applsci-logo

Journal Browser

Journal Browser

Advanced Technologies, Methods, and Systems for Sustainable Global Networks

A topical collection in Applied Sciences (ISSN 2076-3417). This collection belongs to the section "Applied Industrial Technologies".

Viewed by 3063

Editor


E-Mail Website
Collection Editor
Department of Construction and Fabrication Engineering, National Distance Education University (UNED), 28040 Madrid, Spain
Interests: ergonomics; workplace design; industrial engineering; manufacturing processes; maintenance management; strategic management; manufacturing technologies; Industry 4.0, corporate social responsibility; operations; industrial heritage
Special Issues, Collections and Topics in MDPI journals

Topical Collection Information

Dear Colleagues,

Over the history of evolution, the satisfaction of needs has had varied responses, although there has always been a pattern: the possibilities, technologies, and capabilities to meet them have increased. However, the world of the 21st century is one in which the basic needs of millions of human beings are still not satisfied. Therefore, the current global market situation pursues high adaptability as globalization makes disruptions a major risk for operations in the existing global networks. Disruptions such as disasters, epidemic crises, product changes, and socio-economic situations lead to significant global consequences for organizations, society, and individuals if they are not managed properly with suitable methods and supporting technologies. Therefore, there is an urgent need, with regard to both research and the real world, to develop technological solutions to improve the management of industrial and service companies to increase their adaptability to face any potential future event.  In this context, Industry 4.0, the initiative created in 2011, with its developments in cloud, the Internet of Things (IoT), big data analytics, and digital twins, as well as other related technologies, can improve organizational performance and sustainability. In these circumstances, and considering that it was the first time an industrial revolution was predicted a priori, all kinds of organizations have the opportunity to decide how they will transform their business models and how they will shape their strategies, organizational models, future technologies, and systems, as well as internal processes. In this context, the human factor integration in Industry 4.0 environments arises as a concept that must be considered when designing, developing, implementing, and managing new technologies towards new business and organizational models. Moreover, being capable of performing and optimizing operations in a continuous way at the lowest risk possible to maximize the overall company's value and optimize the impact on its related environment plays a fundamental role within current global supply chain networks. Furthermore, practitioners often fail to holistically consider all the related factors in the different planning horizons (long, medium, and short terms) to a certain decision leading to partial, suboptimal, or even negative decisions. Thus, the aim of this Topic Collection is to develop integrated approaches to increase the organizational capabilities and to apply new industrial organization models to deal with current and future challenges. As a result, this Topic Collection aims to create new opportunities to generate and develop concepts, methods, technologies, and systems from the design to the end of product and service life cycles to increase organizational competitiveness and to secure viability in the long term to contribute to the achievement of both organization's and society's challenges. In conclusion, this Topic Collection seeks to encourage researchers and practitioners to submit their abstracts and papers that relate to the broad, multidisciplinary topic of Industrial Organization (e.g., road mapping and strategy, smart manufacturing, industrial sustainability, sustainable product and services, circular economy, supply chain optimization, new technologies, among others) pertinent to the continuous improvement of industrial and service organizations.

Prof. Dr. Manuel García-García
Collection Editor

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 collection 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

  • systems optimization
  • road mapping and strategy
  • circular economy
  • smart manufacturing
  • industrial sustainability
  • sustainable product and services
  • supply chain optimization
  • occupational health and safety
  • information systems
  • new technologies
  • industrial revolutions
  • project management
Topics:
  • systems optimization
  • sustainable production
  • road mapping and strategy
  • risk management
  • decision systems
  • decision support tools
  • supply chain optimization
  • life cycle
  • resource efficiency
  • advanced manufacturing processes
  • process optimization
  • sustainable processes
  • manufacturing and assembly systems
  • production logistics
  • sustainable energy services
  • human factors engineering
  • design for manufacturing and assembly
  • occupational health and safety
  • maintenance management
  • predictive maintenance
  • quality management and control
  • industrial heritage
  • advanced technologies
  • innovation management
  • information systems
  • digitalization
  • IoT
  • cyber
  • physical systems
  • modeling and simulation
  • data analytics
  • artificial intelligence
  • digital twin

Published Papers (2 papers)

2024

20 pages, 2936 KiB  
Article
Multilevel Hierarchical Bayesian Modeling of Cross-National Factors in Vehicle Sales
by Monika Sukiennik and Jerzy Baranowski
Appl. Sci. 2024, 14(14), 6325; https://doi.org/10.3390/app14146325 - 20 Jul 2024
Viewed by 685
Abstract
SUVs (sport utility vehicles), as a car segment, have become a foundation within the automotive industry due to their versatility, which is used by a wide range of customers. Recognising the complex interplay between geographical and economic conditions across countries, we delve into [...] Read more.
SUVs (sport utility vehicles), as a car segment, have become a foundation within the automotive industry due to their versatility, which is used by a wide range of customers. Recognising the complex interplay between geographical and economic conditions across countries, we delve into cross-national factors that significantly influence SUV sales. This article presents an analysis of the global sales of SUVs (sport utility vehicles) using multilevel hierarchical Bayesian modelling. We identify key predictors of SUV sales, including the effects of fuel prices, income levels and geographical aspects. We prepared four statistical models that differ in their probability distribution or hierarchical internal structure. The last presented model, with Student’s t-distribution and separate distribution for unique alpha parameter values, turned out to be the best one. Our analysis contributes to a deeper understanding of the automotive market dynamics, and it can also assist manufacturers and policymakers in designing effective sales strategies. Full article
Show Figures

Figure 1

15 pages, 351 KiB  
Article
Novel Ordinary Differential Equation for State-of-Charge Simulation of Rechargeable Lithium-Ion Battery
by Peguy Kameni Nteutse, Ineza Remy Mugenga, Abebe Geletu and Pu Li
Appl. Sci. 2024, 14(12), 5284; https://doi.org/10.3390/app14125284 - 18 Jun 2024
Viewed by 1153
Abstract
Lithium-ion battery energy storage systems are rapidly gaining widespread adoption in power systems across the globe. This trend is primarily driven by their recognition as a key enabler for reducing carbon emissions, advancing digitalization, and making electricity grids more accessible to a broader [...] Read more.
Lithium-ion battery energy storage systems are rapidly gaining widespread adoption in power systems across the globe. This trend is primarily driven by their recognition as a key enabler for reducing carbon emissions, advancing digitalization, and making electricity grids more accessible to a broader population. In the present study, we investigated the dynamic behavior of lithium-ion batteries during the charging and discharging processes, with a focus on the impact of terminal voltages and rate parameters on the state of charge (SOC). Through modeling and simulations, the results show that higher terminal charging voltages lead to a faster SOC increase, making them advantageous for applications requiring rapid charging. However, large values of voltage-sensitive coefficients and energy transfer coefficients were found to have drawbacks, including increased battery degradation, overheating, and wasted energy. Moreover, practical considerations highlighted the trade-off between fast charging and time efficiency, with charging times ranging from 8 to 16 min for different rates and SOC levels. On the discharging side, we found that varying the terminal discharging voltage allowed for controlled discharging rates and adjustments to SOC levels. Lower sensitivity coefficients resulted in more stable voltage during discharging, which is beneficial for applications requiring a steady power supply. However, high discharging rates and sensitivity coefficients led to over-discharging, reducing battery life and causing damage. These new findings could provide valuable insights for optimizing the performance of lithium-ion batteries in various applications. Full article
Show Figures

Figure 1

Back to TopTop