Abstract

Titanium alloys are extensively utilized due to their exceptional corrosion resistance, high specific strength, temperature resilience, and biocompatibility. However, the challenges such as poor thermal conductivity, pronounced micro-machining size effects, and the sensitivity of micro-thin wall structures to residual stress complicate the machining of titanium alloy micro-thin walls. This paper investigates the use of supercritical CO2 to assist in arc micro-thin wall milling experiments of titanium alloys, aiming to elucidate the influence of various process parameters on micro-milling performance. The mesoscale prediction model developed in this study shows that the time-varying and static deflection deformations of micro-thin walls cooled by supercritical CO2 are approximately half of those observed under dry cutting conditions. To compare and optimize micro-milling performance metrics, an RVEA-entropy weight TOPSIS optimization scheme was developed, and combined with several high-dimensional multi-objective optimization algorithms. Integrating this with micro-milling finite element model, an iterative optimization and reverification strategy was proposed. The optimized parameters combination achieved through this method reduced micro-milling force, top deformation, and side deformation by 32.5 %, 24.6 %, and 24.3 %, respectively. The research approach and optimization strategy presented in this paper offer valuable insights for enhancing the machining precision of mesoscale titanium alloy micro-thin-wall structures.

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