Machines need to understand their own manufacturing processes in order to unlock the full potential of artificial intelligence for manufacturing. Professor Andreas Michalowski sees this field as one of his research focuses at the University of Stuttgart. During his inaugural lecture, he outlined his vision of the future laser technology in manufacturing.
Lectures are usually about facts, formulas or theories, but rarely about visions. After all, students need the knowledge for their future careers. But the own inaugural lecture is the official start of their teaching activity, when professors like Andreas Michalowski introduce themselves to the faculty and the public in a ceremonial setting. "I would like to give a glimpse into the future of my research field and hope to inspire listeners with my thoughts," Michalowski explains. During his inaugural lecture on June 16, many listeners from academia and industry sat in the lecture hall alongside professors, PhD candidates and students.
Andreas Michalowski holds the newly established chair of "Laser Technology in Manufacturing" and is Deputy Director of the Institut für Strahlwerkzeuge IFSW since August 2022. The professorship was established at the University of Stuttgart wihtin the Innovation Campus Future Mobility (ICM). Another professorship at the University of Stuttgart and two more at the Karlsruhe Institute of Technology will follow.
During the inaugural lecture, the chair holders fundamentally introduce themselves, their subject and their positions. Since not only a professional audience is present, this happens in a generally intelligible and cross-topic lecture. The title of Michalowski's lecture was "Produzieren mit Laser – heute und morgen" ("Manufacturing with laser technology – today and tomorrow").
Michalowski strongly emphasized a future topic in laser technology. "The dramatic advances in the field of artificial intelligence are opening up entirely new possibilities in manufacturing technology," he explained. His vision is for manufacturing machines to become experts themselves, enabling them to produce very complex components cost-effectively, reliably and with the highest quality. This, he said, is an important part of securing the future and competitiveness of Germany as an industrial location. Along the way, data-driven AI algorithms would need to be augmented with physical models and an understanding of causality. Only then would they be able to understand the mechanisms of action underlying manufacturing. Based on this, the machines themselves would be able to make predictions about how a laser process could be executed, for example, with different materials, and which parameters they would need to change to do so. "This link between manufacturing technology and artificial intelligence is a focus of my research," said Andreas Michalowski.