Predictive maintenance is a state-of-the-art approach to maintenance enabled by the newest technologies, like the Internet of Things (IoT), maintenance software, and AI.
Predictive maintenance relies heavily on data, particularly data from intelligent sensors, based on which it anticipates future equipment malfunctions. This approach allows organizations to master timely maintenance scheduling, minimize downtimes, and prolong equipment lifespan.
How does predictive maintenance work?
The general principle usually includes:
- Data collection from sensors
- Data analysis (mostly with the help of software)
- Using the analysis results to schedule maintenance (often automatically)
What is the difference between predictive, proactive & condition-based maintenance?
Predictive maintenance is closely related to other maintenance approaches. Along with preventive maintenance, predictive maintenance is one of the main ways of proactive maintenance.
Terms predictive maintenance and condition-based maintenance (CBM) are sometimes used interchangeably, although technically they slightly differ. Whereas CBM focuses on signals of an ongoing problem with a device, predictive maintenance uses similar data to forecast oncoming problems with the machine (i.e., it is more future-oriented).