The chips contained in any electronic device are manufactured over circular silicon wafers, which are monitored by inspection machines at different production stages. Inspection machines detect and locate any defect within the wafer and return a Wafer Defect Map (WDM), i.e., a list of the coordinates where defects lie, which can be considered a huge, sparse, and binary image. In normal conditions, wafers exhibit a small number of randomly distributed defects, while defects grouped in specific patterns might indicate known or novel categories of failures in the production line. Needless to say, a primary concern of semiconductor industries is to identify these patterns and intervene as soon as possible to restore normal production conditions. Here we address WDM monitoring as an open-set recognition problem to accurately classify WDM in known categories and promptly detect novel patterns. In particular, we propose a comprehensive pipeline for wafer monitoring based on a Submanifold Sparse Convolutional Network, a deep architecture designed to process sparse data at an arbitrary resolution, which is trained on the known classes. To detect novelties, we define an outlier detector based on a Gaussian Mixture Model fitted on the latent representation of the classifier. Our experiments on a real dataset of WDMs show that directly processing full-resolution WDMs by Submanifold Sparse Convolutions yields superior classification performance on known classes than traditional Convolutional Neural Networks, which require a preliminary binning to reduce the size of the binary images representing WDMs. Moreover, our solution outperforms state-of-the-art open-set recognition solutions in detecting novelties.
翻译:任何电子设备中所含的芯片都是用环硅片制造的,由不同生产阶段的检查机器加以监测。检查机器检测和定位了瓦费尔断层图(WDM)中的任何缺陷,并返回了瓦费尔断层图(WDM),即缺陷所在的坐标列表,可以被视为巨大、稀疏和二进制图像。在正常情况下,壁画呈现出少量随机分布的缺陷,而具体模式中的缺陷可能显示生产线的已知或新颖故障类别。不用说,半导体行业的主要关切是查明这些模式并尽快干预以恢复正常生产条件。在这里,我们把Wfer DM监测作为开放的识别问题来处理,将WferDM精确地分类在已知类别中进行分类,并迅速探测新模式图。我们提议了一个全面的线谱监测管道,这个深层结构旨在以任意解析方式处理稀疏漏数据,该结构在已知的分层中进行。为了探测新版本,我们定义了一种外向外探测器的解决方案,基于一个高层次的内径探测器,用来在预变平层平层平层的图像上显示我们模型的图像的图像的图像,从而显示我们的图层平流分析。