What is Predictive Maintenance?

Predictive maintenance is the use of data-driven maintenance methods that analyze the condition of plant and machinery and predict when maintenance actions should be performed. Predictive maintenance software uses data science and predictive analytics to estimate when a failure is likely to occur so that appropriate maintenance actions can be planned before the failure occurs.

Predictive maintenance and preventive maintenance are both proactive maintenance strategies that aim to minimize asset downtime and reduce maintenance costs. However, there is a fundamental difference between these two strategies.

Preventive maintenance is a scheduled maintenance strategy in which maintenance is performed on a regular basis, whether the plant needs it or not. The goal is to prevent breakdowns by replacing worn parts, performing routine inspections, and lubricating moving parts, among other things. The schedule for preventive maintenance is usually based on the manufacturer's recommendations or historical data on the plant.

Predictive maintenance, on the other hand, is a data-driven maintenance strategy that uses sensors, data analytics and algorithms to monitor assets in real time and predict when maintenance should be performed. This approach analyzes data on asset performance, such as vibration, temperature and pressure, to identify patterns that indicate potential failures. Predictive maintenance allows maintenance to be scheduled only when necessary, maximizing asset life and minimizing maintenance costs.

• Long-term cost savings

• Reduction of failures

• Increasing the service life of plants

• More complex than preventive maintenance

• Costs for additional systems

• Unplanned downtime possible