Title: Design and research of IIoT intelligent automatic production line security monitoring system based on digital twin

Authors: Mengjia Lian; Lanqing Li; Shiyu Wang; Chunxiao Wang; Mingshi Li

Addresses: School of Mathematics and Information Engineering, Longyan University, Longyan, Fujian, China ' Institute of Software, China Industrial Control Systems Cyber Emergency Response Team, Shijingshan, Beijing, China ' Shenyang CASNC Technology Co., Ltd., Shenyang, China ' Business Unit of Digital City, Glodon Company, Haidian, Beijing, China ' Institute of Software, China Industrial Control Systems Cyber Emergency Response Team, Shijingshan, Beijing, China

Abstract: The paper proposes a security monitoring method of intelligent automatic production lines to address the issues such as the inability to proactively predict instrument failures and inconvenient daily maintenance, and establishes a security monitoring architecture of intelligent automatic production lines. The architecture specifically includes four parts: the physical model of the production line, the virtual model of the production line, the twin data of the production line and the digital twin service platform. Furthermore, the twin data of the production line are effectively analysed based on the fault hybrid prediction method, which can predict the possible faults and existing security risks that the production line is running. The intelligent automatic production line security monitoring method based on digital twins has the ability to predict and maintain the possible faults in the production line while ensuring normal production and processing, which can improve the stability of the production line.

Keywords: industrial internet of things; intelligent automatic production line; security monitoring; failure prediction.

DOI: 10.1504/IJCAT.2026.151374

International Journal of Computer Applications in Technology, 2026 Vol.78 No.1, pp.13 - 24

Received: 03 Apr 2025
Accepted: 26 Jun 2025
Published online: 26 Jan 2026 *

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