A digital twin-based architecture for human-humanoid-machine interaction (DT-H2MI) in smart manufacturing
Year: 2026
Type: article
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.
Institutions: Hasselt University, Korea University, University of Georgia
Language: English
Subfield: Industrial and Manufacturing Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $3,290
OpenAlex ID: W7225750175