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Diagnostic Analytics for Operational Excellence
A Multi-Site Renewable Energy Company
Problem
Impossible to review the millions of records gathered by their SCADA supervisory system.
Among these records are valuable insights about operational failures that are difficult to identify with so much data.
Hundreds of highly complex signals hide the genuine root cause of failure, making it difficult for humans to identify.
Action
Built Machine Learning (ML) and advanced statistics models for data driven diagnostic analysis
Developed powerful visualizations to tell the story of what happened and to reveal the root causes of failures with efficiency and clarity
Trained management for continuous re-training to increase efficiency and accuracy over time
Tool Stack
Python, Azure (Data Factory, Machine Learning Studio, Power BI)
100
+
Signals Processed
35
B+
Billions of Records
90
%+
Accuracy of Root Cause Detection