Koenig & Bauer recently launched its predictive maintenance services for press owners. Various workflows have been elaborated and implemented in close cooperation with more than 20 pilot users.
“The objective of predictive maintenance is clearly defined,” said Thomas Potzkai, Head of Service at Koenig & Bauer. “We use the information contained in existing press data for automated analysis. This makes it possible to identify and rectify potential problems before they occur.”
Service managers are provided with full details of the situation on a given press. On this basis, arrangements can be made for remote maintenance interventions or service calls, as necessary. A technician subsequently rectifies the fault within the framework of a scheduled assignment, averting the risk of unplanned stoppages. Any necessary downtime is scheduled for a production-free period. The customer benefits from greater production reliability and increased press availability. Predictive maintenance applies artificial intelligence methods, such as rule mining or machine learning, to enable precise and automated real-time analysis of the press data.
