Inaccuracies and deviations from programmed toolpath in industrial robots pose a significant barrier to the adoption of robotic technologies in surface rolling and other surface treatment processes. This project aimed to develop a robust and precise robotic surface rolling cell and demonstrate deep rolling capability to improve fatigue of aerospace graded part representative of turbine blade. These advances make robotic surface treatment processes a viable and competitive alternative to traditional CNC machine driven treatment processes. The project also addressed the limitations of CNC machines, including the inability to accommodate heavy loads and being unable to accommodate hard-to-reach spots.
Lower the costs of surface treatment processes while increasing throughput.
This project aimed to demonstrate that robotic surface rolling processes can be as effective and precise as a traditional CNC machine while significantly reducing the cost of the process and improving flexibility. The project includes:
- Development of software/algorithm to improve positional accuracy of industrial robots by accounting for the nonlinear dynamics and deadtime lag
- Integration of improved robot motion with already existing surface rolling process to optimize the load set point
The project outputs have the potential to be readily adapted for other surface treatment processes including grinding, deburring, and polishing.
United Research Technologies Center (Principal Investigator), Rensselaer Polytechnic Institute