公开(公告)号：US20220114484A1

公开(公告)日：2022-04-14

申请号：US17265857

申请日：2020-03-02

Applicant: SPP TECHNOLOGIES CO., LTD.

Inventor： Katsuji HANADA ,  Yuki FUJIWARA

IPC: G06N20/00 ,  C23C16/52 ,  C23C16/50

Abstract: Provided are a production process determination device for a substrate processing apparatus, which can easily suppress deterioration of determination accuracy, and the like. A production process determination device 20 includes a process log acquisition section 21 that acquires process log data of a substrate processing apparatus 10, and a determination section 22 that creates input data based on the process log data and performs determination regarding production process in the substrate processing apparatus based on the input data. The determination section includes multiple learning models 25 each of which receives input of the input data and each of which outputs a determination result regarding the production process, and the multiple learning models are generated by performing machine learning by use of mutually different training datasets. The determination section can switch the learning model to be used for determination among the multiple learning models.

公开(公告)号：US20210366750A1

公开(公告)日：2021-11-25

申请号：US17251859

申请日：2020-01-23

Applicant: SPP TECHNOLOGIES CO., LTD.

Inventor： Keisuke SUNABA ,  Yuki FUJIWARA

IPC: H01L21/67 ,  H01L21/66 ,  H01L21/683 ,  H01L21/687 ,  G06N20/00

Abstract: Provided is an abnormality detection apparatus and the like capable of quickly and accurately detecting lifting abnormality of a substrate attributable to detachment failure of a substrate from an electrostatic chuck, or the like. An abnormality detection apparatus 100 includes a measurement section 2 configured to measure a parameter having a correlation with load applied to a lifting mechanism 4; and a detection section 3 configured to detect lifting abnormality of a substrate S. The detection section 3 includes a learning model 31 generated by using machine learning, in which the learning model 31 receives, as input, a plurality of measurements of the parameter continuously measured by the measurement section 2 during lifting-up of the substrate S by the lifting mechanism 4, and outputs a level of lifting abnormality of the substrate S.