Helps prevent problems before they occur by forecasting imminent issues and initiating appropriate responses to avoid run-to-failure situations
Avoids unnecessary preventative maintenance. Able to detect something is wrong and schedule maintenance before failure based on early warnings of pending asset failure
Employ machine learning to identify operational factors that positively and negatively affect performance. Use this information to improve maintenance practices to attain greater asset reliability.
Ingest, aggregate and analyze a wide range of operational data– sensors, SCADA, telemetry, environmental, work order history – to develop models that identify potential asset degradation or failure.
Designed to analyze operational data and visualize the results to help maintenance managers identify and manage asset reliability risks that could adversely affect plant or business operations.
SaaS solution avoids added IT infrastructure costs; attractive to SMB and large enterprises; enables faster implementation; allows asset-intensive organizations to realize analytics benefits sooner.