Predictive maintenance
Predictive maintenance
Predictive maintenance definition
Predictive maintenance (PdM) is a proactive maintenance strategy designed to detect anomalies and predict equipment failures before they happen. This process involves monitoring the condition and performance of equipment to reduce the chance something will fail. Predictive maintenance is primarily data-driven because it uses various forms of data monitoring, such as vibration analysis, thermal imaging, and oil analysis.
See also: structured prediction, predictive data mining
Predictive maintenance use cases
- Vibration analysis in industrial equipment. It’s important to notice wear and imbalance in industrial rotating machinery. To achieve this, you can install sensors that analyze vibration patterns.
- Thermal imaging in electrical Systems. Thermal cameras identify hotspots in electrical equipment and help recognize early signs of failure.
- Oil analysis in heavy machinery. Analyzing the oil for metal particles in engines and hydraulic systems can tell you a lot about the condition of the machine.
Benefits of predictive maintenance
- Reduced downtime. When failures can be predicted in advance, you can significantly reduce downtime because of a much lower rate of unexpected equipment breakdowns.
- Cost savings. Repairing equipment in time or scheduling major repairs in advance will significantly lower maintenance costs.
- Increased equipment lifespan. Regular maintenance based on actual equipment conditions can extend the life of your equipment.
- Improved safety. Most importantly, with fewer breakdowns, predictive maintenance enhances your workplace safety.