Intelligent robotic system for automated shot peening and peen forming

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Shot peen forming (or SPF) and Shot peening (or SP) and are extensively applied in aerospace and transportation engineering to, respectively, form curved shapes from sheet metal (which would be difficult to form with traditional methods like stamping) and improve mechanical properties of the surfaces. Despite a wide range of their applications, many SPF and SP processes are currently executed mostly manually or in an open-loop fashion by qualified operators. The reach, repeatability, accuracy, and response time of the processes are then obviously limited by those of the operator. A robotic system seems to offer an attractive substitute addressing the aforementioned issues. However, the application of robots in such applications is hindered by the process uncertainties which limit the accuracy, repeatability, and response time of automated solutions. For instance, several trials to reach the desired forming are common to many SPF processes. Two main sources of uncertainty, tackled in this project, include the nozzle's motion (position and velocity) and peening coverage. Teams from Ryerson University, NRC-IAR-AMTC, Sonaca Montreal, Vibra Finish, and Quanser have organized a research program to address the aforementioned issues. A vision-based control solution is developed that uses closed-loop position and orientation (pose) control with visual feedback to adapt to the surface pose uncertainty in real-time, e.g., when the surface is continuously deforming due to peening effect or when the workpiece has not been properly fixtured or calibrated with respect to the robot. Finally, novel real-time coverage measurement and control techniques are proposed that could improve coverage quality for shot peening applications. The developed methods can readily be extended to similar applications such as shot blasting, depainting, and abrasive jet machining. The research outcome would lead to reduced time-to-market for the new parts, lower production costs and cycle time, and superior end products. The results could thus make a strategic impact on the manufacturing industry, especially in aerospace and automotive sectors, by raising their core technical competencies and ability to compete in the global economy.