MACHINE AND DEEP LEARNING METHODS FOR SPECTRA-BASED METROLOGY AND PROCESS CONTROL

• Main Authors: BRINGOLTZ, Barak, COHEN, Oded, YOGEV, Shay, YACOBY, Ran, STURLESI, Boaz, TAL, Noam
• Format: Patent
• Language: English
• Published: 19.09.2024
• Subjects: APPARATUS SPECIALLY ADAPTED THEREFOR; CINEMATOGRAPHY; CONTROL OR REGULATING SYSTEMS IN GENERAL; CONTROLLING; ELECTROGRAPHY; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; HOLOGRAPHY; MATERIALS THEREFOR; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS ORELEMENTS; ORIGINALS THEREFOR; PHOTOGRAPHY; PHOTOMECHANICAL PRODUCTION OF TEXTURED OR PATTERNED SURFACES,e.g. FOR PRINTING, FOR PROCESSING OF SEMICONDUCTORDEVICES; PHYSICS; REGULATING

A system and methods for Advance Process Control (APC) in semiconductor manufacturing include: for each of a plurality of waiter sites, receiving a pre-process set of scatterometric training data, measured before implementation of a processing step, receiving a corresponding post-process set of scatterometric training data measured after implementation of the process step, and receiving a set of process control knob training data indicative of process control knob settings applied during implementation of the process step; and generating a machine learning model correlating variations in the pre-process sets of scatterometric training data and the corresponding process control knob training data with the corresponding post-process sets of scatterometric training data, to train the machine learning model to recommend changes to process control knob settings to compensate for variations in the pre-process scatterometric data.