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The purpose of this study was to develop a product design model for estimating the impact toughness of low alloy steel plates. The rejection probability in a Charpy V test is predicted with process variables and chemical composition. Joint modelling of the mean and deviation was used in order to improve the results. The proposed method is suitable for the whole production line, including all grades of steel in production and it is not restricted to a few test temperatures. Using the proposed model the product design group could have recognised most of the rejections before production. Next, the developed model will be implemented into a graphical simulation tool that is in daily use in the product planning department and already contains some other mechanical property models. The model will guide designers in predicting the related risk of rejection and in producing desired properties in the product at lower cost. [ABSTRACT FROM AUTHOR]

In steel manufacturing, enormous amounts of data are gathered from many kinds of processes and it is difficult to distinguish useful knowledge from the resulting extensive databases. The recorded databases in the rolling process contain hundreds of features, and new methods are needed to reveal the novel and useful information. In the present study, the data from a hot strip rolling process were analysed in order to identify the rolling conditions in which some common defects, such as too thin or too narrow strip, do and do not occur. At the beginning, the dataset was reduced from its original size of over 200 features to 17% by using basic statistical analysis and linear correlation. After this, self-organising maps, parallel coordinates display, and k means clustering were used to find out the conditional probabilities of the common defect types. As a result, the method presented here revealed the rolling conditions for the four common defect types, i.e. coiling temperature close to the limits, too thin strip, too narrow strip, and torn tail end. Most important, the knowledge gained can be used to reduce the number of these defects. [ABSTRACT FROM AUTHOR]