Cymer, Inc.

Matthew Minakais

Russell Allen Burdt

Kumar Raja Guvindan Raju

David Wesley Manley

Systems for maintaining light sources for semiconductor photolithography in which a module making up part of the light source is evaluated at various pulse counts to produce a binary prediction as to whether the module is sufficiently likely to operate without failure in an ensuing sequence of pulses. The binary prediction may be made by a machine learning model trained on metrics extracted from measurements taken on deinstalled modules. A group of models, each trained differently, can be made available according to a selection made by the user or according to the maintenance objectives of the user.

Maintenance of modules for light sources used in semiconductor photolithography

An apparatus includes a decision module that is configured to: receive a performance metric relating to performance conditions of an optical system emitting a light beam; estimate, based on the performance metric and a predetermined learning model, an effectiveness of a proposed change to the optical system; and output a change command to the optical system if it is estimated that the proposed change to the optical system would be effective.

Predictive apparatus in a gas discharge light source

A system includes a laser source configured to generate one or more bursts of laser pulses and a data collection and analysis system. The data collection and analysis system is configured to receive, from the laser source, data associated with the one or more bursts of laser pulses and determine, based on the received data, that the one or more bursts of laser pulses are for external use. The data collection and analysis system is further configured to determine, based on the received data, whether the one or more bursts of laser pulses are for an on-wafer operation or are for a calibration operation.

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San Diego, CA, United States of America

Matthew Minakais