TY  - JOUR
TI  - Application of machine learning methodology for textile defect detection
AU  - Gokhan Nalbant, Kemal
AU  - Bozkurt, Berkan
T2  - Industria Textila
AB  - This study investigates the use of artificial intelligence (AI) and machine learning (ML) technologies in the textile industry,
particularly emphasising how they improve operational efficiency and enhance product quality. Using a comprehensive
dataset obtained from textile manufacturing operations, a specially tailored convolutional neural network (CNN) model
and a long-short-term memory (LSTM) model are implemented for the classification of fabric defects. After undergoing
intensive training and validation, our model showed significant improvements in performance over a large number of
epochs. The CNN model started with 61.15% accuracy initially and reached 92.91% accuracy after training. The
validation accuracy increased from 72.44% to 92.05%. On the same dataset, the LSTM model resulted in 86.11%
training accuracy and 87.80% validation accuracy. The significant improvements in accuracy highlight the power of AI
and ML to not only improve classification accuracy but also boost overall operational performance by continuously
learning from fresh data inputs. Moreover, this research highlights the impact of AI and ML breakthroughs on textile
production as they optimise procedures, enhance efficiency, and strengthen competitive advantage. The findings
demonstrate that these technologies are a substantial advancement for the textile sector, providing powerful tools to
reduce faults, streamline production processes, and ultimately provide goods of superior quality. Therefore, the study
promotes the wider use of AI and ML technologies in the textile manufacturing industry, emphasising their crucial role in
driving future advancements and sustainable growth.
DA  - 2025/06/30/
PY  - 2025
DO  - 10.35530/IT.076.03.2024108
DP  - DOI.org (Crossref)
VL  - 76
IS  - 03
SP  - 372
EP  - 386
SN  - 12225347
UR  - https://www.revistaindustriatextila.ro/images/2025/3/09%20KEMAL%20INDUSTRIA%20TEXTILA%20no.3_2025.pdf
Y2  - 2025/07/08/17:39:28
ER  -