A security-enhanced equipment predictive maintenance solution for the ETO manufacturing

IF 1.5 4区计算机科学 Q3 COMPUTER SCIENCE, INFORMATION SYSTEMS

International Journal of Network Management Pub Date : 2024-02-17 DOI:10.1002/nem.2263

Xiangyu Cao, Zhengjun Jing, Xiaorong Zhao, Xiaolong Xu

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Abstract

With the rapid advancement of intelligent manufacturing, ensuring equipment safety has become a crucial prerequisite for enterprise production. In the engineer-to-order (ETO) production mode, characterized by diverse equipment types and frequent adjustments in production lines, equipment maintenance has become increasingly complex. Traditional maintenance plans are no longer adequate to meet the evolving demands of equipment maintenance. This paper proposes a security-enhanced predictive maintenance scheme specifically designed for ETO-type production equipment. The scheme utilizes industrial Internet of Things (IIoT) technology to monitor machines and equipment, constructs prediction models using machine learning methods, and reinforces the security of the prediction system through adoption of a decentralized architecture with blockchain distributed storage. In this experiment, six supervised learning models were compared, and it was found that the model based on the random forest algorithm achieved an outstanding accuracy rate of 98.88%. Furthermore, the average total response time for generating predictions within the system is 2.0 s, demonstrating a performance suitable for practical equipment maintenance applications.

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针对 ETO 制造业的安全增强型设备预测性维护解决方案

随着智能制造的快速发展，确保设备安全已成为企业生产的重要前提。在按订单生产（ETO）模式下，设备类型多样，生产线调整频繁，设备维护变得日益复杂。传统的维护计划已无法满足不断发展的设备维护需求。本文提出了一种专为 ETO 型生产设备设计的安全增强型预测性维护方案。该方案利用工业物联网（IIoT）技术监控机器设备，使用机器学习方法构建预测模型，并通过采用区块链分布式存储的去中心化架构来加强预测系统的安全性。本实验比较了六种监督学习模型，发现基于随机森林算法的模型准确率高达 98.88%，表现出色。此外，系统内生成预测的平均总响应时间为 2.0 秒，表现出适合实际设备维护应用的性能。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

International Journal of Network Management COMPUTER SCIENCE, INFORMATION SYSTEMS-TELECOMMUNICATIONS

CiteScore

5.10

自引率

6.70%

发文量

审稿时长

>12 weeks

期刊介绍： Modern computer networks and communication systems are increasing in size, scope, and heterogeneity. The promise of a single end-to-end technology has not been realized and likely never will occur. The decreasing cost of bandwidth is increasing the possible applications of computer networks and communication systems to entirely new domains. Problems in integrating heterogeneous wired and wireless technologies, ensuring security and quality of service, and reliably operating large-scale systems including the inclusion of cloud computing have all emerged as important topics. The one constant is the need for network management. Challenges in network management have never been greater than they are today. The International Journal of Network Management is the forum for researchers, developers, and practitioners in network management to present their work to an international audience. The journal is dedicated to the dissemination of information, which will enable improved management, operation, and maintenance of computer networks and communication systems. The journal is peer reviewed and publishes original papers (both theoretical and experimental) by leading researchers, practitioners, and consultants from universities, research laboratories, and companies around the world. Issues with thematic or guest-edited special topics typically occur several times per year. Topic areas for the journal are largely defined by the taxonomy for network and service management developed by IFIP WG6.6, together with IEEE-CNOM, the IRTF-NMRG and the Emanics Network of Excellence.