<p>This study presents an integrated numerical and multi-objective optimization framework to analyze and improve the combined deep drawing–ironing process of AA1050-O aluminum sheets. Three key process parameters, including the drawing coefficient, thinning (ironing) coefficient, and die semi-angle, were systematically varied through a Box–Behnken experimental design. Finite element simulations were carried out to establish response surface models for punch force, forming energy, bottom thinning, and Cockroft–Latham damage. The optimization results reveal a clear monotonic trend governed primarily by the die cone angle: larger cone angles reduce the required forming load and energy but cause the material to enter the ironing zone prematurely, intensifying the overlap between drawing and ironing and thereby increasing thinning. In contrast, smaller cone angles require higher load and energy yet delay the onset of ironing, stabilize the deformation, and considerably suppress thinning. A physically motivated damage constraint derived from previous experimental–numerical calibration was incorporated into the optimization. The selected threshold of 32.6&#xa0;MJ/m³ represents a sub-critical damage level at which ductility recovery becomes limited despite the absence of fracture, ensuring that all optimal solutions remain both fracture-safe and metallurgically viable for subsequent forming steps. Independent numerical validation confirmed deviations below ± 3% for all predicted responses. The findings provide new mechanistic insight into thinning evolution during combined drawing–ironing and show that damage-informed response surface models can support forming-window definition and process evaluation for aluminum sheet components with different diameter and thickness specifications.</p>