Exploiting Defect Clustering Information in VLSI Testing

该项目正在研究利用晶圆上的缺陷聚类信息，根据相邻晶圆的测试结果对单个晶圆进行良率预测。假设晶圆上的缺陷是聚集在一起的，因此大多数好晶圆靠近其他好晶圆，大多数有缺陷的晶圆靠近其他好晶圆。然后，聚类信息可用于针对晶圆片上单个晶圆片的特定测试。利用已发表文献中的晶圆缺陷分布数据进行模拟，以评估该方法的可行性。目前正在开发准确的模型来预测可达到的缺陷水平，并确定晶圆上测试模具的策略。

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.