Repairing components only after a fault occurs – that's so yesterday. Today sensor technology and intelligent data analysis enable predictive machine maintenance. Thanks to digital networking and machine communication, real-time data from parts and components in an Industry 4.0 environment can be sent to machine operators and systems, combined with data from other systems (such as ERP or CRM), and analyzed to predict optimal maintenance intervals. Predictive maintenance, or PM for short, can identify incipient faults before they occur, speed up processes and prevent production stops – or at least that is the expectation.

"Predictive maintenance is currently the most hotly discussed and scrutinized maintenance, repair and overhaul strategy," says Peter-Michael Synek, acting director of the fluid engineering association of the German Engineering Federation (VDMA). The hopes placed in PM are not unfounded, according to a recent study by the World Economic Forum and Accenture consulting, which estimates cost savings for planned repairs at twelve percent. Maintenance costs are lowered by almost 30 percent, according to the study, and unplanned downtime is 70 percent lower.

Pneumatics specialist Aventics, the Schaeffler Group and the telematics platform Openmatics, a subsidiary of ZF Friedrichshafen, previously addressed this trend at HANNOVER MESSE 2015, and Bosch Rexroth used its own Industry 4.0 demonstrator to show how condition monitoring with predictive maintenance can be integrated into the overall manufacturing process.

In 2016, the new Predictive Maintenance 4.0 exhibitor area is drawing more attention to this topic at HANNOVER MESSE. In a special event at the north end of Hall 17, specific solutions are being presented with the participation of Schaeffler, Aventics, Bosch Rexroth, Schmalz and ZF Friedrichshafen, among others. Alongside the Predictive Maintenance 4.0 special event with its showcases and live demos, special guided tours are also available. Participants can hear at the corporate stands how machine data is collected, processed and analyzed to give operators specific information about the condition of a component, system or machine.

Expert presentations in the Industrial Automation Forum on new concepts and solutions for predictive maintenance round out the package.