Knowledge transfer in Digital Twins: The methodology to develop Cognitive Digital Twins

IF 4.6 2区工程技术 Q2 ENGINEERING, MANUFACTURING

CIRP Journal of Manufacturing Science and Technology Pub Date : 2024-07-02 DOI:10.1016/j.cirpj.2024.06.007

Rosario Davide D’Amico , Arkopaul Sarkar , Mohamed Hedi Karray , Sri Addepalli , John Ahmet Erkoyuncu

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引用次数: 0

Abstract

In the realm of Digital Twins (DTs), industry experts have emphasised the pivotal concept of the Federation of Twins, envisioning seamless collaboration across sectors driven by shared semantics. In response to this challenge, the Cognitive Digital Twin (CDT) integrates the DT framework with formal semantics, specifically ontologies. This paper introduces a comprehensive five-step methodology for CDT development. Furthermore, it becomes possible to incorporate human expertise into the DT ecosystem by adopting an ontological approach. The CDT enhances DT services with advanced reasoning capabilities, leading to a profound semantic enrichment of the data. The presented methodology has been validated using a use case where the CDT is employed to detect malfunctions, significantly reducing manual intervention. This paper advocates for the adoption of CDTs, which represent a harmonious fusion of formal semantics and human expertise, enhancing system efficiency and operational performance.

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数字孪生中的知识转移：开发认知数字孪生的方法论

在数字孪生（DTs）领域，行业专家强调了孪生联盟（Federation of Twins）这一关键概念，希望通过共享语义实现跨部门的无缝协作。为了应对这一挑战，认知数字孪生（CDT）将数字孪生框架与正式语义（特别是本体）整合在一起。本文介绍了 CDT 开发的五步综合方法。此外，通过采用本体论方法，将人类专业知识纳入数字孪生生态系统成为可能。CDT 通过先进的推理能力增强了 DT 服务，从而极大地丰富了数据的语义。本文介绍的方法已通过一个使用案例进行了验证，在该案例中，CDT 被用于检测故障，大大减少了人工干预。本文提倡采用 CDT，它代表了正式语义与人类专业知识的和谐融合，可提高系统效率和运行性能。

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

CIRP Journal of Manufacturing Science and Technology Engineering-Industrial and Manufacturing Engineering

CiteScore

9.10

自引率

6.20%

发文量

166

审稿时长

63 days

期刊介绍： The CIRP Journal of Manufacturing Science and Technology (CIRP-JMST) publishes fundamental papers on manufacturing processes, production equipment and automation, product design, manufacturing systems and production organisations up to the level of the production networks, including all the related technical, human and economic factors. Preference is given to contributions describing research results whose feasibility has been demonstrated either in a laboratory or in the industrial praxis. Case studies and review papers on specific issues in manufacturing science and technology are equally encouraged.