Analyze operational data and visualize the results to help reliability engineers proactively identify and manage asset reliability risks that could adversely affect plant or business operations.
Identify which assets are over-, under- or well-maintained. Use prescriptive analytics to recommend optimum maintenance schedules with the goal of better utilization of maintenance resources.
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.
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.