Otimizacao do processo de reuso do cavaco do aco Vanadis ® 8 pela rota da metalurgia do pó, utilizando a moagem de alta energia

Abstract

Tool steels produced by powder metallurgy, such as Vanadis® 8, stand out due to their excellent mechanical properties, making them suitable for applications in cutting tools, punches, and dies. However, the chips obtained from machining this material are sold as scrap to companies that use remelting, an inefficient method due to non-uniform cooling, which promotes the coarse formation of carbides and compromises the material’s microstructural properties. Therefore, the objective of this work is to utilize a new optimization algorithm called the multi-objective algorithm of Lichtenberg to determine the best parameters for the high-energy milling (MAE) and sintering processes, with the aim of making the reuse of this material economically viable. The response surface methodology, a statistical technique used to model and optimize processes, was employed to generate metamodels with the equations. The milling parameters used were 300–400 rpm, a ball-to-weight ratio of 1:15, and a duration of 12–50 hours. To validate the model, microstructural characterization analyses, such as SEM, XRD, and laser diffraction, were performed. The responses analyzed included particle size, particle distribution, and mill energy consumption. The metamodel exhibited an overall error of 6.82% when compared to the confirmation experiment. The milling results showed that it is possible to save up to 26 process hours with the optimization and obtain powders of excellent quality for subsequent processes, such as compaction and sintering. For the sintering process, the parameters used were 1200-1300 ◦C and 1-2 hours. The evaluated responses were apparent density, furnace energy consumption, and microhardness. The equations derived from the metamodels showed satisfactory fits, with adjusted R² values of 81.17% for apparent density, 91.58% for energy consumption, and 85.94% for microhardness, enabling the identification of optimized sintering temperature and time variables. The sintering metamodel demonstrated a global error of 7.2% compared to the validation experiment. Following heat treatment involving quenching and double tempering, the recycled samples achieved an average hardness of 96.9% compared to the commercial material, demonstrating good performance despite microstructural differences caused by the recycling process. In the compression test, the recycled samples attained 66.84% of the commercial material’s elastic modulus. The novelty of this study lies in the integration of Lichtenberg’s new multiobjective algorithm with an innovative approach to recycling tool steels manufactured through powder metallurgy, offering significant added value.