Industry 4.0: Integrating Advanced Manufacturing Technologies, Artificial Intelligence, and Contemporary Information Technology

A special issue of Processes (ISSN 2227-9717). This special issue belongs to the section "Advanced Digital and Other Processes".

Deadline for manuscript submissions: closed (30 April 2024) | Viewed by 3158

Special Issue Editors


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Guest Editor
Advanced Manufacturing Institute, King Saud University, Riyadh 11421, Saudi Arabia
Interests: advanced manufacturing technologies; Industry 4.0; additive manufacturing; smart manufacturing

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Guest Editor
Department of Industrial Engineering, College of Engineering, King Saud University, Riyadh 11421, Saudi Arabia
Interests: advanced manufacturing technologies; multi-criteria decision making; artificial intelligence

Special Issue Information

Dear Colleagues,

For any developed nation’s economy, manufacturing is one of the major contributors. Hence, it is important to focus on state-of-the-art manufacturing technologies. In the present era, the advent of Industry 4.0 is redefining how organizations manufacture, enhance, and distribute their goods. The internet of things (IoT), cloud computing, analytics, AI, and machine learning are among the cutting-edge technologies that manufacturers are incorporating into their manufacturing processes. The last decade in manufacturing belongs to automation, but Industry 4.0 is a step ahead of that. Industry 4.0 includes IoT, big data analysis, artificial intelligence, machine learning, real-time data processing, smart manufacturing, machine-to-machine communication, digitization, additive manufacturing, enterprise resource planning, and cyber-physical systems. Industry 4.0 spans across the complete product lifecycle, including supply chain, inventory management, customer feedback, quality, recycling, etc. Smart factories have cutting-edge sensors, embedded software, and robotics that gather data, analyze it, and help with better decision-making. The amalgamation of the latest information technology tools such as IoT, big data with the manufacturing results into better automation, predictive maintenance, self-optimization of processes, and, most importantly, a new level of efficiency and customer responsiveness is now possible.

The articles in this Special Issue on “Industry 4.0: Integrating Advanced Manufacturing Technologies, Artificial Intelligence, and Contemporary Information Technology” will present cutting-edge developments in research that either make use of the concept of Industry 4.0 and one of its main pillars, smart manufacturing, or demonstrate the advancements in these fields with improved frameworks and applications of modern technologies in manufacturing.

Topics include, but are not limited to:

  • Development of the framework for smart factory;
  • Advancements in system integration and cyber-physical systems;
  • Digital twins and its applications in manufacturing;
  • Socio-economic aspects of Industry 4.0;
  • Additive manufacturing in Industry 4.0;
  • Industry 4.0 impacts in supply chain and allied fields.

Dr. Hisham Alkhalefah
Dr. Ateekh Ur Rehman
Guest Editors

Manuscript Submission Information

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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-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Processes is an international peer-reviewed open access monthly 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

  • Industry 4.0
  • Internet of Things
  • additive manufacturing
  • autonomous robots
  • big data analysis
  • advanced simulation
  • virtual/augmented/mixed reality
  • cyber-security
  • smart manufacturing
  • manufacturing systems integration

Published Papers (2 papers)

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Research

18 pages, 2021 KiB  
Article
Evaluating Industry 4.0 Manufacturing Configurations: An Entropy-Based Grey Relational Analysis Approach
by Ateekh Ur Rehman and Abdullah Yahia AlFaify
Processes 2023, 11(11), 3151; https://doi.org/10.3390/pr11113151 - 4 Nov 2023
Viewed by 791
Abstract
Worldwide manufacturing and service sectors are choosing to transform the existing manufacturing sector, particularly reconfigurable manufacturing systems using the technologies of the next generation Industry 4.0. In order to satisfy the demands of the fourth industrial revolution, model evaluation and assessing various candidate [...] Read more.
Worldwide manufacturing and service sectors are choosing to transform the existing manufacturing sector, particularly reconfigurable manufacturing systems using the technologies of the next generation Industry 4.0. In order to satisfy the demands of the fourth industrial revolution, model evaluation and assessing various candidate configurations in reconfigurable manufacturing systems was developed. The proposed model considers evolving consumer demands and evaluates manufacturing configurations using a gray relational approach. For the case at hand, it is evident that considering all possible dynamic market scenarios 1 to 6, the current manufacturing configuration, i.e., alternative 1, has 89% utilization, total 475 h of earliness and 185 h of lateness in the order demand delivery to the market, and a total of 248 throughput hours and around 1143 bottleneck hours. The main challenge is to make a perfect match between the market demands, variations in product geometry, manufacturing processes and several reconfiguration strategies/alternatives. Furthermore, it is evident that alternative 1 should be reconfigured and that alternative 3 is the best choice. Alternative 3 exhibits 86% system utilization, a total of 926 h of earliness and 521 h of lateness in the order demand delivery to the market, and a total of 127 throughput hours and around 853 bottleneck hours. A simulation framework is used to demonstrate the efficacy of each possible reconfigurable production setup. The sensitivity analysis is also carried out by adjusting the weights through principal component analysis and validating the acquired ranking order. Thus, if the decision makers want to provide a preference to all criteria, the order of the choices of configurations is found to be alternative 3, alternative 1, alternative 4, alternative 2 and alternative 5. Full article
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19 pages, 5661 KiB  
Article
Digital Twinning of a Magnetic Forging Holder to Enhance Productivity for Industry 4.0 and Metaverse
by Omid Khalaj, Mohammad (Behdad) Jamshidi, Parsa Hassas, Bohuslav Mašek, Ctibor Štadler and Jiří Svoboda
Processes 2023, 11(6), 1703; https://doi.org/10.3390/pr11061703 - 2 Jun 2023
Cited by 6 | Viewed by 1807
Abstract
The concept of digital twinning is essential for smart manufacturing and cyber-physical systems to be connected to the Metaverse. These digital representations of physical objects can be used for real-time analysis, simulations, and predictive maintenance. A combination of smart manufacturing, Industry 4.0, and [...] Read more.
The concept of digital twinning is essential for smart manufacturing and cyber-physical systems to be connected to the Metaverse. These digital representations of physical objects can be used for real-time analysis, simulations, and predictive maintenance. A combination of smart manufacturing, Industry 4.0, and the Metaverse can lead to sustainable productivity in industries. This paper presents a practical approach to implementing digital twins of a magnetic forging holder that was designed and manufactured in this project. Thus, this paper makes two important contributions: the first contribution is the manufacturing of the holder, and the second significant contribution is the creation of its digital twin. The holder benefits from a special design and implementation, making it a user-friendly and powerful tool in materials research. More specifically, it can be employed for the thermomechanical influencing of the structure and, hence, the final properties of the materials under development. In addition, this mechanism allows us to produce a new type of creep-resistant composite material based on Fe, Al, and Y. The magnetic forging holder consolidates the powder material to form a solid state after mechanical alloying. We produce bars from the powder components using a suitable forging process in which extreme grain coarsening occurs after the final heat treatment. This is one of the conditions for achieving very high resistance to creep at high temperatures. Full article
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