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Real time, multiscale digital twin as decision support for adaptive welding robots

Alternative title: Sanntids og multiskala digital tvilling som beslutningsstøtte for adaptive sveiseroboter

Awarded: NOK 2.0 mill.

The goal of the project was to teach robots a deep understanding of welding, by using a combination of smart electromechanical design and a well-informed software. As Welmax is a developer and producer of automated adaptive welding robots, and IFE has mathematical models for simulating welds (WeldSim), we decided to attempt this project together to improve the time and quality of welding Duplex steel. This would allow Welmax' robots to weld Duplex easier and better as they would be able to test weld parameters before actually welding, and correct itself during weld. We were about to test the mathematical model against real-world measurements with help from Sintef Manufacturing, but we needed to stop the project due to the complications of the Covid19 outbreak in 2020.

Through testing of the welding simulation and communication interfacing, we have seen promising indications that this project could be one of the next big revolutions within automated welding. Due to time and resource constraints internally we weren't able to fully explore the capabilities of this project, but it could shave off several weeks or months of work per welding project from reduced defects and rapid WPQ certification.

We will develop a physics informed supervisory control system for robotic welding: A machine learning component will suggest on-the-fly corrective measures to the welding robot based on sophisticated physics simulations and live sensor data. By using inverse modelling in a scalable cluster of cloud computers, we will generate a real time digital twin of the currently welded joint. Validated microstructure models for duplex steels will be used together with a finite element simulation of the thermal transport in the macroscopic weld joint geometry. This multi-scale simulation will inform the robot about the integrity of the weld in real time, so that the robot can take corrective measures if needed. Welmax makes flexible robot solutions that employ laser scanning of the weld groove and the joint geometry to adapt the robot programming to the actual task at hand. The integration of IFE's cloud-based welding simulation software "Weldsim as a Service" with Welmax's adaptive robot welding solutions, will give increased weld consistency over an even wider range of geometric variations, materials and process environments. We focus on duplex steels, as this is an advanced material which is difficult to weld due to a microstructure which is highly dependent on the temperature history. IFE will improve the mathematical models for these steels, and Sintef Manufacturing will contribute with experiments and characterization to validate the models. Both the market for advanced materials and for adaptive robotics are growing, and this project aims for value creation directly in the intersection of these markets. For this reason we expect a tremendous potential for economic gains, provided that the project succeeds.

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