Customers have increasingly high expectations of steel producers regarding production costs and product quality. Alongside many other criteria, a main focus is the demand to reduce the amount of defective products delivered. The following approaches may be taken to achieve this goal:

• Recording and monitoring product quality features to the greatest possible extent and using this information for process optimisation;
• Rapid identification of the root causes of quality defects;
• Monitoring of the main parameters in the production process to detect changes (medium and long term uni-variate and multi-variate SPC);
• Aggregation and analysis of product quality and process data for decision support when allocating material or assessing plants.

All the stated approaches are based on the analysis of measured quality and process information. To exploit the potential of these approaches, an extensive data base is required. It must include the information stated above, prepared in a suitable way. Since these data have to be recorded along the entire process chain from the melt shop through to the finished product, the quality and process database must be designed to span all these process stages.