Reduce unexpected equipment failures with Optimum VĪS™
Predictive Maintenance, a fine-grained, non-intrusive equipment monitoring system.
Using Machine Learning and Predictive Analytics, Optimum VĪS™ learns nominal equipment signatures leveraging data like power draw, vibration and temperature. When variations to these norms are detected, Optimum VĪS™ alerts operations personnel of potential issues and predicts what behavior may be expected, and when it may occur. These advanced alerts facilitate scheduled maintenance during off-peak periods, avoiding emergency downtime and operational losses.
A recent study by McKinsey & Company published in the McKinsey Quarterly found "Sensor data that are used to predict when equipment is wearing down or needs repair can reduce maintenance costs by as much as 40 percent and cut unplanned downtime in half."
Your Assets Are Talking. Are You Listening?