Methods And Systems For Systematic Error Compensation Across A Fleet Of Metrology Systems Based On A Trained Error Evaluation Model

• Main Authors: Hu, Dawei, Tsai, Jenching, Zhang, Tianhao, Huang, Bowei, Chen, Xi, Zhao, Qiang, Sadiq, Malik Karman, Neil, Mark Allen, Tsao, Yao-Chung, Baskin, Igor, Xu, Ce, Chang, Yih-Chung, Krishnan, Shankar, Di, Ming, Ygartua, Carlos L
• Format: Patent
• Language: English
• Published: 15.02.2024
• Subjects: BASIC ELECTRIC ELEMENTS; ELECTRIC SOLID STATE DEVICES NOT OTHERWISE PROVIDED FOR; ELECTRICITY; INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIRCHEMICAL OR PHYSICAL PROPERTIES; MEASURING; PHYSICS; SEMICONDUCTOR DEVICES; TESTING

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.