Editorial
Augmented reality-based intelligent manufacturing system for clothing customization: user immersive interaction and process visualization method
@ARTICLE{10.4108/eetsis.13960, author={Zhihui Li}, title={Augmented reality-based intelligent manufacturing system for clothing customization: user immersive interaction and process visualization method}, journal={EAI Endorsed Transactions on Scalable Information Systems}, volume={13}, number={5}, publisher={EAI}, journal_a={SIS}, year={2026}, month={9}, keywords={Clothing customization, Intelligent manufacturing, Process visualization, Knowledge graph, Digital twin}, doi={10.4108/eetsis.13960} }- Zhihui Li
Year: 2026
Augmented reality-based intelligent manufacturing system for clothing customization: user immersive interaction and process visualization method
SIS
EAI
DOI: 10.4108/eetsis.13960
Abstract
INTRODUCTION: AR-based clothing customization improves user interaction, but multimodal customer requirements remain weakly connected to process planning and shop-floor scheduling. OBJECTIVES: This study develops a closed-loop method that converts immersive interaction data into executable manufacturing decisions. METHODS: A KG-DT-MARL framework was developed to encode body scans, speech, gestures, touch inputs, and fabric preferences into a six-element semantic graph, synchronize order, equipment, material, process, and quality states through a digital twin, and perform constraint-guided multi-agent scheduling. RESULTS: The framework achieved 96.38% requirement-parsing accuracy, 95.74% process-chain generation accuracy, 91.86% resource utilization, and 94.62% on-time delivery under the tested order and disturbance scenarios. CONCLUSION: The framework provides a closed-loop connection between immersive customization and visualized manufacturing execution.
Copyright © 2026 Zhihui Li, licensed to EAI. This is an open access article distributed under the terms of the CC BY-NC-SA 4.0, which permits copying, redistributing, remixing, transformation, and building upon the material in any medium so long as the original work is properly cited.