Use of nickel and titanium parts for civil aircrafts drives the demand for laser-based welding because of the connected boost in productivity and quality of the final part. The low heat that laser welding introduces into the welded material makes it a prime choice in manufacturing. However, the laser welding process has stricter requirements for material preparation and fit-up of the abutting sheets and plates as a result of material vaporisation, fast welding speeds and, subsequently, a highly dynamic process. Process monitoring systems commonly use a seam tracker to detect geometrical mismatch and a vision systems for detecting surface defects in the melt pool. These sensor systems have concrete limits. Close or too distant butting edges often do not produce sufficient signals to detect the seam or lots of light during the welding process disturbs the image captured by camera and affects overall performance of the monitoring capability. A missing integration of seam tracker signals and vision/infrared camera images most often lead to an incomplete or a misaligned picture of the weld.
If the INNOSEAM assessment manages to provide a viable solution to the challenge, then laser-based welding of structural components from nickel and titanium will receive an improved joint integrity and better fatigue performance. The adaptive control system will combine the information from the seam tracking device and the signals from the laser fibre and evaluate them in real-time. Based on the validation runs, a database will be established that maps the signal events to welding defects for later analysis and algorithm development. Once validated, the INNOSEAM can be transferred to other application areas where the detection of process deviations in welding support the overall manufacturing outcome.