Latest Developments on AI-Controlled Product Changes at Cold Rolling Mills That Significantly Improve Performance

This paper describes how an expert system automatically calculates the optimum strategy for all product changes, i.e., the optimum combined method of operation from the technology clusters such as strip flatness or thickness. The next step, therefore, is to supply digital AI systems to provide a forecast for the optimal product change strategy. This presentation shows the latest developments on how artificial intelligence provides a sufficient hit rate in its prediction; it generates commands for the automation to add value regarding an improved off-gauge length for strip flatness and thickness and increased product change stability.

Authors:

Mr. Joern Sieghart | SMS group
 

Mr. Klaus Pronold | SMS group GmbH
 

Christian Pfeifer | SMS group
 

Rachid Barkouta | SMS group
 

Session Chairs:

Bryan Beard | TMEIC Corporation Americas
 

Jim Hendrickson | NWI Automation