We are looking for a PhD-student to strengthen our highly motivated and multidisciplinary research team, who will work on the monitoring and sensing of the fundamental physical phenomena occurring during laser-material interaction, in order to optimize laser-material processing for laser-based manufacturing, e.g. laser cladding.
High power laser beams are increasingly employed not only due to their commercial availability, but also for the ability to deposit high energy at localized area with controllable energy rate in order to achieve desired material properties. This photonics-based manufacturing technique leads to various laser-based manufacturing processes, including but not limited to, laser cladding, laser welding, laser implantation, laser ablation and laser etching. Metal additive manufacturing at large scale such as laser cladding is a well-established technique to reduce the cost of repairing or regenerating the damaged industrial components in energy, transport, waste, construction and manufacturing industries to name few. In comparison with conventional coating techniques such as plasma, thermal spray coating and arc welding techniques, laser cladding provides excellent metallurgical bonding, high precision and low distortion – offering substantial sustainability benefits in the terms of resource efficiency, product lifetime and value chain reconfiguration.
For examples of recent work done in this line of research, please check:
- Bremer, S. J. L. et. al. (2023). Laser intensity profile as a means to steer microstructure of deposited tracks in Directed Energy Deposition. Materials and Design, 227, .
- Ur Rahman, N. et. al. (2019). Directed energy deposition and characterization of high-carbon high speed steels. Additive manufacturing, 30, .
Laser-based Direct Energy Deposition (DED) is an Additive Manufacturing technique involving melting of feedstock on substrate resulting in high cooling rates, non-linear material properties at elevated temperature and differential shrinkage. Solidification initiates from the melt pool, and the associated parameters such as temperature, thermal gradient and geometry of the melt pool largely determines the quality of the cladded product. Measurement techniques to measure e.g., temperature, clad geometry, pressure, stress and flow rates are often trivial at low temperatures and/or during post-processing steps, however, in-situ, real-time insights into the melt-pool are either not possible, or cannot be performed easily at high temperatures. You will, as a PhD candidate, establish a more accurate, real-time (multi-) sensor-based monitoring approach in order to characterize melt pool spatio-temporally as well as spectro-thermally. To minimize individual sensor uncertainties and to maximize various sensor modalities, you will subsequently develop algorithms for sensor fusion, using Artificial Intelligence/Machine Learning concepts, that can be employed in data, fusion or decision level to optimize strategies and real-time feedback for consistent, high quality production of metallic parts using laser based additive manufacturing. Such a sensing solution could also be scaled for different length and time scales. State-of- the-art laser facilities are available at the Chair of Laser Processing. You will also closely collaborate with researchers in other groups at the University of Twente.
If you are someone with a strong background in experimental optics involving high power lasers, preferably in imaging and spectroscopy, driven by curiosity, creativity, and dedication, we invite you to apply for this opportunity.