Predictive maintenance, also known as PdM, is a maintenance strategy that uses machine learning algorithms trained with Industrial Internet of Things (IIoT) data to make predictions about future outcomes, such as determining the likelihood of equipment and machinery breaking down.
Using a combination of data, statistics, machine learning and modeling, predictive maintenance is able to optimize when and how to execute maintenance on industrial machine assets. Through this predictive analysis, PdM helps avoid costly repairs, as well as maximize the utilization and availability of the equipment in service.
Predictive maintenance takes into account estimated service intervals, as well as data-driven insights based on the measurement of operating conditions to monitor and diagnose equipment issues in real time. As a result, it catches anomalies in automated operations before they become major challenges that could impact the business. In most cases today, the objectives of predictive maintenance programs can be boiled down to improved production, maintenance and operational efficiency.
Predictive maintenance is becoming increasingly important because of its efficiency in isolating and identifying system, production and other failures before they occur, thus decreasing downtime and waste. Monitoring is made easier through the use of sensors, which can keep tabs on things like machine conditions, and sensor data that pairs with traditional log data from databases and cloud storage systems for advanced insight into a combined technical infrastructure. This creates a pool of archived data, creating opportunity for the analysis of machine data for diagnostic and maintenance purposes. The ability to discover patterns and signals from sensor data enables organizations to look around corners, apply maintenance strategies at the right time and ultimately predict the next equipment failure or catastrophic event.
In this article, we’ll discuss maintenance in general, different types of maintenance strategies and additional resources on predictive maintenance.