Understanding asset health is necessary to optimizing maintenance activities and preventing critical failures. However that often means sorting through staggering volumes of data to find small variations in normal operating parameters. This is where the rise of AI and Machine Learning play a part, in helping to analyze massive data stores to find trends and cues that may indicate abnormal behavior leading to a failure.
Asset Performance Analytics solutions utilize both pre-set conditions and variable machine learning to trigger action for possible issues related to asset operations. These tools augment existing alarm capabilities found in traditional HMI and SCADA applications to narrow in on signals that may be missed by simple threshold alerts.
Helps organizations gain the highest return on critical assets by supporting predictive maintenance programs with early warning detection of equipment issues ahead of existing operational alarms.
Create conditional alerts in real-time, providing early failure detection and driving appropriate actions to increase asset availability, reduce costs and avoid unnecessary maintenance and downtime.