4 Predictive Maintenance Technologies That Reduce Machine Downtime

Maintenance professionals are always looking to keep machines running at peak performance for as long as possible.

Predictive maintenance technology offers a simple way to decrease machine downtime—by using one or more sensors, computerized maintenance management system (CMMS) can receive and interpret the condition data of an asset to predict potential failures in real-time.

When the sensor readings exceed their defined thresholds, the CMMSs can automatically generate a work order and notify technicians to perform preventive repairs.

This facilitates “just-in-time” maintenance, which is shown to decrease machine downtime four times more effectively than other methods, according to a 2014 study by Plant Engineering.

Several condition-monitoring methods exist, such as infrared thermography, lubrication testing, ultrasound monitoring and vibration analysis. These methods can reveal potential failures in several types of machinery and are commonly used by maintenance crews to address problems before they cause costly downtime.

In the infographic below, we highlight the four most common predictive maintenance software technologies to help CMMS buyers choose the most appropriate methods for their assets.