The current riveting process to assemble components in the aerospace industry involves either manual riveting or the use of riveting robots. The manual riveting process requires pneumatic rivet hammers and bucking bars. This operation creates a hazardous environment for operators, as it produces significant noise and vibration levels. Prolonged exposure to noise has adverse impacts on the human hearing system and also contributes to other physiological concerns. Similarly, vibrations transferred to their hands during operation, puts them at risk for developing musculoskeletal disorders leading to injuries. Despite advances in additive manufacturing, composites, and robotics, human operated riveting will likely remain a large component of aerospace and other manufacturing. Alternative kinds of bucking bars, intended to reduce vibration-related stress on the operator, have been proposed and tested with mildly positive results, including spring-dampened bars. This study explores the feasibility and effectiveness of a novel kind of bucking bar, which will incorporate an active control system to reduce the vibration transmitted to the operator. The incorporation of an active element makes this problem analogous to the comparison of active and passive suspensions in motor vehicles. Various active-control bucking bar (ACBB) designs will be discussed, some of which will be selected for development into prototypes. A mathematical model of the selected ACBBs will be developed and a neural network algorithm will be used to evaluate an optimization metric based on ISO 5349-1. The optimal control parameters to best reduce the vibration felt at the bucking bar handle are then selected to minimize the metric. These results will be compared with mathematical models of the current state-of-the-art standard and passive damping bucking bars.
