Recognition of material status in workshop and logistics automatic scheduling technology based on RestNet

Youfu Rao; Yi Liu; Guotong Zou; Zuozhi Zhang; Wei Wen

doi:10.1117/12.2627187

14 February 2022 Recognition of material status in workshop and logistics automatic scheduling technology based on RestNet

Youfu Rao, Yi Liu, Guotong Zou, Zuozhi Zhang, Wei Wen

Author Affiliations +

Proceedings Volume 12161, 4th International Conference on Informatics Engineering & Information Science (ICIEIS2021); 1216118 (2022) https://doi.org/10.1117/12.2627187
Event: 4th International Conference on Informatics Engineering and Information Science, 2021, Tianjin, China

Abstract

Material transfer and material status monitoring have always been an important part of operation and maintenance in the workshop. Too much reliance on manual operation will greatly reduce work efficiency and cause frequent errors. This article is based on Residual Neural Network (ResNet) transfer learning (TL) for model training. The status of material points in the workshop, namely empty frame, no frame, and full-frame, has been well recognized by using a small amount of surveillance video stream data for image analysis, which realizes the reverse optimization of the model. The accuracy of material point status recognition is as high as 99.7%. Based on the material point status recognition technology, the manufacturing operation management system interface can be called through the HTTP protocol to issue tasks, and the intelligent logistics system can be combined to realize the automatic circulation of materials in the workshop and improve production efficiency.

Citation Download Citation

Youfu Rao, Yi Liu, Guotong Zou, Zuozhi Zhang, and Wei Wen "Recognition of material status in workshop and logistics automatic scheduling technology based on RestNet", Proc. SPIE 12161, 4th International Conference on Informatics Engineering & Information Science (ICIEIS2021), 1216118 (14 February 2022); https://doi.org/10.1117/12.2627187

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KEYWORDS

Data modeling

Manufacturing

Image classification

Image quality

Neural networks

Video surveillance

Video

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