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5G and Beyond Technologies in Smart Manufacturing, 2nd Edition
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5G and Beyond Technologies in Smart Manufacturing, 2nd Edition

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Industrial Electronics".

Deadline for manuscript submissions: closed (31 October 2025) | Viewed by 7059

Editors

Prof. Dr. Robert Schmitt

E-Mail Website
Guest Editor
Laboratory for Machine Tools and Production Engineering (WZL), RWTH Aachen University, 52074 Aachen, Germany
Interests: production metrology; networked, adaptive production; 5G applications in manufacturing; metrology-assisted robotics; assembly; production intelligence; quality management
Special Issues, Collections and Topics in MDPI journals
Dr. Joachim Sachs

E-Mail Website
Guest Editor
Ericsson Research, Stockholm, Sweden
Interests: mobile networks; cellular IoT; 5G for manufacturing
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Communication systems are the backbone of future factories. In this context, digitization and networking are taking on an increasingly important role for manufacturing companies to make their production processes more flexible and, at the same time, more robust, ultimately with the vision of resilient factories.

Cellular technology has a high potential to become an important factor in future manufacturing because of the ability to wirelessly connect multiple assets in factories and simultaneously guarantee them a determined quality of service (QoS). Ultra-reliable low-latency communication (URLLC) is of particular importance in this context.

To further develop the 5G ecosystem, additional R&D efforts are required to make industrial 5G devices marketable and validate their performance in the corresponding use cases. Furthermore, the integration of 5G networks into an industrial LAN and interaction with edge–cloud systems is of high importance. The coexistence of public and non-public cellular networks also needs to be investigated, as well as different 5G services, e.g., positioning, time synchronization and network exposure interface.

Moreover, beyond 5G and 6G system concepts need to be analyzed for manufacturing applications. Human-inclusive production, sustainability aspects, energy-efficient designs, AI/ML-native cellular architectures, dependable communication and network digital twins are some of the topics seen relevant for enabling smart manufacturing.  

Therefore, this Special Issue covers essential aspects of current research topics on the use of 5G in production, while also addressing potential features beyond 5G and their relevance for manufacturing

Prof. Dr. Robert Schmitt
Dr. Joachim Sachs
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-anonymized peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Electronics is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • 5G use cases for smart production
  • industrial 5G devices
  • performance analysis
  • network coexistence analysis
  • 5G industrial LAN and edge–cloud integration
  • beyond 5G proof-of-concept prototypes for smart production
  • deterministic communication
  • early 6G prototype systems

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Related Special Issue

Published Papers (3 papers)

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Research

22 pages, 2605 KB  
Article
Congestion-Aware Scheduling for Large Fleets of AGVs Using Discrete Event Simulation
by Jeonghyeon Kim and Junwoo Kim
Electronics 2026, 15(1), 139; https://doi.org/10.3390/electronics15010139 - 28 Dec 2025
Cited by 1 | Viewed by 986
Abstract
Conventional large fleets of Automated Guided Vehicles (AGVs) suffer from issues related to the network environment, including handoff latency and interference. Recently, 5G technology has emerged as a practical tool to resolve these network issues. Consequently, there is a growing trend toward deploying [...] Read more.
Conventional large fleets of Automated Guided Vehicles (AGVs) suffer from issues related to the network environment, including handoff latency and interference. Recently, 5G technology has emerged as a practical tool to resolve these network issues. Consequently, there is a growing trend toward deploying large AGV fleets based on 5G technology. Typically, AGVs are controlled by an AGV control system (ACS), which is responsible for tasks such as path planning and AGV scheduling. AGV scheduling is the process of assigning the right task to the right vehicle at the right time. This process has a significant impact on the performance of an AGV fleet, particularly for large-scale fleets. However, existing AGV scheduling approaches hardly consider traffic congestion, which often occurs in large fleets. To fill this gap, this study proposes a simulation-based congestion-aware AGV scheduling approach for large AGV fleets. The proposed approach is characterized by three components: congestion functions, congestion penalties, and congestion-aware scheduling rules. Congestion functions are employed to compute the degree of congestion at a specific point or area within the shop floor. Congestion penalties represent the loss incurred when a vehicle traverses a specific segment within the AGV path network. Congestion-aware scheduling rules provide the decision-making logic for task and vehicle dispatching. We outline the components and apply them to a discrete event simulation (DES) model containing an AGV fleet. The experimental results demonstrate that the proposed approach reduces the inefficiencies of the AGV system caused by traffic congestion. Full article
(This article belongs to the Special Issue 5G and Beyond Technologies in Smart Manufacturing, 2nd Edition)
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35 pages, 2441 KB  
Article
Power Normalized and Fractional Power Normalized Least Mean Square Adaptive Beamforming Algorithm
by Yuyang Liu and Hua Wang
Electronics 2026, 15(1), 49; https://doi.org/10.3390/electronics15010049 - 23 Dec 2025
Viewed by 592
Abstract
With the rapid deployment of high-speed maglev transportation systems worldwide, the operational velocity, electromagnetic complexity, and channel dynamics have far exceeded those of conventional rail systems, imposing more stringent requirements on real-time capability, reliability, and interference robustness in wireless communication. In maglev environments [...] Read more.
With the rapid deployment of high-speed maglev transportation systems worldwide, the operational velocity, electromagnetic complexity, and channel dynamics have far exceeded those of conventional rail systems, imposing more stringent requirements on real-time capability, reliability, and interference robustness in wireless communication. In maglev environments exceeding 600 km/h, the channel becomes predominantly line-of-sight with sparse scatterers, exhibiting strong Doppler shifts, rapidly varying spatial characteristics, and severe interference, all of which significantly degrade the stability and convergence performance of traditional beamforming algorithms. Adaptive smart antenna technology has therefore become essential in high-mobility communication and sensing systems, as it enables real-time spatial filtering, interference suppression, and beam tracking through continuous weight updates. To address the challenges of slow convergence and high steady-state error in rapidly varying maglev channels, this work proposes a new Fractional Proportionate Normalized Least Mean Square (FPNLMS) adaptive beamforming algorithm. The contributions of this study are twofold. (1) A novel FPNLMS algorithm is developed by embedding a fractional-order gradient correction into the power-normalized and proportionate gain framework of PNLMS, forming a unified LMS-type update mechanism that enhances error tracking flexibility while maintaining O(L) computational complexity. This integrated design enables the proposed method to achieve faster convergence, improved robustness, and reduced steady-state error in highly dynamic channel conditions. (2) A unified convergence analysis framework is established for the proposed algorithm. Mean convergence conditions and practical step-size bounds are derived, explicitly incorporating the fractional-order term and generalizing classical LMS/PNLMS convergence theory, thereby providing theoretical guarantees for stable deployment in high-speed maglev beamforming. Simulation results verify that the proposed FPNLMS algorithm achieves significantly faster convergence, lower mean square error, and superior interference suppression compared with LMS, NLMS, FLMS, and PNLMS, demonstrating its strong applicability to beamforming in highly dynamic next-generation maglev communication systems. Full article
(This article belongs to the Special Issue 5G and Beyond Technologies in Smart Manufacturing, 2nd Edition)
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19 pages, 5059 KB  
Article
5G-TSN Integrated Prototype for Reliable Industrial Communication Using Frame Replication and Elimination for Reliability
by Pierre E. Kehl, Junaid Ansari, Mikael Lovrin, Praveen Mohanram, Chi-Chuan (Eric) Liu, Jun-Lin (Larry) Yeh and Robert H. Schmitt
Electronics 2025, 14(4), 758; https://doi.org/10.3390/electronics14040758 - 15 Feb 2025
Cited by 13 | Viewed by 4262
Abstract
The stringent requirements of industrial communication, especially high reliability and real-time response, are regarded as the main bottlenecks for the widespread adoption of wireless technologies in industrial applications. The integration of 5G and Time-Sensitive Networking (TSN) protocols offers convergence of both wireless and [...] Read more.
The stringent requirements of industrial communication, especially high reliability and real-time response, are regarded as the main bottlenecks for the widespread adoption of wireless technologies in industrial applications. The integration of 5G and Time-Sensitive Networking (TSN) protocols offers convergence of both wireless and various wired communication technologies for industrial applications. In this article, we describe our 5G and TSN integrated prototype, which achieves high reliability based on the IEEE 802.1CB Frame Replication and Elimination for Reliability (FRER) scheme. Different 5G systems have been used in various combinations to empirically study the benefits of FRER for 5G communication in real industrial environments. We evaluate the performance of our prototype and validate it for an industrial use case on Smart Sensors for Milling Processes, requiring a latency below 10 ms for 99.99% of the packets sent, which has been achieved in the measurements using FRER. This use case and the high requirements towards latency and reliability demonstrate the benefits of 5G integration with FRER for industrial production. Full article
(This article belongs to the Special Issue 5G and Beyond Technologies in Smart Manufacturing, 2nd Edition)
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