Flexible Automation and Intelligent Manufacturing: Establishing Bridges for More Sustainable Manufacturing Systems - Proceedings of FAIM 2023, June 18-22, 2023, Porto, Portugal, Volume 2: Industrial Management
Flexible Automation and Intelligent Manufacturing: Establishing Bridges for More Sustainable Manufacturing Systems - Proceedings of FAIM 2023, June 18-22, 2023, Porto, Portugal, Volume 2: Industrial Management
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灵活自动化和智能制造：为更可持续的制造系统建立桥梁 - FAIM 2023 会议记录，2023 年 6 月 18-22 日，葡萄牙波尔图，第 2 卷：工业管理
DOI：
10.1007/978-3-031-38165-2_136
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发表时间：
2024
期刊：
影响因子：
--
通讯作者：
Vasantha G
中科院分区：
文献类型：
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作者：
Vasantha G
数字传感技术是实现工业4.0的关键，因为它们提高了生产率，有助于实时决策，并为制造工厂提供了灵活性和敏捷性。然而，实施这些技术可能是一个巨大的挑战，因为需要考虑制造工厂中的各种因素，例如不同的设备、零散的知识、定制要求、多种替代技术以及试错过程中涉及的大量成本。提出了一种知识图(KG)方法来简化工厂移动跟踪系统的实施。KG方法利用一个集成了制造目标、活动、资源、环境、工厂移动、数据、基础设施和决策支持系统的知识表示参考模型。这个参考模型有助于对从研究摘要中提取的关键短语进行分类，并在它们之间建立知识关系。通过分析30篇研究摘要创建的综合KG正确回答了关于实施工厂移动跟踪系统的搜索查询。这种方法为开发软件系统以通过自动解释、推理和建议支持运动跟踪实现奠定了基础。
Digital sensing technologies are essential for realizing Industry 4.0, as they enhance productivity, assist with real-time decision-making, and provide flexibility and agility in manufacturing factories. However, implementing these technologies can be a significant challenge due to the need to consider various factors in manufacturing factories, such as heterogeneous equipment, fragmented knowledge, customization requirements, multiple alternative technologies, and the substantial costs involved in the trial-and-error process. A Knowledge Graph (KG) approach is proposed to streamline the implementation of the factory movement tracking system. The KG approach utilizes a knowledge representation reference model that integrates manufacturing objective, activity, resource, environment, factory movement, data, infrastructure, and decision support system. This reference model aids in classifying key phrases extracted from research abstracts and establishing knowledge relationships among them. A synthesized KG, created by analyzing thirty research abstracts, has correctly answered search queries about implementing the factory movement tracking system. This approach establishes a pathway for developing a software system to support movement tracking implementation through automatic interpretation, reasoning, and suggestions.