A digital twin-based architecture for human-humanoid-machine interaction (DT-H2MI) in smart manufacturing

Abstract This paper integrates the well-established concepts of digital twins (DTs), human-in-the-loop (HITL) systems, humanoid robots (HRs), and human–machine interaction (HMI) to introduce a conceptual architecture for smart manufacturing. DT-H 2 MI offers a transformative approach to enhancing interactions between humans, humanoids, and machines by creating an advanced digital replica of a physical system that not only mirrors and simulates real-world assets but also incorporates artificial intelligence and cognitive capabilities. Leveraging real-time data streams and cloud/edge computing platforms, DT-H 2 MI is designed to enable dynamic interactions, thereby improving manufacturing efficiency and flexibility. This framework aligns with Industry 5.0’s principles, aiming to enhance sustainability, resiliency, and human-centrism within manufacturing operations. By introducing humanoids into a unified DT framework, the architecture is intended to support seamless human–machine interaction and cognitive automation, with the aim of achieving real-time adaptability beyond conventional Industry 4.0/5.0 approaches. The DT-H 2 MI architecture consists of three fundamental modules: the avatar-human system (AHS), the cyber-physical system (CPS), and the physical artificial intelligence system (PAIS), along with middleware and third-party cloud services. This research lays a crucial foundation for developing the next generation of manufacturing systems and processes, enabling more efficient and intuitive interactions across the manufacturing ecosystem. DT-H 2 MI is presented as a conceptual reference architecture developed following the Design Science Research (DSR) paradigm. A potential welding case study demonstrates how it can be instantiated, rather than providing empirical validation, and its performance claims are formulated as testable propositions with metrics and acceptance criteria for future evaluation.

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Publication Details

Journal
Journal of Intelligent Manufacturing
Published
2026-11-10
DOI
https://doi.org/10.1007/s10845-026-03024-w
Primary Topic
Digital Transformation in Industry
Type
article
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article

A digital twin-based architecture for human-humanoid-machine interaction (DT-H2MI) in smart manufacturing

Mahdi Sadeqi Bajestani, Duck Bong Kim, Duhwan Mun
Journal of Intelligent Manufacturing
Digital Transformation in Industry
article

A digital twin-based architecture for human-humanoid-machine interaction (DT-H2MI) in smart manufacturing

Mahdi Sadeqi Bajestani, Duck Bong Kim, Duhwan Mun
article en

Abstract

Abstract This paper integrates the well-established concepts of digital twins (DTs), human-in-the-loop (HITL) systems, humanoid robots (HRs), and human–machine interaction (HMI) to introduce a conceptual architecture for smart manufacturing. DT-H 2 MI offers a transformative approach to enhancing interactions between humans, humanoids, and machines by creating an advanced digital replica of a physical system that not only mirrors and simulates real-world assets but also incorporates artificial intelligence and cognitive capabilities. Leveraging real-time data streams and cloud/edge computing platforms, DT-H 2 MI is designed to enable dynamic interactions, thereby improving manufacturing efficiency and flexibility. This framework aligns with Industry 5.0’s principles, aiming to enhance sustainability, resiliency, and human-centrism within manufacturing operations. By introducing humanoids into a unified DT framework, the architecture is intended to support seamless human–machine interaction and cognitive automation, with the aim of achieving real-time adaptability beyond conventional Industry 4.0/5.0 approaches. The DT-H 2 MI architecture consists of three fundamental modules: the avatar-human system (AHS), the cyber-physical system (CPS), and the physical artificial intelligence system (PAIS), along with middleware and third-party cloud services. This research lays a crucial foundation for developing the next generation of manufacturing systems and processes, enabling more efficient and intuitive interactions across the manufacturing ecosystem. DT-H 2 MI is presented as a conceptual reference architecture developed following the Design Science Research (DSR) paradigm. A potential welding case study demonstrates how it can be instantiated, rather than providing empirical validation, and its performance claims are formulated as testable propositions with metrics and acceptance criteria for future evaluation.

Journal of Intelligent Manufacturing
University of Georgia (US), Korea University (KR), Hasselt University (BE)
Digital Transformation in Industry
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