Sead Spuzic and Kazem Abhary
The University of South Australia, Australia
Posters & Accepted Abstracts: J Appl Mech Eng
Hot rolling is amongst the most widely used manufacturing techniques. However, rolling mills are major resource consumers, and thus urgent rationalisations in the relevant industrial systems are required. 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 of industrial records. For this algorithms are developed that enable the generation of structured RPD databases. This novel structure is characterised by intelligently constructed hierarchy and universality of numerically defined variables. In addition, it allows for optimised invariance of the matrix components on the irrelevant features of the analysed rolling series. The variable hierarchy and matrix invariance enables extracting important RPD patterns relevant to the specific assortments of analysed rolling mill, and for comparing these patterns to more generic databases. Extracted statistical functions are then used for nonlinear optimisation of RPD parameters. An example of design of the leader oval groove for rolling wire rod is presented along with discussion of general mathematical aspects.
Email: Sead.Spuzic@unisa.edu.au