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Predictive maintenance is generally understood to mean the early anticipation and avoidance of an error in machinery or components thanks to data on their condition. This is possible with data-based methods that analyse the condition of your machines and help predict malfunctions, faults and also the time when maintenance work is required.
Industry 4.0 promises greater efficiency in production through networked machines, insights due to data analyses and better machine availability. In this context, predictive maintenance, i.e. a forward-looking maintenance process based on the evaluation of process and machine data, is a crucial component.
Unplanned downtime of production equipment costs money and cuts your profits significantly in the long run. What is certain is that machine and system failures pose a serious threat to the industrial sector. Predictive maintenance is intended to lead to cost savings compared to routine, interval- or time-based preventive maintenance as work is only carried out when necessary.
First of all, you need various sensors to record functionally relevant data on the machines, such as speed, temperature, noise level, bearing vibrations or power consumption. After that, a combination of real-time analysis technology and a database is required for the interpretation and meaningful evaluation of the sensor data. If all this is successful, it will be possible to fix the machine problem before it actually arises.
No; predictive maintenance is not only interesting for the manufacturing industry or associated MRO areas (maintenance, repair and operations), but also for all mobility offers - be it in the air, in vehicles or on rails. It is usually worthwhile for companies that use the same type of machine more often or that do not want to use predictive maintenance for their own production but for the machines they sell.
► What examples of predictive maintenance are there in practice?
In practice, it often makes sense to use predictive maintenance with machines where a breakdown would mean high sales losses or consequential damage. Modern machines are often already equipped with the necessary measuring sensors, older ones can be retrofitted. Here are a few examples:
► In which industries does predictive maintenance make the most sense?
Predictive maintenance is primarily used in industries in which the failure of systems, machines or components means significant consequential damage and failure costs:
