AI Intelligent learning for Manufacturing Automation

Abstract: The garment industry is experiencing a transformative shift by integrating intelligent learning technologies, including machine learning (ML) and deep learning. This applied research with case study examines the application of Convolutional Neural Networks (CNNs) for automating quality control in garment manufacturing, specifically focusing on the detection of sewing lines in captured images. Manufacturers can enhance efficiency, improve product quality, and reduce operational costs by utilizing advanced data analytics and image processing techniques. The CNN model is trained to identify unique features of sewing lines, allowing for real-time comparisons between machine outputs and standard benchmarks. This intelligent learning approach not only streamlines the inspection process but also enables predictive maintenance and data-driven decision-making, fostering adaptability to market demands. The findings highlight the potential of AI-driven solutions to replace manual inspections, ultimately driving innovation and sustainability in garment production. As the industry evolves, embracing intelligent learning technologies will be crucial for manufacturers seeking to maintain a competitive edge in an increasingly dynamic marketplace. This research underscores the importance of preparing high-quality training data to optimize CNN performance and ensure effective garment quality control. Keywords: Artificial Intelligence, AI, Automation, Convolutional Neural Networks, Machine Learning, Garment Manufacturing, Quality Control. Title: AI Intelligent learning for Manufacturing Automation Author: Ray Wai Man Kong, Ding Ning, Theodore Ho Tin Kong International Journal of Mechanical and Industrial Technology ISSN 2348-7593 (Online) Vol. 13, Issue 1, April 2025 - September 2025 Page No: 1-9 Research Publish Journals Website: www.researchpublish.com Published Date: 05-April-2025 DOI: https://doi.org/10.5281/zenodo.15159741 Paper Download Link (Source) https://www.researchpublish.com/papers/ai-intelligent-learning-for-manufacturing-automation

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-04-05
DOI
https://doi.org/10.5281/zenodo.15159740
Primary Topic
Industrial Vision Systems and Defect Detection
Type
article
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article

AI Intelligent learning for Manufacturing Automation

Zenodo (CERN European Organization for Nuclear Research)
Industrial Vision Systems and Defect Detection
article

AI Intelligent learning for Manufacturing Automation

article en

Abstract

Abstract: The garment industry is experiencing a transformative shift by integrating intelligent learning technologies, including machine learning (ML) and deep learning. This applied research with case study examines the application of Convolutional Neural Networks (CNNs) for automating quality control in garment manufacturing, specifically focusing on the detection of sewing lines in captured images. Manufacturers can enhance efficiency, improve product quality, and reduce operational costs by utilizing advanced data analytics and image processing techniques. The CNN model is trained to identify unique features of sewing lines, allowing for real-time comparisons between machine outputs and standard benchmarks. This intelligent learning approach not only streamlines the inspection process but also enables predictive maintenance and data-driven decision-making, fostering adaptability to market demands. The findings highlight the potential of AI-driven solutions to replace manual inspections, ultimately driving innovation and sustainability in garment production. As the industry evolves, embracing intelligent learning technologies will be crucial for manufacturers seeking to maintain a competitive edge in an increasingly dynamic marketplace. This research underscores the importance of preparing high-quality training data to optimize CNN performance and ensure effective garment quality control. Keywords: Artificial Intelligence, AI, Automation, Convolutional Neural Networks, Machine Learning, Garment Manufacturing, Quality Control. Title: AI Intelligent learning for Manufacturing Automation Author: Ray Wai Man Kong, Ding Ning, Theodore Ho Tin Kong International Journal of Mechanical and Industrial Technology ISSN 2348-7593 (Online) Vol. 13, Issue 1, April 2025 - September 2025 Page No: 1-9 Research Publish Journals Website: www.researchpublish.com Published Date: 05-April-2025 DOI: https://doi.org/10.5281/zenodo.15159741 Paper Download Link (Source) https://www.researchpublish.com/papers/ai-intelligent-learning-for-manufacturing-automation

Zenodo (CERN European Organization for Nuclear Research)
Industry, innovation and infrastructure
Openalex Percentile: Top 46%
Industrial Vision Systems and Defect Detection
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AI Intelligent learning for Manufacturing Automation · Zenodo (CERN European Organization for Nuclear Research) (2025) | TGRS Research Map | TGRS