Industrial Applications: Industry 4.0 Challenges in the Environmental, Social, and Corporate Governance Context

A special issue of Machines (ISSN 2075-1702). This special issue belongs to the section "Industrial Systems".

Deadline for manuscript submissions: closed (31 July 2024) | Viewed by 2396

Special Issue Editors


E-Mail Website
Guest Editor
Department of Mechatronics and Mechanical Systems Engineering, Universidade de São Paulo, São Paulo 2231, Brazil
Interests: CAD/CAM; computer graphics; industry 4.0; cutting and packing and optimization problems
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
Department of Mechatronics and Mechanical Systems Engineering, Universidade de São Paulo, São Paulo 2231, Brazil
Interests: industry 4.0; cyber-physical systems; Internet of Things; virtual entreprises; APS systems; modeling and simulation; time windows; planning and scheduling heuristics; constraint programming
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
Federal Center for Technological Education of Rio de Janeiro, Rio de Janeiro 20271-110, Brazil
Interests: artificial intelligence; embedded electronics; robotic systems; unmanned aerial vehicles; data processing; fog-cloud computing

Special Issue Information

Dear Colleagues,

The authors from the conference INDUSCON 2023 (https://induscon.org/) held in São Bernardo do Campo, Brazil, are invited to submit an expanded version of their papers to Machines. The papers are related to the industrial applications in several major topics of the conference, including: Social and Sustainable Processes and Practices, Renewable Energy and Sustainable Operations, Circular Economy Tracking and Industry 4.0 Solutions for Governance, Additive Manufacturing and Personalized Products, Industry 4.0, Internet of Things, Life Support Systems, Robotics and Mechatronics, Ultrasound Techniques, Electrical Machines and Drives, Electric Vehicles, Autonomous Vehicles and Drones, Big Data Applied to Modeling, Diagnostics, Deep Learning and Machine Learning Applied to Industry Systems and Processes, and others.

Dr. Marcos de Sales Guerra Tsuzuki
Dr. Marcosiris Amorim de Oliveira Pessoa
Dr. Milena Faria Pinto
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. Machines 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

-Practices of social and sustainable processes

-Electric vehicle and energy storage

-Renewable energy

-Industry applications

-Industry 4.0

-Robotics and mechatronics

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • e-Book format: Special Issues with more than 10 articles can be published as dedicated e-books, ensuring wide and rapid dissemination.

Further information on MDPI's Special Issue polices can be found here.

Published Papers (1 paper)

Order results
Result details
Select all
Export citation of selected articles as:

Research

20 pages, 899 KiB  
Article
A Koopman Reachability Approach for Uncertainty Analysis in Ground Vehicle Systems
by Alok Kumar, Bhagyashree Umathe and Atul Kelkar
Machines 2024, 12(11), 753; https://doi.org/10.3390/machines12110753 - 24 Oct 2024
Viewed by 1834
Abstract
Recent progress in autonomous vehicle technology has led to the development of accurate and efficient tools for ensuring safety, which is crucial for verifying the reliability and security of vehicles. These vehicles operate under diverse conditions, necessitating the analysis of varying initial conditions [...] Read more.
Recent progress in autonomous vehicle technology has led to the development of accurate and efficient tools for ensuring safety, which is crucial for verifying the reliability and security of vehicles. These vehicles operate under diverse conditions, necessitating the analysis of varying initial conditions and parameter values. Ensuring the safe operation of the vehicle under all these varying conditions is essential. Reachability analysis is an important tool to certify the safety and stability of the vehicle dynamics. We propose a reachability analysis approach for evaluating the response of the vehicle dynamics, specifically addressing uncertainties in the initial states and model parameters. Reachable sets illustrate all the possible states of a dynamical system that can be obtained from a given set of uncertain initial conditions. The analysis is crucial for understanding how variations in initial conditions or system parameters can lead to outcomes such as vehicle collisions or deviations from desired paths. By mapping out these reachable states, it is possible to design systems that maintain safety and reliability despite uncertainties. These insights help to ensure the stability and reliability of the vehicles, even in unpredictable conditions, by reducing accidents and optimizing performance. The nonlinearity of the model complicates the computation of reachable sets in vehicle dynamics. This paper proposes a Koopman theory-based approach that utilizes the Koopman principal eigenfunctions and the Koopman spectrum. By leveraging the Koopman principal eigenfunction, our method simplifies the computational process and offers a formal approximation for backward and forward reachable sets. First, our method effectively computes backward and forward reachable sets for a nonlinear quarter-car model with fixed parameter values. Furthermore, we applied our approach to analyze the uncertainty response for cases with uncertain parameters of the vehicle model. When compared to time-domain simulations, our proposed Koopman approach provided accurate results and also reduced the computational time by half in most cases. This demonstrates the efficiency and reliability of our proposed approach in dynamic systems uncertainty analysis using the reachable sets. Full article
Show Figures

Figure 1

Back to TopTop