Semantic Block Reconstruction for Refactoring Industrial Control Systems in Flexible Manufacturing

IF 9.8 1区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

IEEE Transactions on Industrial Informatics Pub Date : 2026-10-01 Epub Date: 2026-07-07 DOI:10.1109/TII.2026.3701792

Maodong Lin;Qinyun Hu;Wenchao Zou;Klaus Wendelberger;Wenbin Dai

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引用次数: 0

Abstract

Aiming for flexible manufacturing, industrial control software must react rapidly to meet new requirements resulting from product customization and the convergence of operations and information technology. Software reusability is one of the key performance indicators that accelerates this process. However, due to the variety and complexity of platforms and requirements, the reusability of industrial control software across various projects often faces challenges from both cost and efficiency perspectives. This article proposes a reusable block identification method for extracting semantics from legacy industrial automation programs, refactoring them into platform-independent behavior models that can be further generated in any programming language for rapid migration and flexible integration. Experimental results demonstrate that this method can identify reusable modules in functionally similar programs with differing syntax. This method improves the efficiency of industrial control software development and reduces the efforts required.

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基于语义块重构的柔性制造工业控制系统

针对柔性制造，工业控制软件必须快速响应，以满足产品定制和操作与信息技术融合带来的新要求。软件可重用性是加速这一过程的关键性能指标之一。然而，由于平台和需求的多样性和复杂性，工业控制软件在各种项目中的可重用性经常面临成本和效率方面的挑战。本文提出了一种可重用的块识别方法，用于从遗留工业自动化程序中提取语义，并将其重构为与平台无关的行为模型，这些模型可以用任何编程语言进一步生成，以实现快速迁移和灵活集成。实验结果表明，该方法可以识别功能相似但语法不同的程序中的可重用模块。该方法提高了工业控制软件开发的效率，减少了工作量。

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

IEEE Transactions on Industrial Informatics 工程技术-工程：工业

CiteScore

24.10

自引率

8.90%

发文量

1202

审稿时长

5.1 months

期刊介绍： The IEEE Transactions on Industrial Informatics is a multidisciplinary journal dedicated to publishing technical papers that connect theory with practical applications of informatics in industrial settings. It focuses on the utilization of information in intelligent, distributed, and agile industrial automation and control systems. The scope includes topics such as knowledge-based and AI-enhanced automation, intelligent computer control systems, flexible and collaborative manufacturing, industrial informatics in software-defined vehicles and robotics, computer vision, industrial cyber-physical and industrial IoT systems, real-time and networked embedded systems, security in industrial processes, industrial communications, systems interoperability, and human-machine interaction.