A reverse optimization design approach of frequency reliability for handling robot arm

The manipulator arm constitutes a critical component in robotic systems, with its dynamic performance exerting a direct influence on operational stability and positioning accuracy during material handling. Even minimal vibrations can result in substantial end-effector displacement, which may cause operational errors or system failure. This study examines the mechanical response of a material-handling robotic manipulator through quasi-static and modal analyses under critical configurations. Key performance indicators, including maximum von Mises stress, deformation, and natural frequencies, are extracted to assess structural behavior. This research investigates the impact of large-arm structural parameters on dynamic system characteristics and utilizes random reliability analysis to identify parameters with the highest influence on frequency stability. This study integrates these parameters into a reliability-driven robust optimization paradigm. A multi-criteria optimization paradigm is devised to systematically balance reliability robustness and mass constraints, effectively reconciling performance-efficiency trade-offs. Post-optimization results indicate reduced sensitivity of frequency parameters and significant mass reduction while preserving structural stability and expected performance levels. The proposed optimization approach maintains the strengths of conventional optimization models while achieving an optimal reverse design that satisfies structural stability, weight requirements, and predetermined reliability criteria.