Industrial Internet of Things (IIoT) Journey Reducing Scrap

Industrial Internet of Things (IIoT) Journey – Reducing Scrap:

A large North American plant we work with had to reduce the amount of scrap they were generating to 2%.

Not an easy task, right?

By using Azure Machine Learning we helped them to create models with historical sensor data, which were then used on real-time sensor data to predict scrap. 


We worked with them to build a predictive machine learning solution with Azure Machine Learning, Azure IoT Hub, Azure Stream Analytics, and Power BI.  Azure Iot Hub consolidates sensor data from an on-premises system. Azure Stream Analytics formats data for storage and passes it to Azure Machine Learning for prediction modeling. Then Power BI displays real-time production dashboards of sensor data and live prediction results to operators.

As you read this, these solutions are live in one plant and are being rolled out to a second. The remaining three U.S. plants will follow. 

Once this solution is rolled out to all five plants, this customer expects to save $2 million at EACH PLANT annually through predictive scrap reduction. They are already seeing 6-7% increase in yield at the first plant.

We got our 2%.

Check out our case study in this video: