Remote assistance, remote support, and visual assistance
09/09/2024
Explore the differences between remote assistance, remote support, and visual assistance to enhance the effectiveness
5G Retrofit of Machines for Realtime Applications of Augmented Reality
Written by
Florian Bartholomäus
Florian Bartholomäus
- TECHNOLOGY
- 4 min. reading time
Together with seven partners from research and industry, oculavis GmbH is developing Augmented Reality (AR) applications in “hard” real-time on the basis of the new 5G mobile network standard. Thus we are already able to utilize the advantages of this new technology for the Augmented Support solution oculavis SHARE. High transmission rates of up to 10 Gb enable extremely short latencies for video and audio transmissions from mobile devices to a remote expert. The use of extremely large CAD models as well as their visualization and overlaying on the basis of augmented reality also opens up new possibilities for the service and maintenance of machines and equipment. The integration of machine and sensor data in real time provides innovative approaches for process monitoring and control within the framework of the consortium project.
Motivation
Especially for complex components, where modern production facilities reach the limits of their flexibility, companies have to upgrade: with sensors and mobile devices that display large amounts of data with 5G and cloud technology almost without delay and support machine operators with new functions for process monitoring and control. 5G and Augmented Reality offer the opportunity to meet the new requirements for wireless communication within a network of machines, sensors and people. With the new mobile communications standard, data volumes can be transmitted at up to 10 gigabits per second and with low latencies between sensors, terminals and cloud and mainframe systems, ensuring time-critical communication on the shop floor as well.
Flexible systems with intelligent control and maximum capacity utilization
Together with seven partners, oculavis GmbH is developing a modular, expandable sensor cloud system for existing machines. This consists of 5G sensors and a flexible platform for control, evaluation and visualization. The 5GSensPRO project includes the following modules:
- Intelligent sensor hardware with a basic unit for data pre-processing and wireless transmission via 5G
- Innovative Visualisierungsschnittstellen auf Basis von Smart Glasses und Augmented Reality
- Tracking functions based on mobile networks for the identification of components and for the automatic assignment of suitable process and logistics data
- Uniform, system-wide communication protocols for data transmission and coupling of sensors and other components for fast and uncomplicated expansion of the overall system
- Smart Sensor Cloud as infrastructure for data processing, analysis and transfer to other systems
Tailoring to real applications in production together with partners from industry
The goal of the consortium in the 5GSensPRO project is to create a flexible production environment that meets the growing requirements of manufacturing complex components. The project partners jointly develop and test the 5GSensPRO system using the example of a highly dynamic manufacturing process for turbomachinery components. Sensors are mounted directly on the component and integrated directly into the manufacturing process. The display of sensor data and process control with mobile terminals and augmented reality in a overlaid display of the production environment offer the user a completely new way of interacting with the overall system. The following partners work together with oculavis within the research project 5GSensPRO:
- Fraunhofer-Institute for Production Technology IPT
- Marposs Monitoring Solutions GmbH
- Meastream GmbH
- QSQ Werkzeug- und Vorrichtungsbau
- CP Tech GmbH
- Ericsson GmbH
- MTU Aero Engines AG
The project “5GSensPRO – 5G-based sensor technology for monitoring in production” is funded by the European Regional Development Fund (EFRE) 2014-2020 (funding reference: EFRE 0801636).
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