Marker-free identification of components for bearing rings

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In the transfer project „Marker-free identification of components for bearing rings, the application partner Schaeffler promotes its activities in the field of Auto-ID. By using a component-inherent marker, expensive markers such as laser marking can be saved, surface alterations and impairments can be avoided and a hidden identification marker invisible to the human eye can be employed. By using this technology, Schaeffler will be enabled to identify individual bearing rings without additional marking process and to gather, record and analyze component-related data in consecutive manufacturing steps. In addition, marker-free component identification will complement the Industry 4.0 activities of the application partner.To this end, a method for individual component identification previously developed at the Institut für Informationsverarbeitung (TNT) at Leibniz Universität Hannover will be adopted to the production of bearing rings. Using this patent-pending method, a camera image of a surface portion of machined component will be assigned a “fingerprint”, which is stored in a database along with the corresponding ID. The functionality of this “fingerprinting” method was successfully evaluated by simulation, experiments and in the form of a demonstrator.The purpose of the transfer project is the further development and the adoption of existing algorithms for fully-automatic identification of individual bearing rings of different diameters, ranging from 10mm to 240mm. Here, the ground front face acts information-carrier area. For the intended application within the production process several modifications are necessary. First, a complete scan of the entire fingerprinting area in every process step is too time-consuming. Instead, only once at the start of the process chain the entire scan will be performed. At the consecutive read-out and identification stations, only a small sector of the circular ring will be imaged to perform the matching. Second, a scalable search- and matching algorithm will be developed, which is able to operate in real-time even on database with high numbers of pieces of several 10.000 or 100.000. The improved image processing algorithms then will implemented in a prototype installation in a productive grinding line. Finally, the system will be evaluated with respect to robustness and mass-production readiness.