Zero-tuning Grinding Process Methodology of Cyber-Physical Robot System

The aerospace industry still relies on manual processes for finish applications, which can be a tedious task. In recent years, robotic automation has gained interest due to its flexibility and adaptability to provide solutions to this issue. However, these processes are difficult to automate, as the material removal rate can vary due to changes in the process variables. This work proposes an approach for automatically modeling the material removal process based on experimental data in a robotic belt grinding application. The methodology concerns the measurement of the removed mass of a test part during a finishing process using an automatic precision measurement system. Then, experimental models are used to develop a control algorithm for continuous material removal that maintains a uniform finishing process by regulating the robot’s feed rate. Next, the results for various experimental material removal models under different process conditions are presented, showing the process parameter’s influence on the removal capacity. Finally, the proposed control algorithm is validated, achieving a constant material removal rate.

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Zero-tuning Grinding Process Methodology of Cyber-Physical Robot System

Cited by 2 publications

References 17 publications

Learning to Shape by Grinding: Cutting-Surface-Aware Model-Based Reinforcement Learning

Learning to Shape by Grinding: Cutting-Surface-Aware Model-Based Reinforcement Learning

Robotic Belt Finishing with Process Control for Accurate Surfaces

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