Goals

With the help of predictive analytics, a company can achieve higher profitability. The following factors ensure :

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• Reduction of downtimes

• Increase in system availability

• Reduced cost of unplanned outages

• Increasing the lifespan of machines through regular maintenance

• Perfect time for maintenance: The fact that machine data is recorded continuously means that the best time for maintenance can be determined and integrated into the process.

• Higher productivity: Improve machine performance by analyzing data

Predictive Analytics

Predicitive analytics collects machine and process data and evaluates it in real time.

In particular, the technology measures data on vibration, pressure, temperature and similar factors. These current machine data in combination with historical data result in patterns in the operating parameters. These in turn make it possible to predict the service life or optimize the machine. The maintenance engineer can thus be informed before a problem occurs. Predictive maintenance prevents unforeseen failures.

Measure and

monitor measured values

Depending on the material, operating and environmental conditions, measured values may deviate from the ideal operating conditions. In order to reach the right conclusions about the optimization of the machine performance or the need for service work, the cluster analysis provides reliable statements taking into account certain influencing factors to preventively prevent possible failures.

Vibration monitoring to prevent failures

Depending on the material, operating and environmental conditions, measured values can deviate from the ideal operating conditions. In order to get the right conclusions about the optimization of the machine performance or the need for service work, the cluster analysis provides reliable statements taking into account certain influencing factors

preventively prevent possible failures.

Carry out maintenance at the right time

Depending on the material, operating and environmental conditions, measured values can deviate from the ideal operating conditions. In order to reach the right conclusions about the optimization of the machine performance or the need for service work, the cluster analysis provides reliable statements taking into account certain influencing factors to

preventively prevent possible failures.

Thanks to the intelligent data analysis of industrial analytics, it can be precisely predicted whether and when maintenance of machines or systems will become necessary. This will enable you to plan repairs with the right spare parts in advance, reduce downtimes and save unnecessary costs.