Resumo:
Research on duplex stainless steel end milling has gained prominence due to the challenges encountered due to its low machinability characteristics. Duplex stainless steel has low thermal conductivity, high toughness, and a high work hardening rate. To ensure good final quality in manufactured products, it is important that the milling process be well planned, to minimize the wear of the cutting tools during the process and at the same time present good productivity indicators. The objective of this work is to perform a robust multi-objective optimization in the end milling process of duplex stainless steel UNS S32205. The experiments were performed using a central composite design combining the control variables: cutting speed, feed per tooth, depth of cut and milled width and the noise variables: flank wear, fluid flow rate and fluid concentration. The response variables evaluated were the surface roughness R_a and R_t of the machined part. Response surface methodology, robust parameter design, and mean square error techniques were applied. Then, the effects of the control and noise variables, as well as interactions, were analyzed and discussed. The cutting speed was the variable that most influenced the roughness R_a. Roughness R_t was influenced especially by the feed per tooth. The values obtained for roughness R_a ranged between 0.243 and 1.097 µm and 1.800 and 7.058 µm for R_t. The optimization of the mean and variance of each characteristic of interest was performed, as well as the optimization of the mean square error. Thus, 21 Pareto-optimal solutions were obtained, contributing to the improvement of surface quality and productivity in the milling process. For the confirmation tests, an orthogonal Taguchi arrangement (L9) was used where the optimal setups capable of mitigating the influence of noise variables were obtained, which corroborated the good suitability of the proposed methodology.
