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Improve tool performance by associating tool operating parameters and material measurements with spectroscopic information

机译:通过将工具操作参数和材料测量值与光谱信息相关联来提高工具性能

摘要

System(s) and method(s) are provided for adjustment and analysis of performance of a tool through integration of tool operational data and spectroscopic data related to the tool. Such integration results in consolidated data that enable, in part, learning at least one relationship amongst selected portions of the consolidated data. Learning is performed autonomously without human intervention. Adjustment of performance of the tool relies at least in part on a learned relationship and includes generation of process recipe parameter(s) that can adjust a manufacturing process in order to produce a satisfactory tool performance in response to implementation of the manufacturing process. A process recipe parameter can be generated by solving an inverse problem based on the learned relationship. Analysis of performance of the tool can include assessment of synthetic performance scenarios, identification of spectroscopic condition(s) that affect performance, and extraction of endpoints based at least on time dependence spectroscopic data.
机译:提供一种或多种系统和方法,用于通过整合工具操作数据和与该工具有关的光谱数据来调整和分析工具的性能。这样的集成导致合并的数据,该合并的数据能够部分地学习合并的数据的所选部分之间的至少一种关系。学习是自动进行的,无需人工干预。工具性能的调整至少部分地依赖于学习的关系,并且包括可以响应于制造过程的实施而调整制造过程以便产生令人满意的工具性能的过程配方参数的产生。可以通过基于所学习的关系求解逆问题来生成过程配方参数。该工具的性能分析可以包括评估综合性能方案,识别影响性能的光谱条件以及至少基于时间依赖性光谱数据提取端点。

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