A Novel Statistical Metrology Framework for Identifying Sources of Variation in Oxide Chemical‐Mechanical Polishing

Abstract

A statistical metrology framework is used to identify systematic and random sources of interlevel dielectric thickness variation. Electrical and physical measurements, technology computer‐aided design simulations, design of experiments, signal processing, and statistical analysis are integrated via statistical metrology to deconvolve interlevel dielectric thickness variation into constituent variation sources. In this way, insight into planarization variation is enabled; for a representative chemical/mechanical polishing process, we find that die‐level neighborhood interactions are comparable to die level feature dependent effects, and that within each die, die level variation is greater than wafer level variation. The characterization of variation sources via statistical metrology is critical for improved process control, interconnect simulation, and robust circuit design.