ABB has introduced a new Asset Optimization software package for high-voltage circuit breakers.
With Asset Optimization, information from many types of breakers – including DTB, LTB, GCB & GIS – is quickly collected, aggregated, analyzed and compared to historical data to provide advanced notice of degrading performance and impending failure of breakers. Comprehensive workflow processes extend from condition monitoring in the circuit breaker to Enterprise Asset Management applications such as Computer Maintenance Management Systems (CMMS.)
“ABB has designed Asset Optimization software to significantly increase process uptime while reducing maintenance costs through early detection of asset performance problems and optimized remediation work processes,” said Jeff Barker, ABB global business development manager for high-voltage circuit breaker monitoring. “This system feature exploits high voltage circuit breaker information to assess and report equipment conditions in real-time to reduce what our customers have told us is costly corrective and preventive maintenance by optimizing maintenance work flows.”
This condition-based monitoring solution also helps prioritize managing a fleet assessment of SF6 breakers to determine corrective actions, thus vastly simplifying the accounting of a breaker’s SF6 usage.
Asset Optimization System maintenance management features make information within the CMMS (Computerized Maintenance Management System) transparently accessible to maintenance personnel. Seamless, context-sensitive interaction is provided through standard CMMS displays, such as active work orders, work order, history, preventive maintenance schedules, and available spare parts.
Asset optimization’s unique engineering environment manages one set of consistent data, which enables single-point change management and configuration; this eliminates the risk of inconsistencies between multiple databases and the need to duplicate engineering effort.
Asset Optimization’s asset monitors use real-time information as inputs to detect health and performance conditions before failure occurs, assist in the diagnosis of the problem, and offer correction recommendations. These vary in complexity from simply identifying status changes in an intelligent device to identifying abnormal conditions using advanced monitoring applications.