Exploiting Defect Clustering Information in VLSI Testing

这个项目正在调查有关缺陷的信息的使用 在晶片上进行聚类以预测各个管芯的产量 基于相邻管芯的测试结果。 前提是 晶片上的缺陷是聚集的，因此大多数好的管芯接近于 其它好的和大多数有缺陷的管芯与其它管芯接近。 然后，聚类信息可以用于针对特定的 测试晶圆上的单个芯片。 使用晶圆进行模拟 已发表文献中的缺陷分布数据正在 用于评估该方法的可行性。 精确的模型 预测可达到的缺陷水平正在开发中， 正在确定用于测试晶片上的管芯的策略。

This project is investigating the use of information about defect clustering on wafers to make yield predictions for individual dies based on test results for neighboring dies. The hypothesis is that defects on a wafer are clustered, thus most good dies are close to other good ones and most defective dies are close to others. Clustering information can then be used for targeting particular tests to individual dies on the wafer. Simulations using wafer defect distribution data from the published literature is being employed to assess the viability of the approach. Accurate models to predict defect levels attainable are being developed and strategies for testing dies on the wafer are being determined.