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1.
公开(公告)号:US20240193759A1
公开(公告)日:2024-06-13
申请号:US18533652
申请日:2023-12-08
Applicant: CREFLE Inc.
Inventor: Eunseok SEO
IPC: G06T7/00 , G06Q10/0633 , G06V10/25
CPC classification number: G06T7/0008 , G06Q10/0633 , G06V10/25 , G06T2207/30164 , G06V2201/07
Abstract: An artificial intelligence-based process defect detection system may include: a photographing module that collects image data by capturing a process that progresses on an object; a machine learning model that generates work data that is a result of recognizing and reading the object based on the image data; and a detection module that receives instruction data recorded regarding a process for an object optimized for product production, detects a defect or a non-defect by comparing the work data with the instruction data, and generates defect information when the process is defective.
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2.
公开(公告)号:US20240192645A1
公开(公告)日:2024-06-13
申请号:US18533660
申请日:2023-12-08
Applicant: CREFLE Inc.
Inventor: Eunseok SEO , Myungjoong JEON
CPC classification number: G05B13/0265 , G06T7/001 , G06V10/761 , G06T2207/30108
Abstract: An artificial intelligence-based process optimization method includes: executing one or more unit processes in different sequences, wherein, in the unit processes, an entire process for manufacturing a product is executed in a series of sequences, evaluating each of the unit processes in accordance with an evaluation criterion by a reading module while each execution progresses, collecting execution data generated by cumulatively evaluating the unit processes in sequence, and transmitting the execution data to a determination module; and generating instruction data as the execution data for an optimal execution determined among a plurality of executions in which the unit processes are executed in different sequences by the determination module, based on the execution data of the reading module.
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