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Applied Sciences
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Advanced Technologies for Industry 4.0 and Industry 5.0
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Advanced Technologies for Industry 4.0 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: 30 December 2024 | Viewed by 3383

Special Issue Editors

Dr. Maja Trstenjak

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Guest Editor
Faculty of Mechanical Engineering and Naval Architecture, University of Zagreb, 10000 Zagreb, Croatia
Interests: Industry 5.0; human factors; ergonomics; production planning; logistics; sustainability; sustainable production
Dr. Hrvoje Cajner

E-Mail Website
Guest Editor
Faculty of Mechanical Engineering and Naval Architecture, University of Zagreb, 10002 Zagreb, Croatia
Interests: manufacturing optimization; applied statistics; operational research
Special Issues, Collections and Topics in MDPI journals
Dr. Tihomir Opetuk

E-Mail Website
Guest Editor
Faculty of Mechanical Engineering and Naval Architecture, University of Zagreb, 10002 Zagreb, Croatia
Interests: logistics; manufacturing and logistics process simulation; process planning; human factors and ergonomics
Dr. Paolo Renna

E-Mail Website
Guest Editor
School of Engineering, University of Basilicata, 85100 Potenza, Italy
Interests: design and optimization of manufacturing systems: flexible manufacturing systems, reconfigurable manufacturing systems, and production lines; simulation to support the control and optimization of manufacturing systems; game theory models to support reconfigurable manufacturing systems and distributed production planning
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Issue of Applied Sciences invites authors to contribute with state-of-the-art research related to ‘Advanced Technologies for Industry 4.0 and Industry 5.0’. This issue examines the framework surrounding these advanced industrial paradigms and presents compelling evidence drawn from practical applications. Particular emphasis is given but not limited to the impacts of these technologies on various facets such as logistics activities, production planning and optimization, maintenance and human factors and ergonomics in manufacturing systems. By offering a comprehensive overview of cutting-edge technologies and exploring the possibilities for optimizing existing ones within the framework of Industry 4.0 and 5.0, this issue aims to equip industry practitioners and researchers with a requisite knowledge base to steer the evolution of global industry towards a human-centric, sustainable, and resilient manufacturing system. Additionally, this issue tends to explain the differences between Industry 4.0 and 5.0, fostering a deeper understanding of their transformative potential. We invite researchers from both industry and academia, through preparing case studies and theoretical and empirical evidence, to submit either theoretical or practical research.

Dr. Maja Trstenjak
Dr. Hrvoje Cajner
Dr. Tihomir Opetuk
Dr. Paolo Renna
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 100 words) can be sent to the Editorial Office for announcement on this website.

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. Applied Sciences 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

  • Industry 4.0
  • Industry 5.0
  • logistics
  • human factors and ergonomics
  • industrial Internet of Things
  • optimization
  • production planning
  • sustainability
  • human-centric manufacturing system

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Published Papers (4 papers)

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Research

25 pages, 2545 KiB  
Article
An ML-Based Solution in the Transformation towards a Sustainable Smart City
by Izabela Rojek, Dariusz Mikołajewski, Janusz Dorożyński, Ewa Dostatni and Aleksandra Mreła
Appl. Sci. 2024, 14(18), 8288; https://doi.org/10.3390/app14188288 - 14 Sep 2024
Viewed by 1089
Abstract
The rapid development of modern information technology (IT), power supply, communication and traffic information systems and so on is resulting in progress in the area of distributed and energy-efficient (if possible, powered by renewable energy sources) smart grid components securely connected to entire [...] Read more.
The rapid development of modern information technology (IT), power supply, communication and traffic information systems and so on is resulting in progress in the area of distributed and energy-efficient (if possible, powered by renewable energy sources) smart grid components securely connected to entire smart city management systems. This enables a wide range of applications such as distributed energy management, system health forecasting and cybersecurity based on huge volumes of data that automate and improve the performance of the smart grid, but also require analysis, inference and prediction using artificial intelligence. Data management strategies, but also the sharing of data by consumers, institutions, organisations and industries, can be supported by edge clouds, thus protecting privacy and improving performance. This article presents and develops the authors’ own concept in this area, which is planned for research in the coming years. The paper aims to develop and initially test a conceptual framework that takes into account the aspects discussed above, emphasising the practical aspects and use cases of the Social Internet of Things (SIoT) and artificial intelligence (AI) in the everyday lives of smart sustainable city (SSC) residents. We present an approach consisting of seven algorithms for the integration of large data sets for machine learning processing to be applied in optimisation in the context of smart cities. Full article
(This article belongs to the Special Issue Advanced Technologies for Industry 4.0 and Industry 5.0)
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18 pages, 11679 KiB  
Article
The Maintenance Factor as a Necessary Parameter for Sustainable Artificial Lighting in Engineering Production—A Software Approach
by Darina Dupláková and Patrik Sloboda
Appl. Sci. 2024, 14(18), 8158; https://doi.org/10.3390/app14188158 - 11 Sep 2024
Viewed by 577
Abstract
The presented article addresses the issue of the maintenance factor, which forms a part of the design variables in artificial lighting within engineering practices from a sustainability perspective. The maintenance factor was monitored using two simulation tools—Dialux, version 5.12.0.5527 and Relux, version 2024.2.8.0. [...] Read more.
The presented article addresses the issue of the maintenance factor, which forms a part of the design variables in artificial lighting within engineering practices from a sustainability perspective. The maintenance factor was monitored using two simulation tools—Dialux, version 5.12.0.5527 and Relux, version 2024.2.8.0. In a production hall, inadequate lighting was identified with a value below 300 lx, prompting a redesign of the lighting system. The overall methodology of the Ergonomic Rationalization Sequence was expanded in the “Design of Lighting System” phase to include the determination of the maintenance factor as a necessary parameter for sustainability, which was subsequently verified in a virtual environment using two options in a practical study. According to the in situ measurements, the virtual environments of the production hall were created for both software, in which four alternatives for the lighting system were developed. The illuminance values met the normative requirements in each alternative; however, the first two (illuminance values 1000 lx–1200 lx) were predicted to have long-term high-energy consumption. In alternatives 3 and 4, the number of luminaires was therefore reduced from 6 pieces to 4, with a total illuminance in the range of 680 lx–780 lx. The determination of the variations in the methods for establishing the maintenance factor identified a deviation of 5%, which, indicating the changes in illuminance values, can be considered as the occurrence of a gross error in lighting design. Full article
(This article belongs to the Special Issue Advanced Technologies for Industry 4.0 and Industry 5.0)
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12 pages, 2641 KiB  
Article
Comparison of Dynamic Decoupling Point and Dynamic Buffer Level for Flexible Flow Shops in a Hybrid MTS–MTO Production Model
by Paolo Renna
Appl. Sci. 2024, 14(17), 7975; https://doi.org/10.3390/app14177975 - 6 Sep 2024
Viewed by 479
Abstract
The competition and the volatility of today’s production context require that enterprises are able to rapidly adapt to changes, reducing total costs in production. The main relationship between producer and consumer can be conducted through Make-To-Order (MTO) or Make-To-Stock (MTS) systems. This study [...] Read more.
The competition and the volatility of today’s production context require that enterprises are able to rapidly adapt to changes, reducing total costs in production. The main relationship between producer and consumer can be conducted through Make-To-Order (MTO) or Make-To-Stock (MTS) systems. This study proposes a hybrid MTS and MTO production system with a dynamic decoupling point. The proposed model concerns the monitoring of earliness and tardiness of customer orders to move the decoupling point towards MTS or MTO. Simulation models are proposed to test the proposed model following periodic or continuous review. The numerical results highlight that the best dynamic approach is the periodic review, which is more effective when the customer demand rate is higher. Full article
(This article belongs to the Special Issue Advanced Technologies for Industry 4.0 and Industry 5.0)
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16 pages, 3542 KiB  
Article
Sociodemographic Data and Work-Related Musculoskeletal Symptoms in the Metal Polishing Industry: A Case Study in Central Portugal
by Joel Alves, Tânia M. Lima and Pedro D. Gaspar
Appl. Sci. 2024, 14(16), 7265; https://doi.org/10.3390/app14167265 - 19 Aug 2024
Viewed by 710
Abstract
The prevalence of work-related musculoskeletal disorders is a red flag in industries and is considered an occupational health issue that affects the operator’s well-being, safety, and health. This study contributes to understanding the impact of Industry 5.0 on the workforce and emphasizes the [...] Read more.
The prevalence of work-related musculoskeletal disorders is a red flag in industries and is considered an occupational health issue that affects the operator’s well-being, safety, and health. This study contributes to understanding the impact of Industry 5.0 on the workforce and emphasizes the importance of promoting a safe and healthy working environment. Thus, it focuses on the assessment of anthropometric characteristics and work-related musculoskeletal symptoms in a real industrial environment, specifically in the metal polishing sector of a metallurgical industry in Portugal. The research collected data on physical attributes, health status, and musculoskeletal symptoms using the Portuguese version of the Nordic Musculoskeletal Questionnaire, and incorporated sociodemographic data, including age, gender, and professional status, to provide a comprehensive understanding of the active workforce. The results were analyzed by gender and age clusters and revealed a prevalence of musculoskeletal symptoms, particularly in the spinal column and upper limbs, with a significant impact on the ability to perform work tasks. The need for preventive measures and ergonomic interventions to minimize the high predominance of musculoskeletal symptoms in Portuguese industries is also highlighted to improve the working conditions and enhance the well-being and health of operators. Full article
(This article belongs to the Special Issue Advanced Technologies for Industry 4.0 and Industry 5.0)
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