Automated quality control plays a major role in industrial production. Leoben researchers use artificial intelligence to be able to flexibly detect surface defects in workpieces.
Two important applications of artificial intelligence (AI) in industry are quality control and predictive maintenance. In one case, it is automatically determined whether a component actually meets the required specifications, the other is to react to irregularities before the plant is shut down – according to the motto: the spare part is already just before the Swap breaks. A development of the polymer competence center PCCL in cooperation with the Montanuniversität Leoben shows how one can combine both principles in order to optimize production in a kind of “predictive quality control”. The quality of the manufactured workpieces is not only continuously checked. The smallest deviations that are registered are used to change the parameters of the machine and to improve the following workpieces. Dieter P. Gruber is working on his research group “Robot Vision and artificial intelligence“ at PCCL has been automating surface inspection of components for more than ten years. “It’s about developing an artificial eye that can detect visual disturbances in 3D components – even if these surfaces have variable structures and patterns similar to a wood grain or a textile fabric,” the scientist says.
In experiments, the contact information of an artificial finger is measured on different surfaces with special sensors, the data is evaluated using the neural network and associated with parameters of production. In this way, just like the optics or robustness, the touch of a plastic workpiece could be better designed in the future.