Defect prevention with predictive maintenance

Solution Idea

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Learn how to use Azure Machine Learning to predict failures before they happen with real-time assembly line data.

This solution is built on the Azure managed services: Azure Stream Analytics, Event Hubs, Machine Learning Studio, Azure Synapse Analytics and Power BI. These services run in a high-availability environment, patched and supported, allowing you to focus on your solution instead of the environment they run in.


Architecture Diagram Download an SVG of this architecture.


  • Azure Stream Analytics: Stream Analytics provides near real-time analytics on the input stream from the Azure Event Hub. Input data is filtered and passed to a Machine Learning endpoint, finally sending the results to the Power BI dashboard.
  • Event Hubs ingests raw assembly-line data and passes it on to Stream Analytics.
  • Machine Learning Studio: Machine Learning predicts potential failures based on real-time assembly-line data from Stream Analytics.
  • Azure Synapse Analytics: Synapse Analytics stores assembly-line data along with failure predictions.
  • Power BI visualizes real-time assembly-line data from Stream Analytics and the predicted failures and alerts from Data Warehouse.

Next steps