Process start/end event detection and dynamic time warping algorithms for run-by-run process fault detection

Abstract

In semiconductor/FPD (Flat Panel Display) manufacturing environments, APC (Advanced Process Control) is a vital task for enhancing yield. The APC technology improves the productivity of equipments based on two main control mechanisms: fault management and R2R (Run-to-Run) recipe correction. This paper focuses on FDC (Fault Detection and Classification) for the fault management, and proposes a runby-run process fault detection method. The method consists of a process event detection algorithm to segment process data, and a pattern matching technique to classify the segmented data as normal or abnormal state. Experiments using the data collected from a RIE (Reactive Ion Etching) process show that the proposed method is able to recognize normal/abnormal states with high accuracy.