Journal of Engineering, Project, and Production Management, 2026, 16(2), 2025-195
Production Process Modeling in Textile Industry via Knowledge Graph and Graph Spatiotemporal Attention Networks
1 Lecturer,
School of Arts, Taishan University, Tai'an, 271021, China, E-mail:
starwater999@126.com (corresponding author).
2 Lecturer, School of Arts, Taishan
University, Tai'an, 271021, China.
Production Management
Received September 4, 2025; revised October 20, 2025; accepted October 21, 2025
Available online March 7, 2026
Abstract: The textile industry is a pillar of the national economy. Due to the fragmentation of production factors, insufficient capture of spatiotemporal characteristics, and slow response to dynamic adjustments, current clothing production faces problems such as inefficient process coordination and lagging dynamic scheduling. These issues manifest as a high proportion of waiting time for process connection and low equipment utilization. The study combines knowledge graph with graph spatiotemporal attention network to construct a production process model for textile and clothing industry and conducts research on production process prediction. The results indicated that the average accuracy of the proposed model kept rising and finally neared 1.00, which was notably superior to that of other comparative models. The average precision of the proposed model ultimately exceeded 0.95, accurately matching the process collaboration requirements for multi-variety production. For the proposed model, its mean absolute error remained stable within a range of 0.15. The prediction accuracy of different production processes ranged from 1.87 to 2.36, with a root mean square error of 2.87 to 3.52 and an R2 of 0.91 to 0.95. The prediction error was reduced by 33.8%-49.2%. The research method can effectively model and predict the clothing production process, providing accurate and efficient decision support for the textile industry's clothing production, and improving production efficiency and quality.
Keywords: Textile industry, clothing production, knowledge graph, graph spatiotemporal attention network, gated recurrent unit.
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Citation: Hou, R. and Ma, Y. (2026). Production Process Modeling in Textile Industry via Knowledge Graph and Graph Spatiotemporal Attention Networks. Journal of Engineering, Project, and Production Management, 16(2), 2025-195.
