Virtual rolling quality system for cold rolling

Jari Larkiola, Jari Nylander, Martti Verho, Mika Judin

Research output: Contribution to journalArticleScientificpeer-review


A prototype of virtual rolling quality system for a 4 stands cold rolling process is created. In this system virtual sensors and models are used to calculate quality features based on process information and analyzed history data. The virtual-sensor technology is developed for estimating of hard-to-measure variables and further on to define methods to automatically detect and hierarchically classify deviations in rolling values and strip quality related to thickness, flatness, profile, etc. The analysis of the process data is done by means of classical rolling theories, statistical methods and databased methods such as artificial neural networks to identify and quantify the main effects on strip quality. The flatness and hot strip thickness profiles are decomposed into independent components by means of Chebyshev polynomia coefficients. The strip quality related measurements are also collected to the appropriate extent from up- and downstream processing lines.
Original languageEnglish
Pages (from-to)170-173
JournalSteel Research International
Issue number9, Proceedings
Publication statusPublished - 2010
MoE publication typeA1 Journal article-refereed
Event13th International Conference on Metal Forming - Toyohashi, Japan
Duration: 19 Sept 201022 Sept 2010


  • Cold rolling
  • Modelling
  • Friction
  • Monitoring
  • Setup calculations
  • Classification


Dive into the research topics of 'Virtual rolling quality system for cold rolling'. Together they form a unique fingerprint.

Cite this