This study presents an optimization framework for designing novel retainer rings (NRR) in chemical mechanical planarization (CMP) to enhance the uniformity of material removal rates (MRR). To improve optimization efficiency, we developed a finite element method (FEM) model alongside a Metamodel of Optimal Prognosis (MOP). The NRR outperformed the reference retainer ring (RRR) in our simulations. We classified simulation cases based on the pressure application area: long (LC), middle (MC), and short (SC). The MOP was constructed using Latin hypercube sampling and refined through an adaptive approach to achieve high accuracy while minimizing computational costs. Optimization was performed using an evolutionary algorithm, generating Pareto fronts for analysis. We evaluated representative designs based on MRR distribution and non-uniformity. Ultimately, Design 2-LC was identified as the optimal choice. The results indicate that the proposed framework effectively enhances MRR uniformity while reducing optimization time.
