Research on Quality Monitoring Platform and Resource Scheduling Algorithm Based On Machine Vision
The quality monitoring platform and resource scheduling algorithm based on machine vision are currently the research areas of concern in the manufacturing and logistics industries. It is targeted to the industry and the actual production environment with the combination of manufacturing enterprises....
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| Published in: | Procedia computer science Vol. 259; pp. 1064 - 1071 |
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| Main Author: | |
| Format: | Journal Article |
| Language: | English |
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Elsevier B.V
2025
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| ISSN: | 1877-0509, 1877-0509 |
| Online Access: | Get full text |
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| Abstract | The quality monitoring platform and resource scheduling algorithm based on machine vision are currently the research areas of concern in the manufacturing and logistics industries. It is targeted to the industry and the actual production environment with the combination of manufacturing enterprises. It is proposed to apply automated image processing and machine learning algorithms to the quality monitoring platform, which not only improves the inspection accuracy, but also reduces the defect detection cost of the product. To this end, the research in this paper stems from relevant literature and empirical research, focusing on the working principle and key technologies of a quality monitoring platform and resource scheduling algorithm based on machine vision. The research methods mainly include: data acquisition, image processing, feature extraction, classification algorithm research and resource scheduling strategy. The research results show that the quality monitoring platform based on machine vision has high inspection accuracy and stability, and can effectively extract product features and detect defects. At the same time, the resource scheduling algorithm can optimize resource scheduling and human power allocation, improve production efficiency and production consistency. |
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| AbstractList | The quality monitoring platform and resource scheduling algorithm based on machine vision are currently the research areas of concern in the manufacturing and logistics industries. It is targeted to the industry and the actual production environment with the combination of manufacturing enterprises. It is proposed to apply automated image processing and machine learning algorithms to the quality monitoring platform, which not only improves the inspection accuracy, but also reduces the defect detection cost of the product. To this end, the research in this paper stems from relevant literature and empirical research, focusing on the working principle and key technologies of a quality monitoring platform and resource scheduling algorithm based on machine vision. The research methods mainly include: data acquisition, image processing, feature extraction, classification algorithm research and resource scheduling strategy. The research results show that the quality monitoring platform based on machine vision has high inspection accuracy and stability, and can effectively extract product features and detect defects. At the same time, the resource scheduling algorithm can optimize resource scheduling and human power allocation, improve production efficiency and production consistency. |
| Author | Han, Wei |
| Author_xml | – sequence: 1 givenname: Wei surname: Han fullname: Han, Wei email: 582008886@qq.com organization: Xi’an Fanyi University, Xi’an 710105, Shaanxi, China |
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| Cites_doi | 10.1038/s41586-020-2038-x 10.1007/s10462-021-10102-3 10.1109/JIOT.2021.3103110 10.1016/j.inpa.2021.06.003 10.31871/WJRR.13.3.12 10.1007/s12393-022-09307-1 10.1016/j.xphs.2021.09.011 10.1016/j.jksuci.2018.06.006 10.1007/s10694-020-01064-z 10.1016/j.tibtech.2022.03.012 10.1007/s10845-019-01508-6 10.1109/JIOT.2020.2980432 10.1007/s40684-021-00343-6 10.1109/TII.2019.2896357 |
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| Keywords | Quality Monitoring Platform Minimize Cost Machine Vision Resource Scheduling Algorithm |
| Language | English |
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| Title | Research on Quality Monitoring Platform and Resource Scheduling Algorithm Based On Machine Vision |
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