ThyssenKrupp Rasselstein GmbH (Andernach, Germany):

Nörtesheuser M., Mag. Eng., Quality Assurance System, e-mail: michael.noertesheuser@thyssenkrupp.com

VDEh Institute of Industrial Researches GmbH (Düsseldorf, Germany):

Brandenburger J., Mag. Math., Head of Engineering Group, Quality and Information Technics

Tata Steel (Ijmuiden, Netherlands):

Jonker K., Mag. Eng., Principal Researcher, Research and Development

voestalpine Stahl GmbH (Linz, Austria):
Kogler A., Mag. Inf., Cold Sheet and Coating, TKQ Quality Department

Salzgitter Flachstahl GmbH (Salzgitter, Germany):
Krätzner M., Mag. Eng., Head of Competence Area Surface Coating Inspection System

ThyssenKrupp Steel Europe AG (Duisburg, Germany):
Miβmahl W., Mag. Eng., Technology and Innovation, Surface Coating Measuring Technics

VDEh Steel Institute (Düsseldorf, Germany):
Moninger G., Mag. Eng., Head opf ZPF and Measuring Technics Department

The detection and documentation of surface defects in the production of steel strip is crucial to deliver a high quality product to the customer and essential for the optimization of production processes through direct conclusion on the origin of the error. For this reason Surface Inspection Systems (SIS) are used by all the leading steel producers in various stages of their production. SIS have for some years been a tightly integrated tool for monitoring the quality of the steel surface and to support the quality assurance. Surface inspection system at the continuous pickling line at Salzgitter Flachstahl GmbH is presented. Detection settings and their effects on the classification performance are examined. Aberration over the bandwidth and displacement between two inspection angles because of thickness variations are analyzed. Examples of „Artificial Defects“, such as shell, hole, scratch, welding seam with hole, geometrical forms are observed as well as density distribution of defects A and B from image library and density distribution of defects A and B from inspection results. Inspection result of the same side with slightly different classifiers allowed to distinguish the surfaces with some critical defects and with many critical defects. Data sources for statistical monitoring and analysis are generalized.