Optimization of an integrated and automated macro inspection system for the utilization of wafer color variation detection in a photolithography cluster

Stephen J. Lickteig; Thomas W. Forstner; Anthony R. Barnett; David S. Dixon; Vinayan C. Menon; Robert L. Isaacson; Matthew C. Nicholls; Yonqiang Liu; Pinar Kinikoglu

doi:10.1117/12.655706

24 March 2006 Optimization of an integrated and automated macro inspection system for the utilization of wafer color variation detection in a photolithography cluster

Stephen J. Lickteig, Thomas W. Forstner, Anthony R. Barnett, David S. Dixon, Vinayan C. Menon, Robert L. Isaacson, Matthew C. Nicholls, Yonqiang Liu, Pinar Kinikoglu

Author Affiliations +

Proceedings Volume 6152, Metrology, Inspection, and Process Control for Microlithography XX; 61523B (2006) https://doi.org/10.1117/12.655706
Event: SPIE 31st International Symposium on Advanced Lithography, 2006, San Jose, California, United States

Abstract

The IBM 300 mm wafer manufacturing line provides a case study for the optimization of an automated macro defect inspection system to accurately flag global wafer color variation. The IBM inspection system was falsely flagging a large number of wafers primarily for global wafer color variation, leading to unacceptable amounts of production volume being placed on hold. A review of the macro inspection system identified several areas for improvement. An investigation into the installed hardware base found a panel behind the beam splitter was introducing noise through reflected light. This panel was replaced with a less reflective material. A review of the failed wafers found that maximum light levels were not achieved across all tools and an improved diffuser plate for the fiber optic output was designed to improve light transmittance. Global wafer color is determined by comparing the scanned wafer image to a "golden" data set, referred to as a "color baselist," which is composed of data from 30 wafers. A review of the recipe baselists revealed that some of the wafer samples did not accurately represent process conditions, and new wafer samples were collected. Finally, a tool-to-tool matching test revealed that the set of weightings given to each of the color parameters in the baselists was not optimized. After implementing the above changes, false global wafer color failures were virtually eliminated.

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Stephen J. Lickteig, Thomas W. Forstner, Anthony R. Barnett, David S. Dixon, Vinayan C. Menon, Robert L. Isaacson, Matthew C. Nicholls, Yonqiang Liu, and Pinar Kinikoglu "Optimization of an integrated and automated macro inspection system for the utilization of wafer color variation detection in a photolithography cluster", Proc. SPIE 6152, Metrology, Inspection, and Process Control for Microlithography XX, 61523B (24 March 2006); https://doi.org/10.1117/12.655706

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