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Abstract
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.
Original language | English |
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Article number | 6030 |
Journal | Applied Sciences (Switzerland) |
Volume | 12 |
Issue number | 12 |
DOIs | |
Publication status | Published - 14 Jun 2022 |
MoE publication type | A1 Journal article-refereed |
Keywords
- digital twin
- extended reality
- human-machine interaction
- framework
- crane
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Responsiveness test data for XR application development framework
Yang, C. (Creator), Zenodo, 7 Jun 2022
Dataset
Projects
- 1 Finished
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MACHINAIDE: MACHINAIDE - Knowledge based services for and optimization of machines
Tammi, K., Ala-Laurinaho, R., Autiosalo, J., Hietala, J., Salminen, P., Sahoo, S., Yang, C., Mattila, J., Tu, X. & Juhanko, J.
01/10/2019 → 30/04/2023
Project: Business Finland: Other research funding