Visual Inspection with AI
In addition to highly efficient and cost-optimised assembly, intelligent factories are increasingly focussing on fully automated quality assurance of parts, in the shape of measuring and testing tasks during production or at the end-of-line.
To keep the volume of pseudo scrap to a minimum during measuring and testing tasks, reliability is hugely important. Artificial intelligence in particular can play an important part here. FGB is working closely with universities and research institutes to develop an innovative optical testing procedure that detects errors on the surface of rotation-symmetrical steel parts with a high level of reliability.
In this procedure, parts are tested using state-of-the-art self-learning artificial intelligence methods to facilitate reliable, fast, durable and large-scale industrial quality assurance of a previously unknown level. Within the meaning of Industry 4.0, the system that is to be developed will teach itself based on conforming and nonconforming parts, and will therefore allow a quantum leap in quality assurance and the operation of machines.
Also, intelligent algorithms will enable the test module to learn and decide independently which products lie within the production tolerance based on the defined image information for conforming and nonconforming parts. In addition, when the system is used in a large-scale industrial environment, it can simply adapt the testing program to new products, without any complex and expensive further developments.
Any questions or comments about this research project? We will be happy to discuss this in more detail with you. In addition, we always take on new development topics connected to the specific development of your own projects. We look forward to receiving your enquiry.
