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Smart Factory big data analytics platform collected massive amounts of test and measurement data to product actionable insights. One of these insights would be test and measurement anomalies that may be a prediction of deteriorating product quality that may be due to parts, process or people. And the industry may be oblivious to the serious challenges from ‘alert fatigue’. In this paper, we will highlight the desired outcome and performance of our proprietary anomaly detection algorithm and alert scoring machine learning model that automatically rates, categorizes and filters the anomaly alerts by severity of a potential quality incidence.