Important results from the project
QWELD has delivered strong results in welding quality through sensor-based monitoring, digital twins and AI to detect weld height and defects. Data from laser welding was collected with 4D photonics sensors. Various industrial test cases with key partners provided high relevance. A new materials lab was established at HiS, two master´s theses were completed and two doctoral students were recruited for continued research in data-driven laser welding.
Expected long term effects
QWELD results create a lasting impact through intelligent welding solutions that improve efficiency, quality, and sustainability in the manufacturing industry. It strengthens collaboration between industry and academia and invests in 4D sensors and a new materials lab, with a focus on Innovation and Excellence. By integrating digital tools in education and research, QWELD promotes interdisciplinary learning, skills provision, and scalable solutions for automotive, energy, and future industries.
Approach and implementation
QWELD comprised seven work packages: coordination, industry cases, digital twins, weld quality, sensors, machine learning and dissemination. Despite a change in leadership, the project continued smoothly through adaptive planning. FEM models were validated, a materials lab was established at HiS, and sensor data enabled real-time monitoring and ML. Strong industrial coupling ensured relevance. Two master´s theses were completed and two doctoral students were recruited for continued research.
External links
The project description has been provided by the project members themselves and the text has not been looked at by our editors.
