自动化系统基础设施,以促进实验设计(DOE)数据分析

N. Tandon, G. Baweja
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引用次数: 0

摘要

复杂的半导体制造工艺需要快速优化,以提高晶圆厂的工艺良率和效率。实验设计(DOE)技术经常应用于半导体领域,通过将晶圆批次分离成晶圆段,并研究不同工艺参数对扩散、光刻、蚀刻和其他制造工具的基线分裂的影响。提出了一种在德州仪器Kilby中心(KFAB)实现的自动化解决方案,用于捕获和存储批次拆分DOE数据进行分析,满足数据量、准确性和可访问性的要求。关于如何一致地定义批量划分的指导方针(“规则集”),系统基础设施组件的设计和实现,以及系统应用程序都包括在内。
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Automated system infrastructure to facilitate design of experiments (DOE) data analysis
The complex semiconductor fabrication process needs to be optimized quickly to increase process yield and efficiency in fab operations. The Design of Experiments (DOE) technique is frequently applied in semiconductor domain by separating a wafer lot into wafer splits, and studying the effects of varying process parameters in relation to a baseline split across diffusion, photo, etch and other fabrication tools. An automated solution implemented at Kilby Center (KFAB) of Texas Instruments to capture and store the lot split DOE data for analysis, which satisfies the requirements of data volume, accuracy, and accessibility, is presented. Guidelines on how lot splits are defined consistently (the "rule set"), design and implementation of the system infrastructure components, and system's applications are included.
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