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.

公开(公告)号：US20240192675A1

公开(公告)日：2024-06-13

申请号：US18533646

申请日：2023-12-08

Applicant: CREFLE Inc.

Inventor： Eunseok Seo

IPC: G05B23/02 ,  G06T7/00

CPC classification number: G05B23/0275 ,  G05B23/024 ,  G06T7/0004

Abstract: An artificial intelligence-based process optimization management system may include: a reading module that, when receiving instruction data recorded for an optimal execution determined among a plurality of executions that are performed in different progress sequences of unit processes, which are part of a process for manufacturing a product, generates work data, which is a result of reading image data for a process that progresses on an object, so as to correspond to the instruction data; a detection module that receives the work data from the reading module and generates defect information for the process by comparing the work data with the instruction data; and an output module that outputs the defect information.

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

IPC: G05B13/02 ,  G06T7/00 ,  G06V10/74

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.