This study presents a transient thermo-mechanical finite element framework for high-speed end milling of AISI 4340 steel. The model couples moving heat sources, rate- and temperature-dependent plasticity, and adaptive mesh refinement (AMR) triggered by temperature gradient, plastic strain rate, and contact pressure. It is integrated with a design of experiments/response surface methodology using cutting speed (VC), feed per tooth (fZ), radial depth of cut/width of cut (ae), axial depth of cut (ap), and coolant mode. Responses include peak interface temperature per tooth (Tpeak), predicted surface residual stress (?_xx^"surf" ), and depth of compressive residual stress layer (dcomp). Experiments provide X-ray diffraction-based surface/depth profiles and arithmetic mean surface roughness (Ra). AMR is applied in this study to minimize the cut compute cost by 41-52% and error by 35-45%. Across 12 validation cuts, root mean square errors were 24 °C of Tpeak, 33 MPa of ?_xx^"surf" , 0.07 µm of Ra, and 22 MPa of dcomp. The response surface methodology and analysis of variance identified VC as the main driver of thermal load, while fZ, ae, and ap controlled the sign and depth of the residual field; coolant modified heat partition. Multi-objective desirability optimization with a material removal rate constraint yielded a balanced minimum quantity lubrication. Overall, exit-edge cooling and subsurface plasticity jointly set residual sign and magnitude; AMR is essential to resolve these gradients efficiently. The framework offers a reproducible route for residual stress-aware process planning in fatigue-critical AISI 4340 components while preserving throughput and is readily transferable to allied high-strength steels.
