{"id":4717,"date":"2021-09-12T10:14:17","date_gmt":"2021-09-12T10:14:17","guid":{"rendered":"https:\/\/humaine.info\/pilot-applications\/root-cause-analysis-of-quality-deviations-in-steel-rolling-processes\/"},"modified":"2023-10-24T12:55:18","modified_gmt":"2023-10-24T12:55:18","slug":"root-cause-analysis-of-quality-deviations-in-steel-rolling-processes","status":"publish","type":"page","link":"https:\/\/humaine.info\/en\/pilot-applications\/root-cause-analysis-of-quality-deviations-in-steel-rolling-processes\/","title":{"rendered":"Root Cause Analysis of Quality Deviations in Steel Rolling Processes"},"content":{"rendered":"

Pilot 6:<\/b>
\nRoot cause analysis for quality deviations and complex process chains.<\/p>\n<\/div>

Partner<\/p><\/h2><\/div>

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Description<\/p><\/h2><\/div>

The high quality of products is very important for manufacturers of flat steel products in European and international competition. The work intensity of the employees responsible for the production process and product quality is correspondingly high. They must consider a very large amount of information (process data, quality data, the customer’s intended use, complaints, information from the starting material) to be able to identify and eliminate the causes of deviations quickly and in a targeted manner. Specialists from a range of disciplines work together to identify the causes of problems and resolve them as quickly as possible.<\/p>\n

In this pilot application, an AI assistance system will be developed that automatically analyses the available data and identifies the causes of deviations from the normal state. For the development of the AI assistance, the knowledge of the domain experts has to be taken into account and an appropriate workflow has to be developed for reliability in case of cross-domain use of data & knowledge.<\/p>\n

Method development:<\/p>\n