Pilot Application 6: Root Cause Analysis of Quality Deviations in Steel Rolling Processes<\/h2><\/div>\n\nAnalysis of the Causes of Quality Deviations and Complex Process Chains<\/p>\n<\/div>\n
\n<\/h2>\n<\/div>\n<\/div>\n\n<\/h2>\n<\/div><\/h4><\/div><\/div><\/div><\/div><\/div>Starting Point<\/h3><\/div><\/div><\/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<\/div><\/div><\/div>
![](\"https:\/\/humaine.info\/wp-content\/uploads\/2026\/07\/Pilot-6.bmp\" "\\"Pilot")
<\/span><\/div><\/div><\/div>Approach<\/h3><\/div>\nIn this pilot application, an AI assistance system was developed that automatically analyzes existing data and detects the causes of deviations from normal conditions. In developing the AI assistance system, it was necessary to incorporate the expertise of domain experts and to develop an appropriate workflow to ensure reliability in the cross-domain use of data and knowledge. <\/p>\n<\/div>\n<\/div><\/div><\/div><\/div><\/div>
\n\nAnalysis of the Causes of Quality Deviations and Complex Process Chains<\/p>\n<\/div>\n
\n<\/h2>\n<\/div>\n<\/div>\n\n<\/h2>\n<\/div><\/h4><\/div><\/div><\/div><\/div><\/div>Starting Point<\/h3><\/div><\/div><\/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<\/div><\/div><\/div>
<\/span><\/div><\/div><\/div>Approach<\/h3><\/div>\nIn this pilot application, an AI assistance system was developed that automatically analyzes existing data and detects the causes of deviations from normal conditions. In developing the AI assistance system, it was necessary to incorporate the expertise of domain experts and to develop an appropriate workflow to ensure reliability in the cross-domain use of data and knowledge. <\/p>\n<\/div>\n<\/div><\/div><\/div><\/div><\/div>
Analysis of the Causes of Quality Deviations and Complex Process Chains<\/p>\n<\/div>\n
<\/h2>\n<\/div>\n<\/div>\n\n<\/h2>\n<\/div><\/h4><\/div><\/div><\/div><\/div><\/div>Starting Point<\/h3><\/div><\/div><\/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<\/div><\/div><\/div>
<\/span><\/div><\/div><\/div>Approach<\/h3><\/div>\nIn this pilot application, an AI assistance system was developed that automatically analyzes existing data and detects the causes of deviations from normal conditions. In developing the AI assistance system, it was necessary to incorporate the expertise of domain experts and to develop an appropriate workflow to ensure reliability in the cross-domain use of data and knowledge. <\/p>\n<\/div>\n<\/div><\/div><\/div><\/div><\/div>
<\/h2>\n<\/div><\/h4><\/div><\/div><\/div><\/div><\/div>Starting Point<\/h3><\/div><\/div><\/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<\/div><\/div><\/div>
<\/span><\/div><\/div><\/div>Approach<\/h3><\/div>\nIn this pilot application, an AI assistance system was developed that automatically analyzes existing data and detects the causes of deviations from normal conditions. In developing the AI assistance system, it was necessary to incorporate the expertise of domain experts and to develop an appropriate workflow to ensure reliability in the cross-domain use of data and knowledge. <\/p>\n<\/div>\n<\/div><\/div><\/div><\/div><\/div>
Starting Point<\/h3><\/div><\/div><\/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<\/div><\/div><\/div>
<\/span><\/div><\/div><\/div>Approach<\/h3><\/div>\nIn this pilot application, an AI assistance system was developed that automatically analyzes existing data and detects the causes of deviations from normal conditions. In developing the AI assistance system, it was necessary to incorporate the expertise of domain experts and to develop an appropriate workflow to ensure reliability in the cross-domain use of data and knowledge. <\/p>\n<\/div>\n<\/div><\/div><\/div><\/div><\/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<\/div><\/div><\/div>
<\/span><\/div><\/div><\/div>Approach<\/h3><\/div>\nIn this pilot application, an AI assistance system was developed that automatically analyzes existing data and detects the causes of deviations from normal conditions. In developing the AI assistance system, it was necessary to incorporate the expertise of domain experts and to develop an appropriate workflow to ensure reliability in the cross-domain use of data and knowledge. <\/p>\n<\/div>\n<\/div><\/div><\/div><\/div><\/div>
In this pilot application, an AI assistance system was developed that automatically analyzes existing data and detects the causes of deviations from normal conditions. In developing the AI assistance system, it was necessary to incorporate the expertise of domain experts and to develop an appropriate workflow to ensure reliability in the cross-domain use of data and knowledge. <\/p>\n<\/div>\n<\/div><\/div><\/div><\/div><\/div>
![](\"https:\/\/humaine.info\/wp-content\/uploads\/2021\/05\/Logo_Betriebsforschungsinstitut-GmbH-BFI-150x150.jpg\"){kind=logo}
<\/a><\/span><\/div>![\"Norbert](\"https:\/\/humaine.info\/wp-content\/uploads\/2021\/09\/avatar-1577909_1280.png\"){kind=avatar}
<\/div><\/div>![\"Jens](\"https:\/\/humaine.info\/wp-content\/uploads\/2021\/09\/Brandenburger-Jens1.jpg\")
<\/div><\/div>![](\"https:\/\/humaine.info\/wp-content\/uploads\/2021\/06\/Logo_IAW.jpg\"){kind=logo}
<\/a><\/span><\/div>![\"Prof.](\"https:\/\/humaine.info\/wp-content\/uploads\/2022\/05\/C_Meske.jpg\")
<\/div><\/div>![\"Prof.](\"https:\/\/humaine.info\/wp-content\/uploads\/2023\/02\/Wilkens_2022_quadrat_copyright.jpg\")
<\/div><\/div>![\"Dr.](\"https:\/\/humaine.info\/wp-content\/uploads\/2021\/09\/Langholf-Valentin.jpg\")
<\/div><\/div>![](\"https:\/\/humaine.info\/wp-content\/uploads\/2021\/05\/Logo_Institut-fuer-Neuroinformatik-INI-e1776420901676.jpg\"){kind=logo}
<\/a><\/span><\/div>![\"Prof.](\"https:\/\/humaine.info\/wp-content\/uploads\/2021\/06\/laurenz_wiskott-attr.jpg\")
<\/div><\/div>![\"Prof.](\"https:\/\/humaine.info\/wp-content\/uploads\/2021\/09\/Glasmachers-Tobias.1jpg.jpg\")
<\/div><\/div>