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Electronics
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Application of Digitization, Intelligent Systems and Artificial Intelligence in Industry...
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Application of Digitization, Intelligent Systems and Artificial Intelligence in Industry and Services

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Industrial Electronics".

Deadline for manuscript submissions: 15 October 2025 | Viewed by 634

Special Issue Editors

Dr. Miroslav Rakyta

E-Mail Website
Guest Editor
Department of Industrial Engineering, University of Zilina, Univerzitna 3215/1, 010 26 Žilina, Slovakia
Interests: advanced industrial engineering
Dr. Bubenik Peter

E-Mail Website
Guest Editor
Department of Industrial Engineering, University of Zilina, Univerzitna 3215/1, 010 26 Žilina, Slovakia
Interests: advanced industrial engineering
Dr. Vladimíra Biňasová

E-Mail Website
Guest Editor
Department of Industrial Engineering, University of Zilina, Univerzitna 3215/1, 010 26 Žilina, Slovakia
Interests: advanced industrial engineering
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Advanced Industrial Engineering (AIE) is the main direction of current and future technological developments and is a strategy for European development and research. Artificial intelligence (AI) gives the opportunity to improve digital processes and automation and allows the acceleration of the innovation potential of enterprises.

It creates opportunities in the workplace, where it will enable the streamlining of processes and ensure their sustainability at all levels of the production company.

This topic seeks high-quality studies of research and development and applications in practice, focusing on the following:

  • Research and development of artificial intelligence in all areas of industry and services.
  • Application of digitization as a basis for building intelligent systems.
  • Application of artificial intelligence in the conditions of industrial practice in various production technologies.
  • Use of IoT and Industry 4.0 tools.
  • Artificial intelligence research in automation and robotization.
  • Prediction models of object and process states.
  • Machine learning and neural networks (learning optimization).
  • Cybernetics and artificial intelligence.
  • Modeling and simulation versus artificial intelligence.
  • Artificial intelligence in production, service and auxiliary processes.

Dr. Miroslav Rakyta
Dr. Bubenik Peter
Dr. Vladimíra Biňasová
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. Electronics 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

  • sustainable development
  • Industry 4.0
  • maintenance
  • artificial intelligence
  • advanced industrial engineering
  • digitalization in Industry 4.0

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Published Papers (1 paper)

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Research

35 pages, 12681 KiB  
Article
Robotic Ultrasound Diagnostic System for Non-Destructive Testing in Highly Variable Production
by Zuzana Kovarikova, Frantisek Duchon, Martin Porubsky, Marek Trebula, Lubos Chovanec, Eva Salat and Miroslav Rakyta
Electronics 2025, 14(10), 2063; https://doi.org/10.3390/electronics14102063 - 20 May 2025
Viewed by 270
Abstract
This paper aims to describe a method of non-destructive testing in highly variable production using a robotic ultrasound diagnostic system. Highly variable production involves producing products of different shapes and dimensions, which requires flexible positioning and the adaptation of diagnostic technology. Typically, highly [...] Read more.
This paper aims to describe a method of non-destructive testing in highly variable production using a robotic ultrasound diagnostic system. Highly variable production involves producing products of different shapes and dimensions, which requires flexible positioning and the adaptation of diagnostic technology. Typically, highly variable products are made in small batches. Implementing automation tools, including robotic systems, can meet this requirement, even in diagnostic processes that demonstrate the required quality level. This paper deals with the design, simulation, optimization, and verification of an innovative robotic ultrasound diagnostic system for non-destructive testing in highly variable production environments. The robotic positioning of the diagnosed object and the ultrasound probe achieves the automatic adaptation of the system. Robots can automatically position the ultrasound probe relative to the diagnosed object using laser distance measurements in the water environment of a diagnostic vessel. Computer processing of the data measured by the ultrasound probe enables the evaluation of data and the documentation of quality criterion fulfillment in digital form. Setting the technology parameters, monitoring the technology status, and displaying the quality control results are enabled by a human–machine interface system also described in this paper. Full article
(This article belongs to the Special Issue Application of Digitization, Intelligent Systems and Artificial Intelligence in Industry and Services)
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