Hot rolling is among the most widely used
manufacturing techniques. However, rolling mills are major
resource consumers; thus, urgent rationalisation is required in
the relevant industrial systems. Roll pass design (RPD) is a
principal factor that determines process efficiency, product
quality and resource consumption. Therefore, it is important
to optimise RPD including the selection of roll materials. New
avenues for optimising RPD are to be found by extracting
knowledge buried in the vast repository of industrial records.
The extracted statistical functions are then used for the nonlinear
optimisation of RPD parameters. The design of a leading
oval groove for rolling a wire rod is presented as an example,
along with a discussion of the general mathematical
aspects. The presented case analysis shows how regression
analysis and the probability density function (PDF) are used
to define principal dimensions—height and width—for the
leading oval groove. These two dimensions are inferred following
the logic of probabilistic design, and are based on an
understanding of the trend in groove contour changes, which
occur due to surface wear during rolling campaigns.