KUKA, the German manufacturer of industrial robots and factory automation systems, is supplying 23 friction stir welding (FSW) cells with integrated robots for the production of electric vehicle (EV) components/assemblies for an automotive customer, in what is the largest single order in this area to date. The FSW cells feature KUKA KR Fortec robots and are integrated into production lines for EVs, where they are used in several production steps that include welding battery trays together, as well as joining cooling plates to the battery trays in a second production step. KUKA is responsible for the entire friction stir welding process.
Battery trays play a crucial role in electric vehicles. They must be leak-proof and resilient, support the correct temperature of the batteries, and help to prevent the vehicle occupants from being endangered by the battery in the event of an accident. A particular challenge in production is 3-D welding; and while robot-based FSW technology is particularly suitable for this application it also requires complex clamping technology. This is another area for which KUKA contributed its engineering expertise, along with a tool changer and a cleaning station for the FSW tools to support fully automatic operation.
With FSW, a rotating, pin-like tool is guided between the contact surfaces of the component, with the resulting frictional heat causing the material to plasticise as the parts are joined together. Even difficult-to-weld or dissimilar materials can be joined; for example, aluminium can be welded together with magnesium, copper, or steel. Moreover, this process consumes less energy and material than conventional processes; and neither does it does require shielding gas or flux cored wires.
KUKA is working with research partners to further develop the technology.
For example, to monitor the quality of the weld seams during the process, and thus reduce the time and costs of the subsequent inspection, KUKA is working with partners in the AI production network of the University of Augsburg on an AI-based process monitoring system.