Find out how, in a project with Schwäbische Werkzeugmaschinen GmbH in the area of discrete manufacturing at automotive supplier Schabmüller, scrap and rework has been reduced by 85 % by means of Xplain Data algorithms.
Applying the Causal Discovery methods, previously unknown causes for production failures quickly became evident.
”Artificial Intelligence helps us to identify cause and effect relationships in complex data”, that is what Dr.-Ing. Mathias Kammüller, Chief Digital Officer and Board Member of Trumpf said after a successful project with Xplain Data. The mission of the project was to identify causes for machine failures based on data collected during assembly and operation of machines (root cause analysis). In continuation, the algorithms will now be deployed to constantly monitor for emerging new causes and alert related departments.
The project report was published in the quality management magazine QZ-online in August 2022 (German).
Discover how Siemens Motion Control in Erlangen revolutionized quality assurance in PCB production. By implementing Xplain Data’s Causal AI and ObjectAnalytics technology, the plant broke through the 5-Sigma barrier and achieved Six-Sigma quality levels. Learn how object-centric data analysis and root cause detection enabled a new era of manufacturing excellence.
Download the full story & discover how AI-driven insights can transform electronics manufacturing!
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