Predictive maintenance is particularly important in the areas of Industry and Factory 4.0, automation and artificial intelligence. The aim of predictive maintenance is to predict machine failures before they actually happen. This avoids expensive repairs and unplanned downtime.
To this end, machines are equipped with sensors that measure temperature, vibrations or noise, for example. This data is continuously collected and analysed with the help of artificial intelligence. The analysis shows when a part is likely to fail - so maintenance can be carried out in a targeted and timely manner.
Imagine a factory using predictive maintenance for its production machines. Thanks to the data collected, the system recognises at an early stage that an engine is vibrating abnormally. The engineering department can rectify the problem before the motor fails and production stops. This saves time, reduces costs and increases reliability.
Predictive maintenance therefore helps companies to keep their systems running efficiently and safely. Predictive maintenance is an important component of modern, digitally controlled production.
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