Gigaphoton Inc.

Kunihiko Abe

Osamu Wakabayashi

Yuji Minegishi

Satoru Kikuchi

A machine learning method according to a viewpoint of the present disclosure is a machine learning method for creating a learning model configured to estimate the life of a consumable of a laser apparatus, the method including acquiring first life-related information containing data on a parameter relating to the life of the consumable, the data recorded in correspondence with different numbers of oscillation pulses during a period from the start of use of the consumable to replacement thereof, dividing the first life-related information into a plurality of levels each representing the degree of degradation of the consumable in accordance with the numbers of oscillation pulses to create training data, creating the learning model by performing machine learning using the created training data, and saving the created learning model.

Machine learning method, consumable management apparatus, and computer readable medium

A maintenance management method for a lithography system according to a viewpoint of the present disclosure includes organizing and saving operating information for each of lithography cells that are each an apparatus group formed of a set of apparatuses and form the lithography system, organizing and saving maintenance information on consumables for each of the lithography cells, calculating a standard maintenance timing for each of the consumables for each of the lithography cells based on the operating information and the maintenance information on the consumable for each of the lithography cells, creating a maintenance schedule plan for each of the lithography cells or for each of manufacturing lines based on the standard maintenance timing, information on a downtime, and information on a loss cost due to the downtime for each of the lithography cells or for each of the manufacturing lines, and outputting the result of the creation of the maintenance schedule plan.

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Oyama, Japan

Kunihiko Abe