Expectations for today's advanced enterprise asset management (EAM) systems are expanding to include expanded connectivity and predictive capabilities similar to capabilities desired in asset performance management systems. These capabilities are key to identifying and addressing problems before they occur and help to improve operational effectiveness and minimize downtime. Digital transformation in all forms, and particularly Industrial IoT (IIoT ), edge computing, and analytics, have opened new opportunities for improving the efficiencies and productivity of today's maintenance and operations functions.
Assessing asset condition and performance with predictive maintenance and predictive analytics helps to reduce and often prevent unplanned downtime and improve asset reliability. Intelligent, data-driven maintenance extends the scope to include real-time information from assets using IIoT and edge devices. With well-managed business processes to anticipate and respond to alerts, repairs are performed on equipment when needed and before degradation occurs. These critical business processes include managing maintenance activities and converting high-priority alerts into work orders to execute the appropriate inspection, maintenance, and repair, ideally before failure.