Preliminary study of an intelligent sampling decision scheme for the AVM system

Abstract

Wafer inspection plays a significant role in monitoring the quality of production wafers. However, it requires measuring tools and additional cycle time to do real metrology, which is costly and time-consuming. Therefore, reducing sampling rate to as low as possible is a high priority for many factories to reduce production cost. The most common way for inspecting process quality is to apply periodic sampling. If a manufacturing process is stable, then virtual metrology (VM) may be applied for monitoring the quality of wafers while real metrology is unavailable. Nevertheless, if a production variation occurs between periodic samplings, no real metrology is available during this period for updating the VM models, which may result in un-reliable VM predictions. The authors have developed the automatic virtual metrology (AVM) system for various VM applications. Therefore, this paper focuses on applying various indices of the AVM system to develop an Intelligent Sampling Decision (ISD) scheme for reducing sampling rate while VM accuracy is still sustained.