Fabric Defect Analysis In Textile Manufacturing: Evaluating Methods For Generic And Jacquard Fabrics

Abstract

Regarding maintaining product quality and satisfying customer expectations, fabric defect analysis is vital in textile manufacturing. This research provides a comprehensive assessment of many techniques used for analyzing and pinpointing flaws in standard and Jacquard textiles. This study considers machine vision systems and AI-based algorithms as two examples of cutting-edge automation alongside more conventional human inspection procedures. Manual inspection techniques are extensively reviewed in the first section, with particular emphasis on these techniques' inherent subjectivity and resource inefficiency. More objective and effective defect detection techniques are highlighted as a solution to the problems caused by human bias. The research then looks into automated methods, examining how recent developments in image processing, computer vision, and pattern recognition have the potential to greatly improve the accuracy and speed with which defects may be detected. The major emphasis of this investigation is the use of AI, namely machine learning and deep learning models, for fabric defect identification. This demonstrates how AI may revolutionize textile manufacturing by automating flaw identification and categorization processes. Accuracy, efficiency, scalability, cost-effectiveness, and adaptation to varied fabric compositions, such as basic and complicated Jacquard textiles, are only some aspects considered throughout the evaluation. In addition, the research addresses the problems and opportunities in the field of fabric defect analysis right now. The paper presents prospective improvements, such as hybrid methods and real-time monitoring systems, to solve current constraints and pave the way for a more robust defect analysis framework. These innovations aim to contribute to sustainable practices and customer happiness in the textile manufacturing industry by fostering effective quality monitoring and production optimization. In conclusion, this study provides a thorough comprehension of fabric defect analysis procedures, which is helpful for professionals and academics in the field. The results fuel the never-ending development of quality assurance techniques, resulting in improvements that raise standards, shorten production times, and give the textile business a fighting chance in the market.