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Wireless Communications for Smart Manufacturing and Industrial IoT: Existing Technologies, 5G and Beyond

Lookup NU author(s): Dr Husnain SheraziORCiD

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This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).


Abstract

© 2022 by the authors.Smart manufacturing is a vision and major driver for change in today’s industry. The goal of smart manufacturing is to optimize manufacturing processes through constantly monitoring, controlling, and adapting processes towards more efficient and personalised manufacturing. This requires and relies on technologies for connected machines incorporating a variety of computation, sensing, actuation, and machine to machine communications modalities. As such, understanding the change towards smart manufacturing requires knowledge of the enabling technologies, their applications in real world scenarios and the communication protocols and their performance to meet application requirements. Particularly, wireless communication is becoming an integral part of modern smart manufacturing and is expected to play an important role in achieving the goals of smart manufacturing. This paper presents an extensive review of wireless communication protocols currently applied in manufacturing environments and provides a comprehensive review of the associated use cases whilst defining their expected impact on the future of smart manufacturing. Based on the review, we point out a number of open challenges and directions for future research in wireless communication technologies for smart manufacturing.


Publication metadata

Author(s): Noor-A-Rahim M, John J, Firyaguna F, Sherazi HHR, Kushch S, Vijayan A, O'Connell E, Pesch D, O'Flynn B, O'Brien W, Hayes M, Armstrong E

Publication type: Article

Publication status: Published

Journal: Sensors

Year: 2023

Volume: 23

Issue: 1

Print publication date: 01/01/2023

Online publication date: 21/12/2022

Acceptance date: 12/12/2022

Date deposited: 23/05/2024

ISSN (electronic): 1424-8220

Publisher: MDPI

URL: https://doi.org/10.3390/s23010073

DOI: 10.3390/s23010073

Data Access Statement: Not applicable.

PubMed id: 36616671


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Funding

Funder referenceFunder name
16/RC/3918
847577
European Union Horizon 2020 research and innovation programme
Johnson & Johnson Ireland
Marie Skłodowska-Curie Smart 4.0 Co-Fund
Science Foundation Ireland (SFI)

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