Dariusz Ceglarek

University of Warwick

Darek Ceglarek's research contributions significantly advance the fields of additive manufacturing, laser welding, and robotic assembly. Recent studies focus on improving microstructure, mechanical performance, and process control in dissimilar material welds, exploring various techniques such as shape error modeling, simulation, and deep learning-based optimization. Additionally, work on battery terminal-to-casing connections, robot manipulation, and compliant part collaboration showcases the potential for enhanced safety and precision. By applying advanced numerical methods, optical coherence tomography, and machine learning algorithms, Ceglarek's research enables improved quality control, reduced variation, and increased efficiency in remote laser welding of automotive batteries and other complex assemblies.