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Real-time fault detection and classification for manufacturing etch tools

机译:制造蚀刻工具的实时故障检测和分类

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Process control in semiconductor manufacturing has sought to improve yield, increase tool productivity and reduce manufacturing costs through the analysis of tool sensor outputs. Statistical process control (SPC) utilizes statistical algorithms to detect excursion events, but here a novel fault detection and classification (FDC) approach based upon a pattern recognition algorithm is presented. This FDC method from Straatum/spl trade/ is real-time, outputting a chamber status metric known as the plasma index. The system is in place at ProMOS Technologies Inc, 200 mm manufacturing facility on various semiconductor tools - this document presents its implementation on a number of Tokyo/spl trade/ DRM/spl trade/ oxide etch tools and includes a number of case studies.
机译:半导体制造中的过程控制已试图通过分析工具传感器的输出来提高产量,提高工具生产率并降低制造成本。统计过程控制(SPC)利用统计算法来检测偏移事件,但是这里提出了一种基于模式识别算法的新颖的故障检测和分类(FDC)方法。 Straatum / spl trade /的这种FDC方法是实时的,输出称为等离子体指数的腔室状态度量。该系统在ProMOS Technologies Inc的200毫米制造设施中就位,该制造厂使用各种半导体工具-本文档介绍了在许多Tokyo / spl贸易/ DRM / spl贸易/氧化物蚀刻工具上的实现方式,并包括了许多案例研究。

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