Complex mechatronic systems require expensive, costly measures for maintenance and compliance with process and quality assurance in industrial production. The setting of the process parameters in machines, however, is often dependent on the expertise of individuals and therefore not always reproducible. On the other hand, the extensive process, plant and quality data collected by the sensors on the machines at top speed is monitored only for isolated components or not at all.
The potential for significant cost and time savings in this area lies in software solutions that generate usable information from the sensors’ big data and provide predictive maintenance and quality assurance tasks as open, easy-to-use smart services. A suitable platform for such Internet-based services , which can be transferred to various manufacturing companies, is currently being developed by the OpenServ4P joint project sponsored by the German Federal Ministry for Economic Affairs and Energy (BMWi). It uses methods of machine learning and data mining in connection with scalable cloud services. Munich-based SALT Solutions AG is heading the joint project. You can find them at the Hanover Messe, BMWi joint booth (hall 2, booth C28) .