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An Inter-Disciplinary Modelling Approach in Industrial 5G/6G and Machine Learning Era

  • Recently, the fifth-generation (5G) cellular system has been standardised. As opposed to legacy cellular systems geared towards broadband services, the 5G system identifies key use cases for ultra-reliable and low latency communications (URLLC) and massive machine-type communications (mMTC). These intrinsic 5G capabilities enable promising sensor-based vertical applications and services such as industrial process automation. The latter includes autonomous fault detection and prediction, optimised operations and proactive control. Such applications enable equipping industrial plants with a sixth sense (6S) for optimised operations and fault avoidance. In this direction, we introduce an inter-disciplinary approach integrating wireless sensor networks with machine learning-enabled industrial plants to build a step towards developing this 6S technology. We develop a modular-based system that can be adapted to the vertical-specific elements. Without loss of generalisation, exemplary use cases are developed and presented including a faultRecently, the fifth-generation (5G) cellular system has been standardised. As opposed to legacy cellular systems geared towards broadband services, the 5G system identifies key use cases for ultra-reliable and low latency communications (URLLC) and massive machine-type communications (mMTC). These intrinsic 5G capabilities enable promising sensor-based vertical applications and services such as industrial process automation. The latter includes autonomous fault detection and prediction, optimised operations and proactive control. Such applications enable equipping industrial plants with a sixth sense (6S) for optimised operations and fault avoidance. In this direction, we introduce an inter-disciplinary approach integrating wireless sensor networks with machine learning-enabled industrial plants to build a step towards developing this 6S technology. We develop a modular-based system that can be adapted to the vertical-specific elements. Without loss of generalisation, exemplary use cases are developed and presented including a fault detection/prediction scheme, and a sensor density-based boundary between orthogonal and non-orthogonal transmissions. The proposed schemes and modelling approach are implemented in a real chemical plant for testing purposes, and a high fault detection and prediction accuracy is achieved coupled with optimised sensor density analysis.show moreshow less

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Metadaten
Author: Abdelrahim Mohamed, Hang Ruan, Mohamed Heshmat Hassan Abdelwahab, Bogdan DorneanuORCiD, Pei Xiao, Harvey Arellano-GarciaORCiD, Yang Gao, Rahim Tafazolli
URL:https://ieeexplore.ieee.org/document/9145434
DOI:https://doi.org/10.1109/ICCWorkshops49005.2020.9145434
ISBN:978-1-7281-7440-2
ISBN:978-1-7281-7441-9
ISSN:2474-9133
Title of the source (English):2020 IEEE International Conference on Communications Workshops (ICC Workshops)
Place of publication:Dublin, Ireland
Document Type:Conference publication peer-reviewed
Language:English
Year of publication:2020
First Page:1
Last Page:6
Faculty/Chair:Fakultät 3 Maschinenbau, Elektro- und Energiesysteme / FG Prozess- und Anlagentechnik
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