To reduce unexpected equipment failures, unplanned maintenance activities, and outage time, UT Austin chose HanAra Software’s HanPHI™ solution as its condition-based predictive monitoring solution.
KOGAS strives to minimize risk throughout the process from gas production to supply by constantly running safety diagnostics and emergency drills, but its existing plant information system data infrastructure did not help KOGAS improve its safe and efficient operation.
As systems and equipment in process plants become more complex and sophisticated, gaining actionable intelligence from the vast amount of generated data has become one of the key success factors. Extracting accurate and meaningful information from the data helps KOEN achieve operational excellence.
The high variability of the electricity generating capability hourly, daily, and seasonally exposes wind farms to frequent equipment failures and operational inefficiencies. In order to alleviate concerns of wind station capabilities, Yeong-Am needed a solution to improve operations and reduce inefficiencies.