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Title: Intelligent monitoring method for variable working conditions in intelligent manufacturing systems under digital twin

Authors: Yunlong Zhao; Man Hu

Addresses: Engineering Training Center, Shandong University, Jinan 250100, Shandong, China ' Asset and Laboratory Management Department, Shandong University, Jinan 250100, Shandong, China

Abstract: This study presents a digital twin (DT)-based intelligent monitoring method for intelligent manufacturing systems (IMS) under variable working conditions. A five-dimensional DT architecture is designed to enable real-time data acquisition, synchronisation, and virtual-physical mapping. Linear regression is applied for data processing, enhancing monitoring accuracy. By constructing a DT virtual model of the production line, the system achieves dynamic monitoring and early anomaly detection. Experimental comparisons with genetic algorithm-based monitoring show the DT approach improves average monitoring accuracy by 8.47%, demonstrating its superior reliability, real-time performance, and potential for enhancing production quality and safety in complex, changing environments.

Keywords: intelligent monitoring; variable working condition; digital twin; intelligent manufacturing system; virtual model.

DOI: 10.1504/IJETP.2025.149452

International Journal of Energy Technology and Policy, 2025 Vol.20 No.6, pp.51 - 73

Received: 14 Feb 2025
Accepted: 25 Jul 2025
Published online: 31 Oct 2025 *