Predictive Maintenance with Operating Envelope Models

Predictive maintenance is emerging as a cornerstone of industrial operations, promising enhanced efficiency, reduced downtime and substantial savings. Earlier detection of change operating relationships and impending failures means more time to schedule maintenance and better opportunities to avoid expensive equipment damage by recognizing the developing fault much earlier.

Driving this transformation is the synergy between advanced sensor technologies and the Internet of Things (IoT). These form the backbone of data acquisition, acting as the eyes and ears on the plant floor. This provides realms of data that capture normal and abnormal operation, and allows models to be built.

This webinar focuses on Geometric Process Control and Envelope-based models, showing how using only historic data a model of normal operation can be built that alerts when the process relationships have changed outside their normal range, providing warning of potential upcoming faults and triggering maintenance. The sensitivity of these models delivers much earlier warning and allows more time to schedule predictive maintenance. The low-cost, low-time delivery of GPC models is ideal for bringing predictive maintenance to smaller pieces of equipment that we now have data for.

It’s all done by your engineers with data already captured and requires no specialist mathematics training. Come along to the webinar and we’ll show you how.