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Implementation of an efficient defect classification method in photomask mass production

机译:一种有效的缺陷分类方法在光掩模批量生产中的实现

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In photomask production environments, increasing productivity of defect inspection and improving fidelity of defect classification are important for mask makers to improve capacity of defect inspection tools and to enhance quality of production. In particular, defect classification time corresponds directly to the cost and the cycle time of mask manufacturing and new product development. KLA-Tencor has introduced an automatic defect grouping tool "ReviewSmart" which automatically bins defects with high fidelity. ReviewSmart has been reported in engineering R&D and evaluation [1], [2]. In this paper, we focus on implementation of ReviewSmart in photomask production. 592 plates were processed during the evaluation period. Those plates are for products of logic, memory and flash. Technology nodes are from 65nm to 180nm. With optimized production setting, the automatic defect grouping tool - ReviewSmart improves productivity of defect inspection by 7% with 100% fidelity. In addition to improve productivity, ReviewSmart is helpful to classify aggressive OPC caused nuisance, troubleshoot process issues and expedite product development and improve usable inspection sensitivity as well.
机译:在光掩模生产环境中,提高缺陷检查的生产率和改善缺陷分类的保真度对于掩模制造商提高缺陷检查工具的能力并提高生产质量至关重要。特别地,缺陷分类时间直接对应于掩模制造和新产品开发的成本和周期时间。 KLA-Tencor推出了自动缺陷分组工具“ ReviewSmart”,该工具可以自动保真地分类缺陷。 ReviewSmart在工程研发和评估中已有报道[1],[2]。在本文中,我们重点介绍在光掩模生产中实施ReviewSmart。在评估期间,处理了592个板。这些板用于逻辑,存储器和闪存的产品。技术节点的范围从65nm到180nm。通过优化的生产设置,自动缺陷分组工具-ReviewSmart以100%的保真度将缺陷检查的生产率提高了7%。除了提高生产率之外,ReviewSmart还有助于对由OPC引起的令人讨厌的讨厌事件进行分类,对过程问题进行故障排除并加快产品开发速度,并提高可用的检查灵敏度。

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