Patent ID: 11899437
Assignee: HITACHI HIGH-TECH CORPORATION
Field: Control (Instruments)
Classification: CPC G  H | IPC G

Claim 8:
9. A diagnosis system that diagnoses a state of a device for measuring or inspecting a sample, the diagnosis system comprising:
a computer system configured to estimate a cause for an error occurring in the device, wherein the computer system includes a learning device configured to cluster, by machine learning, a combination of one or more of process content data that describes a content of an inspection process to be executed by the device, an inspection condition by the device, and attribute data that describes an attribute of the device,
when the error occurs in the device after the learning device executes the machine learning, the computer system inputs a first combination of one or more of the process content data that describes the content of the inspection process to be executed by the device when the error occurs, the inspection condition when the error occurs, and the attribute data to the learning device, so as to classify the first combination into one of clusters obtained by the clustering, and
the computer system acquires an estimation result on whether or not the error occurs based on a result of the classification and outputs the estimation result,
wherein the device is configured to acquire an image of the sample,
the computer system causes the learning device to learn the first combination when the error does not occur, the first combination is clustered into one of the classifications, and the image is abnormal, so as to generate a third learning unit configured to cluster the first combination when the error does not occur, all of the content of the inspection process, the inspection condition, and the attribute are normal, and the image is abnormal, and
when a new first combination is used, based on whether or not the new first combination is classified into one of clustering results by the third learning unit, the computer system acquires, from the third learning unit, an estimation result on whether or not the error does not occur, all of the content of the inspection process, the inspection condition, and the attribute are normal, and the image is abnormal.