Optimisation of high-speed steels chemical composition using the artificial intelligence methods

The main goal of the research carried out was developing the design methodology for the new high-speed steels with the required properties, including hardness and fracture toughness, as the main properties guaranteeing the high durability and quality of tools made from them. It was decided that hardness and fracture toughness KIc are the criteria used during the high-speed steels design. In case of hardness, the statistical and neural netw chemical composition and its heat treatment parameters, i.e., austenitizing- and tempering temperatures. In the second case - high-speed steels fracture toughness, the neural network model was developed, makin it possible to compute the KIc factor based on the steel chemical composition and its heat treatment parameters. The developed material models were used for designing the chemical compositions if the new high-speed steel, demonstrating the desired properties, i.e., hardness and fracture toughness. Methodology was developed to this end, employing the evolutionary algorithms, multicriteria optimisation of the high-speed steels chemical composition.