Edge Computing, Big Data and Digital Twin towards Smart Manufacturing and Industry 5.0

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Mechanical Engineering".

Deadline for manuscript submissions: closed (30 June 2022) | Viewed by 2859

Special Issue Editors


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Guest Editor
Department of Electrical and Computer Engineering, Hellenic Mediterranean University, 714 10 Heraklion, Greece
Interests: edge networking; public safety; cloud computing; NFV; edge computing; cybersecurity; DVB-T; bioengineering; ICT healthcare; networks; distibuted; P2P; telecom

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Guest Editor
National Centre for Scientific Research ”DEMOKRITOS” (NCSRD), Institute of Informatics and Telecommunications, 153 10 Athens, Greece
Interests: NFV; SDN; 6G networks; network slicing; swarm intelligence
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Special Issue Information

Dear Colleagues,

Modern manufacturing industry practices have invested heavily in data transport from the factory floor to the cloud, where bulk process and monitoring data are analyzed in depth, leveraging the computing superiority and resource flexibility of a remote cloud infrastructure. Additionally, cloud processing renders difficult a trustworthy exchange of information between different industrial data providers in a certified manner. Moreover, considering the heterogeneity of data sources and the requirements of the offered services found in Industry 4.0/5.0 scenarios, different processing techniques must be considered. Data sharing already plays a crucial role in the manufacturing industry; either through data sharing for defect detection or through entire production chain provision and analysis, a significant amount of data are generated each second on the factory floor. The existing horizontal approach cannot encapsulate the interrelations between the different domain processes, actors and equipment in the OT environment, and each domain analysis remains isolated and monolithic. The goal of this Special Issue is to invite high-quality, state-of-the-art research papers that deal with challenging issues in the “Edge Computing, Big Data and Digital Twin towards Smart Manufacturing and Industry 5.0” applications and domain.

Papers should focus on:

  • 5G NPN integration in the plant floor;
  • Data sharing across different shop floors;
  • GAIA-X and IDSA integration;
  • Cybersecurity aspects in the I4.0 or I5.0 domain;
  • OPC-UA;
  • Horizontal paradigm in I4.0 or I5.0;
  • Digital twin paradigm;
  • Orbital edge in I4.0 or I5.0;
  • Edge processing;
  • Edge computing;
  • Edge security.

Dr. Evangelos Markakis
Dr. Michael Alexandros Kourtis
Guest Editors

Manuscript Submission Information

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Published Papers (1 paper)

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16 pages, 2426 KiB  
Concept Paper
5G NPN Performance Evaluation for I4.0 Environments
by Michail-Alexandros Kourtis, Andreas Oikonomakis, Dimitris Santorinaios, Themis Anagnostopoulos, Giorgios Xilouris, Anastasios Kourtis, Ioannis Chochliouros and Charilaos Zarakovitis
Appl. Sci. 2022, 12(15), 7891; https://doi.org/10.3390/app12157891 - 06 Aug 2022
Cited by 1 | Viewed by 2340
Abstract
This paper aims to develop an open Asset Administration Shell (AAS) solution for 5G Non-Public Network (NPN) management, focusing on manufacturing digitization and complete Information and Operational Technology (IT/OT) convergence. The proposed 5G NPN framework is evaluated in a factory-like simulation scenario considering [...] Read more.
This paper aims to develop an open Asset Administration Shell (AAS) solution for 5G Non-Public Network (NPN) management, focusing on manufacturing digitization and complete Information and Operational Technology (IT/OT) convergence. The proposed 5G NPN framework is evaluated in a factory-like simulation scenario considering network slicing for I4.0, and demonstrates the outlook of 5G communication in the industrial domain, achieving an upload data rate of up to 86 Mbps, and a Round-Trip Time (RTT) for end-to-end communication as low as 11 ms. The proposed framework integrates OPC UA as an enabler and middleware across different protocols, equipment, and the manufacturing shop floor, with the target of aggregating different industrial data and creating insights on production optimization in a unified manner. The framework combines 5G NPNs with I4.0 environments, in the form of a complete FNMS and its corresponding AAS. In parallel, a set of I4.0 enablers are investigated within the framework of the project, covering a Time-Sensitive Network (TSN) on the shop floor. The main objective of this paper is to propose a method for the unified integration of various enablers in the I4.0 domain and their combination with 5G technology, and to evaluate the feasibility of hosting industrial applications and services over 5G channels through the implementation of different slicing schemas. The paper presents detailed experimental data regarding 5G downlink/uplink data rates and RTT delays. Full article
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