Oil and Gas is an asset-intensive industry, where maintenance of equipment is an essential exercise. The IoT data/ Sensor data from the equipment providing various data including temperature, pressure, RPM, vibration, flow, viscosity, etc. along with the historical maintenance data helps in predictive analytics.
The predictive analytics help to monitor and asses equipment health. This helps in taking proactive measures thus saving unnecessary downtime, thus increasing the overall productivity. ML techniques are used to identify meaningful patterns to generate new, actionable insights & trigger notifications leading to improving asset availability