A good Asset Management program requires some time-based activities, such as filter changes and lubrication events. The challenge is in performing scheduled maintenance activities on time to keep a low-risk profile. Skipping or deferring maintenance items will increase problems over time. In Hydro Generation, if air cooler fouling is left untreated, daily operations can be impacted. Machine Learning (ML) models can provide system alerts and machine or system anomalies to assist with root cause investigations. This series of posts will look at these issues using AI/ML for these types of anomalies that are specific to Hydro Generation.
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