Success Story

reading time: 2 min

Manufacturing

Material Industries

Anomaly Detection

Industrial Software

Context

Our customer produces surfaces and coverings. As a manufacturer, the enterprise had multiple sensors generating data from machines and other systems, but no means of storing or calling off the data from a centralized channel.

Challenge

The challenge was to set up the necessary data infrastructure as well as to make it scalable in order to potentially expand it. This was crucial, since the “end result” was not clearly defined by the client yet.

Assignment

Our task was to process the data in Azure, pre-process it and store the final result in a database while making it accessible via a dashboard.

Solution

The infrastructure was created in Azure (Data Factory functions, Data Lake Storage Gen2) and Timescale DB was also used.

Our scalable approach minimizes waste, fosters improvement, and enhances product quality using sensor data.

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three male team members of craftworks at a meeting table looking at laptops and working

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