公开(公告)号：US20240053280A1

公开(公告)日：2024-02-15

申请号：US18229606

申请日：2023-08-02

Applicant: KLA Corporation

Inventor： Ming Di ,  Yih-Chung Chang ,  Xi Chen ,  Dawei Hu ,  Ce Xu ,  Bowei Huang ,  Igor Baskin ,  Mark Allen Neil ,  Tianhao Zhang ,  Malik Karman Sadiq ,  Shankar Krishnan ,  Jenching Tsai ,  Carlos L. Ygartua ,  Yao-Chung Tsao ,  Qiang Zhao

IPC: G01N21/95 ,  H01L21/66

CPC classification number: G01N21/9501 ,  H01L22/12

Abstract: Methods and systems for compensating systematic errors across a fleet of metrology systems based on a trained error evaluation model to improve matching of measurement results across the fleet are described herein. In one aspect, the error evaluation model is a machine learning based model trained based on a set of composite measurement matching signals. Composite measurement matching signals are generated based on measurement signals generated by each target measurement system and corresponding model-based measurement signals associated with each target measurement system and reference measurement system. The training data set also includes an indication of whether each target system is operating within specification, an indication of the values of system model parameter of each target system, or both. In some embodiments, the composite measurement matching signals driving the training of the error evaluation model are weighted differently, for example, based on measurement sensitivity, measurement noise, or both.