Improvement of tribological behavior of H-13 steel by optimizing the cryogenic-treatment process using evolutionary algorithms

The effect of soaking temperature and duration of cryogenic treatment cycles were investigated for the hot die steel AISI-H13 to improve its wear resistance. The amount of wear, average friction coefficient, and maximum local contact temperature were investigated against the AISI D3 cold work tool steel (hardened and tempered) used as counter-surface for five conditions varying the loading and sliding speed. Sliding parameter has great influence over wear rate when is compared to load effects. The wear detected on the surface analyzed is adhesive wear produced by deformation lips, surface cracks and fractured ridges. To achieve an increase of efficiency, Particle Swarm Optimization is preferred as it showed lower deviation than Bacteria Foraging Optimization in optimized results.