| dc.description.abstract | Abstract. Thin-walled components are extensively utilized in aerospace applications but present significant machining challenges due to their low rigidity and time-varying dynamics. While existing adaptive control approaches have been proposed for thin-walled milling, most fail to address the coupled challenges of real-time dynamics identification and multiparameter coordination under rapidly varying workpiece stiffness, limiting their industrial applicability. This article presents a comprehensive adaptive control strategy for high-speed milling that addresses these challenges through real-time system identification, intelligent parameter optimization, and continuous stability monitoring. The proposed approach integrates multisensor feedback with advanced signal processing to detect impending instabilities and implement corrective actions before chatter development. Experimental validation on aluminum alloy 7075-T6 workpieces demonstrated remarkable performance improvements, including 44% increase in material removal rate, 75% enhancement in dimensional accuracy, and 43% extension in tool life compared to conventional fixed-parameter machining. The adaptive control system maintained surface roughness within 0.9–1.3 μm throughout the machining process while achieving 96% first-pass yield. Economic analysis revealed 42% reduction in cost per part with a 14-month return on investment. These results establish adaptive control as an enabling technology for efficient and reliable thin-walled component manufacturing, with significant implications for aerospace industry competitiveness and sustainability. | |
