Applying MLOps to Industrial Water Pump Anomaly Detection
How MLOps can be used to address this problem by connecting the different stages of the machine learning lifecycle into one automated pipeline. The real challenge is spotting unusual operating conditions early. When sensor data is monitored manually, changes in pump behaviour can be easy to miss, especially as the volume of data grows. If those changes aren’t noticed in time, a developing equipment issue may be harder to catch before it becomes a larger problem. That’s the problem we wanted to address with our water pump anomaly detection pipeline.