The trade-off between corrective and preventive maintenance of assets is a difficult one: How do you ensure that maintenance is not carried out too early or too late, resulting in possible extra costs or damage? Predictive Maintenance can offer a solution. In this whitepaper, we would like to take you through the techniques behind predictive maintenance and the conditions to implement it.
Predictive maintenance
Predictive maintenance is predicting the right moment of maintenance based on data. The techniques behind predictive maintenance help determine the condition of assets. Data from the maintenance process plays a major role in this. Based on this data, it can be predicted when products, devices or machines need maintenance. This has several advantages: the availability of these assets is increased, maintenance costs are reduced and the use of asset data provides more insight into the production process itself.
The asset data underlying predictive maintenance is collected through the use of sensors. These sensors can be configured to your needs: at which values assets function properly, at which values action should be taken and at which values defects occur. The sensors record the current values and when these values are approached, the user receives a signal. This provides insight into when an asset needs maintenance or repair.
Application
Predictive maintenance can be used in numerous sectors and is basically applicable to anything that can be set in motion electrically or mechanically. This makes it an interesting method of maintenance for (rail) infrastructure, process engineering environments, regular building maintenance and others. But predictive maintenance can also be a solution for ICT-related systems. You can download the whitepaper below.
