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- Title
CNN-Based Defect Inspection for Injection Molding Using Edge Computing and Industrial IoT Systems.
- Authors
Ha, Hyeonjong; Jeong, Jongpil
- Abstract
Currently, the development of automated quality inspection is drawing attention as a major component of the smart factory. However, injection molding processes have not received much attention in this area of research because of product diversity, difficulty in obtaining uniform quality product images, and short cycle times. In this study, we proposed a defect inspection system for injection molding in edge intelligence. Using data augmentation, we solved the data shortage and imbalance problem of small and medium-sized enterprises (SMEs), introduced the actual smart factory method of the injection process, and measured the performance of the developed artificial intelligence model. The accuracy of the proposed model was more than 90%, proving that the system can be applied in the field.
- Subjects
CONVOLUTIONAL neural networks; EDGE computing; ARTIFICIAL intelligence; DATA augmentation; SMALL business; INJECTION molding; MAGNETIC flux leakage
- Publication
Applied Sciences (2076-3417), 2021, Vol 11, Issue 14, p6378
- ISSN
2076-3417
- Publication type
Article
- DOI
10.3390/app11146378