Mask line monitor: process improvements and yield learning

Yiyang Jenny Wang; Andrew J Watts

doi:10.1117/12.536773

24 May 2004 Mask line monitor: process improvements and yield learning

Yiyang Jenny Wang, Andrew J Watts

Proceedings Volume 5375, Metrology, Inspection, and Process Control for Microlithography XVIII; (2004) https://doi.org/10.1117/12.536773
Event: Microlithography 2004, 2004, Santa Clara, California, United States

Abstract

With ever increasing linewidth challenges per technology changes, the mask manufacturing process becomes more and more difficult. The challenges can be separated into two categories: image size and defects. Mask inspection detects hard defects most likely caused somewhere in the mask manufacturing process. Defect partitioning highlights the hard defects sources. They range from pre-exposure mask blank handling to the cleanliness of the process tools. A test vehicle was designed to allow for mask manufacturing defect partitioning via a die-to-die inspection tool. The process changes implemented range from pre-write mask handling to tool modifications. The methodology used to determine the process induced defects and the yield gains by making the necessary process changes will be presented.

Citation Download Citation

Yiyang Jenny Wang and Andrew J Watts "Mask line monitor: process improvements and yield learning", Proc. SPIE 5375, Metrology, Inspection, and Process Control for Microlithography XVIII, (24 May 2004); https://doi.org/10.1117/12.536773

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