT