Conventional peening methods often struggle to achieve uniform, controllable strengthening on thin-walled and complex components under combined thermo–mechanical loading. This study develops a robotized ultrasonic multi-needle peening (UMNP) system and a validated experimental–numerical framework for automated process planning and transferable mechanism-based design. The process decouples robotic coverage control (trajectory, speed, step-over) from local impact severity (ultrasonic amplitude, air pressure, stand-off) using a 65-needle array that provides stochastic impacts with spatial averaging. A parameterized multi-needle FE model (ABAQUS/Python), informed by high-speed measurements of needle-tip velocity distributions, predicts plastic indentation and residual-stress profiles with 500 μ m) with 113% higher hardness and –1.1 GPa stress. • Surface refinement enables a tribo-oxidation transition, enhancing high-temperature wear resistance by 33%.
Saifan et al. (Tue,) studied this question.