Simultaneous fault detection and classification for semiconductor manufacturing tools

Increasingly there is a need for fast, accurate, and sensitive detection of equipment and process faults to maintain high process yields and rapid fault classification (diagnosis) of the cause to minimize tool downtime in semiconductor manufacturing. Current methods treat fault detection and classification as a two-step process. We present a novel method to simultaneously detect and classify faults in a single-step using fault-specific control charts. These control charts are designed to discriminate between specific fault classes and the normal process operation as well as all other fault classes. Using a set of experimental data collected from an industrial plasma etcher, we demonstrate that if the fault-specific charts are constructed using an orthogonal linear discriminant approach, they are effective in simultaneously detecting and classifying a given fault. We also demonstrate that this methodology has improved sensitivity for detection of faults when compared to other commonly used methods of fault detection.