Predictive maintenance is a proactive maintenance strategy that uses condition monitoring tools to detect various deterioration signs, anomalies, and equipment performance issues. Based on those measurements, combining IIoT and machine learning, the organization can run algorithms to estimate when a piece of equipment might fail so that maintenance work can be performed just before that happens.
The goal of predictive maintenance is to optimize the usage of maintenance resources. By knowing when a certain part will fail, maintenance managers can schedule maintenance work only when it is actually needed, simultaneously avoiding excessive maintenance and preventing unexpected equipment breakdown
The predictive maintenance is suggested for companies that would like to improve the efficiency of their production equipment. This type of maintenance offers large cost savings because it finds in advance the failures and allows to save production time through early planning.
Through this approach, maintenance interventions are planned punctually: interventions are executed exactly when required, a few moments before a machine failure.
This approach may be strategic if:
Brick Reply™ is the innovative platform allowing to take under control the whole maintenance process. With Brick Reply™ it will be possible to predict maintenance intervention for sensorized and strategical machines, but also to schedule a maintenance plan for not sensorized machined that are critical for production and performing corrective maintenance on other equipment.