Fuzzy tree classification system for fault diagnosis on Ion implanter

Abstract Ion implanter is critical to modern integrated-circuit (IC) manufacturing. requires a long process due low acceleration and high concentration process, which results in productivity becomes bottleneck the semiconductor fabrication. Furthermore, wafer not re-workable if existing error operation either caused by operator or machine. Therefore, it important develop real-time fault detection system minimize probable down time of ion implanter. In this work, system, based on Fuzzy Tree Classification Systems (FTCS), proposed monitor Eaton NV6200A/AV Two datasets, 26-recipe 42- recipe cases, provided renowned foundry Taiwan were used test performance FTCS. The datasets obtained through SECS-II interface. Test demonstrate that FTCS can work for