Industry 4.0 is moving forward under technology upgrades, utilizing information technology to improve the intelligence of the industry, whereas Industry 5.0 is value-driven, aiming to focus on essential societal needs, values, and responsibility. The manufacturing industry is currently moving towards the integration of productivity enhancements and sustainable human employment. Such a transformation has deeply changed the human–machine interaction (HMI), among which digital twin (DT) and extended reality (XR) are two cutting-edge technologies. A manufacturing DT offers an opportunity to simulate, monitor, and optimize the machine. In the meantime, XR empowers HMI in the industrial field. This paper presents an XR application framework for DT-based services within a manufacturing context. This work aims to develop a technological framework to improve the efficiency of the XR application development and the usability of the XR-based HMI systems. We first introduce four layers of the framework, including the perception layer with the physical machine and its ROS-based simulation model, the machine communication layer, the network layer containing three kinds of communication middleware, and the Unity-based service layer creating XR-based digital applications. Subsequently, we conduct the responsiveness test for the framework and describe several XR industrial applications for a DT-based smart crane. Finally, we highlight the research challenges and potential issues that should be further addressed by analyzing the performance of the whole framework.
Digital twins (DTs) and eXtended Reality (XR) are two core technological enablers for engineering in the Metaverse that can accelerate the human-centric Industry 5.0 transformation. The digital twin technology provides a digital representation of a physical asset with data linkages for inspection, monitoring, and prediction of complex processes or systems, while eXtended reality offers real-and-virtual combined environments for human users to interact with machines. However, the synergies between digital twins and eXtended reality remain understudied. This work addresses this research gap by introducing a novel method “TwinXR” that leverages ontology-based descriptions of Digital twins, i.e., digital twin documents, in industrial eXtended reality applications. To ease the use of the TwinXR method, we publish a Unity package that allows data flow and conversion between eXtended reality applications and digital twin documents on the server. Finally, the work applies the TwinXR method in two industrial eXtended reality applications involving overhead cranes and a robot arm to demonstrate the use and indicate the validity of the method. We conclude that the TwinXR method is a promising way to advance the synergies between digital twins and eXtended reality: For eXtended reality, TwinXR enables efficient and scalable eXtended reality development; For digital twins, TwinXR unlocks and demonstrates the potential of digital twins for data interchange and system interoperation. Future work includes introducing more detailed principles of Semantic Web and Knowledge Graph, as well as developing factory-level TwinXR-compatible applications.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.