What is it about?
This paper is about defect inspection that can be applied to artificial intelligence-based smart manufacturing.
Featured Image
Why is it important?
SmartmanufacturingandIndustry4.0aretransformingtraditionalmanufacturingprocessesbyutilizinginnovative technologies such as the artificial intelligence (AI) and internet of things (IoT) to enhance efficiency, reduce costs, and ensure product quality. In light of the recent advancement of Industry 4.0, identifying defects has become important for ensuring the quality of products during the manufacturing process. In this research, we present an ensemble methodology for accurately classifying hot rolled steel surface defects by combining the strengths of four pre-trained convolutional neural network (CNN) architectures: VGG16, VGG19, Xception, and Mobile-Net V2, compensating for their individual weaknesses.
Perspectives
It was meaningful to write a paper on a topic related to smart manufacturing with a PhD student who had been studying with me. Also, through this paper, many researchers and companies interested in AI-based smart manufacturing contacted me, and ultimately, I became more actively involved in related research.
JONGWON SEOK
Changwon National University
Read the Original
This page is a summary of: Steel Surface Defect Recognition in Smart Manufacturing Using Deep Ensemble Transfer Learning-Based Techniques, Computer Modeling in Engineering & Sciences, January 2025, Tsinghua University Press,
DOI: 10.32604/cmes.2024.056621.
You can read the full text:
Contributors
The following have contributed to this page
