Predictive Maintenance Predictive maintenance really boosts overall equipment effectiveness

Capitalize on Industry 4.0 by using predictive maintenance

Everybody’s talking about it, most want it and yet no one shares the same understanding: Predictive maintenance is a proactive, forward-looking maintenance strategy employed at just the right time to reduce costly downtime. With its approach, predictive maintenance goes one step further than condition monitoring. The goal of condition monitoring is to oversee the state of a machine or system — that is, its current state. Predictive maintenance uses AI methods to calculate, interpret and forecast the machine or system’s future behavior on the basis of its historical and current condition — an intelligent early-warning system that’s always looking ahead.

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Your benefits

Precise forecast for the optimum maintenance time

Lower maintenance and personnel costs

Increased machine and system availability

Preventative avoidance of faults

Reduced machine failures and downtimes

Optimized spare-part management

Predictive maintenance from real-world use

The optimum time to carry out maintenance is determined on the basis of predicting the long-term development of key variables over time — variables such as a machine’s performance or its oil quality. Knowing the optimum maintenance time lowers costs. After all, spare parts are there on time, replacements have already been scheduled and costly downtimes are prevented.


Thanks to predictive maintenance from USU, you benefit from a future-oriented approach to maintenance that strategically integrates operational experience and real-time data related to a machine’s condition as well as machine management and planning.

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Use Cases

Man with Tablet and Machines

Condition Monitoring

Real-time information ensures machine efficiency
Worker at the laptop between machines

Predictive Quality

Avoid costly rejects long before they happen
Two man at the screen

Machine Fingerprint

Know the precise status of a machine, even in a heterogeneous production environment
White Paper

Successfully develop data-driven services

Practical guide with important implementation tips for Industrie 4.0 services

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