Optimizing multiple response variables of chemical and mechanical planarization process for semiconductor fabrication using a clustering method

Semiconductors are fabricated through unit processes including photolithography, etching, diffusion, ion implantation, deposition, and planarization processes. Chemical mechanical planarization (CMP), which is essential in advanced semiconductor manufacturing, aims to achieve high planarity across a wafer surface. Selectivity and roughness are the main response variables of the CMP process. Since the response variables are often in conflict, it is important to obtain a satisfactory compromise solution by reflecting the CMP process engineer's preference information. In this study, we present a case study in which the satisfactory compromise solution is obtained. The recently developed posterior preference articulation approach to multi-response surface optimization is employed for this purpose. The performance of response variables of CMP process have been shown to be better at the obtained setting than at the existing setting of process variables.