Additive manufacturing using filler wire and laser

Purpose and goal: InAIRwire will help in applying the knowledge about control and monitoring of robotized metal deposition

with laser and wire with a MIMO(Multiple input and multiple output) controller and monitor the process with Deep learning ML methods .The goal is to increase the process capability and process control robustness to guarantee quality of the final product with sustainable methods. The developed controller and the monitoring system will be used in the building of complex geometries in Nikel based super alloys which makes makes a large presentation of the Turbine engine.

Expected results and effects:

InAIRwire will contribute to the possibility to offer lighter products with improved functionality from complex geometrical flexibility with assured quality. The project is expected to lead to application of the deeper understanding in monitoring using multiple sensors in the form of a industrial monitoring system for Quality assurance. The second result is the implementation of an Industrial MIMO controller that is used in the fabrication of Nickel based super alloys with the nine DOF and resistance preheating.

Approach and implementation: The project has a budget of SEK 1 250 000 and runs for 1-years, starting in September 2023. The project will be run as a collaboration between GKN and Högskolan Väst at PTC in Trollhättan. HV and GKN will

will work on generating and evaluating the controller and the monitoring system. The project is divided into five work packages corresponding to the project´s different focus areas; MIMO controller, HotWire Cracking Prevention, Deep learning for Monitoring as well as Knowledge transfer and Project management.