Towards Data-Driven Material Removal Rate Estimation in Bonnet Polishing

Ultra-precision polishing is a complex process that involves polishing surfaces with nanometre-level accuracy. Even though much of the process is performed using computer numerically controlled (CNC) machines, fully autonomous manufacturing of such fine parts is currently not feasible. The complexity of the process, lack of perfect determinism, surface inaccessibility during the polishing process, and the need for extensive expert knowledge all present significant challenges in ultra-precision manufacturing. In this work, we present a system design for monitoring parameters in the ultra-precision bonnet polishing process, such as the chemical properties of the polishing slurry or tool forces during the process. We also share some initial findings and challenges encountered during the validation stage of the system, which require further consideration. Additionally, we outline our plan for implementing machine learning in material removal rate estimation for bonnet polishing.