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A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Mechanical Engineering".

Deadline for manuscript submissions: 31 December 2025 | Viewed by 3712

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Special Issue Editors

Prof. Dr. Jozef Svetlík

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Guest Editor

Department of Manufacturing Machinery and Robotics, Faculty of Mechanical Engineering, Technical University of Košice, 040 01 Košice, Slovakia
Interests: flexible manufacturing; modularity; industrial robotics; industrial design, computer aided design (CAD)

Dr. Rudolf Jánoš

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Guest Editor

Department of Manufacturing Machinery and Robotics, Faculty of Mechanical Engineering, Technical University of Košice, 040 01 Košice, Slovakia
Interests: industrial robotics; service robotics, control systems, design safety of automated device

Dr. Ján Semjon

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Guest Editor

Department of Manufacturing Machinery and Robotics, Faculty of Mechanical Engineering, Technical University of Košice, 040 01 Košice, Slovakia
Interests: industrial robotics; collaborative robotics; robot accuracy; robot drives; sensors in robots

Special Issue Information

Dear Colleagues,

Advanced digital design and intelligent manufacturing are driving a revolutionary shift in modern industrial processes. Technologies such as computer-aided design (CAD), advanced simulations, and automation are now critical for creating more precise, efficient, and innovative products. These tools not only enhance the quality of products but also significantly reduce production costs and development time. Furthermore, intelligent manufacturing incorporates artificial intelligence (AI), machine learning, and the internet of things (IoT), allowing for real-time monitoring, predictive maintenance, and the optimization of production workflows. This integration enables manufacturers to anticipate issues before they arise, ensuring smoother operations and higher product quality. The transformation toward more automated, flexible, and sustainable systems is redefining global competitiveness, allowing companies to adapt to the fast-evolving demands of the market while minimizing waste and improving operational efficiency.

In this Special Issue, original research articles and reviews are welcome. Research areas may include (but are not limited to) the following:

Advanced digital design;
Intelligent manufacturing;
Automation;
Computer aided design (CAD);
Simulations;
Artificial intelligence (AI);
Machine learning;
Manufacturing process optimization;
Intelligent manufacturing;
Industry 4.0;
Robotics;
Digital twin;
CNC machines;
3D printing;
Sustainable manufacturing;
Industrial competitiveness.

Prof. Dr. Jozef Svetlík
Dr. Rudolf Jánoš
Dr. Ján Semjon
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. Applied Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

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Keywords

advanced digital design
intelligent manufacturing
automation
robotics
Industry 4.0
3D printing
sustainable manufacturing
digital twin
CNC machines
computer aided design (CAD)

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Published Papers (6 papers)

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Research

33 pages, 4714 KiB

Open AccessArticle

Development of a Small CNC Machining Center for Physical Implementation and a Digital Twin

by Claudiu-Damian Petru, Fineas Morariu, Radu-Eugen Breaz, Mihai Crenganiș, Sever-Gabriel Racz, Claudia-Emilia Gîrjob, Alexandru Bârsan and Cristina-Maria Biriș

Appl. Sci. 2025, 15(10), 5549; https://doi.org/10.3390/app15105549 - 15 May 2025

Viewed by 189

Abstract

This work aimed to develop both a real implementation and a digital twin for a small CNC machining center. The X-, Y-, and Z-axes feed systems were realized as closed-loop motion loops with DC servo motors and encoders. Motion control was provided by Arduino boards and Pololu motor drivers. A simulation study of the step response parameters was carried out, and then the positioning regime was studied, followed by the two-axis simultaneous motion regime (circular interpolation). This study, based on a hybrid simulation diagram realized in Simulink–Simscape, allowed a preliminary tuning of the PID (proportional integral derivative) controllers. Next, the CAE (computer-aided engineering) simulation diagram was complemented with the CAM (computer-aided manufacturing) simulation interface, the two together forming an integrated digital twin system. To validate the contouring performance of the proposed CNC system, a circular groove with an outer diameter of 31 mm and an inner diameter of 29 mm was machined using a 1 mm cylindrical end mill. The trajectory followed the simulated 30 mm circular path. Two sets of controller parameters were applied. Dimensional accuracy was verified using a GOM Atos Core 200 optical scanner and evaluated in GOM Inspect Suite 2020. The results demonstrated good agreement between simulation and physical execution, validating the PID tuning and system accuracy. Full article

(This article belongs to the Special Issue Advanced Digital Design and Intelligent Manufacturing)

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18 pages, 3490 KiB

Open AccessArticle

Controlling Product Properties in Forming Processes Using Reinforcement Learning—An Application to V-Die Bending

by Ciarán-Victor Veitenheimer, Dirk Alexander Molitor, Viktor Arne and Peter Groche

Appl. Sci. 2025, 15(10), 5483; https://doi.org/10.3390/app15105483 - 14 May 2025

Viewed by 195

Abstract

Uncertainty is unavoidable in forming processes due to fluctuating properties in the semi-finished product, the tool system and the environment. For this reason, numerous scientists have addressed this issue by developing control approaches like self-optimizing machine tools or the control of product properties. Machine learning algorithms, in particular reinforcement learning (RL) methods, show promising results for controlling production processes in this way. In this paper, the application of RL is demonstrated on an industrially commonly used process, V-die bending. For this purpose, first a flexible tool system is developed that allows the bending angle to be adjusted continuously between 80 and 110°. The developed tool is initially simulated through an FEM model in order to create a sufficient database for the training of an RL agent for springback compensation. The pre-trained agent is then used to control the springback in the real process. To close the resulting sim-to-real gap, it is then retrained on the experimentally generated data. It is shown that the springback can be significantly reduced compared to the uncontrolled case in both the simulative and the experimental process. Full article

(This article belongs to the Special Issue Advanced Digital Design and Intelligent Manufacturing)

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22 pages, 4718 KiB

Open AccessArticle

Methodology for Verification of Geometrically Complex Components Through Reverse Engineering

by Peter Gabštur, Marek Kočiško, Jakub Kaščak and Martin Pollák

Appl. Sci. 2025, 15(7), 3963; https://doi.org/10.3390/app15073963 - 3 Apr 2025

Viewed by 383

Abstract

Verification of geometrically complex components is a crucial step in ensuring the quality and functionality of industrial products. This article presents a comprehensive methodological approach to their verification using reverse engineering techniques. The study highlights the limitations of traditional measurement methods for complex geometries and proposes a framework that integrates advanced 3D scanning and digital modeling. The methodology involves obtaining accurate geometric data, with deviations during repeated measurements being well within the tolerance range. With a tolerance of ±1 mm, the maximum deviation was −0.66 mm, while the maximum deviation with the highest tolerance of 4.5 mm was 1.19 mm. These data were compared with predefined 3D models to analyze deviations and identify process errors. By applying this detailed methodology, more precise fixtures were created, resulting in measurements with deviations well below the required tolerances, compared to measurements without this methodology. A practical example of the design and verification of a welding fixture for cabin manufacturing illustrates the effectiveness of reverse engineering in detecting inconsistencies and optimizing manufacturing processes. The findings emphasize the importance of geometric accuracy in quality control and demonstrate how reverse engineering can streamline verification processes and enhance product reliability. This approach is particularly valuable for the manufacturing industry, which requires high precision in the production of geometrically complex components. Full article

(This article belongs to the Special Issue Advanced Digital Design and Intelligent Manufacturing)

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24 pages, 11143 KiB

Open AccessArticle

Comprehensive Analysis of Deposition Parameters and Energy-Dispersive X-Ray Spectroscopy Characterization in Cataphoretic Coating Processes

by Patrik Fejko, Damián Peti, Jozef Dobránsky, Miroslav Gombár and Peter Michalík

Appl. Sci. 2025, 15(7), 3760; https://doi.org/10.3390/app15073760 - 29 Mar 2025

Viewed by 339

Abstract

This research examines the inter-relationship between the deposition time, degreasing temperature, and applied voltage in the cataphoretic painting process, focusing on their cumulative effects on the thickness of the formed layers. A series of experiments was conducted, systematically varying deposition time effects through voltage levels (200 V to 300 V) and degreasing temperatures (40 °C to 80 °C). The results demonstrate that the maximum layer thickness is achieved at longer cataphoretic times, with significant thickness increments observed at optimal voltage levels. Conversely, the study reveals that lower degreasing temperatures lead to increased layer thickness, while elevated temperatures tend to diminish it. Notably, the thickness variations are consistent across different voltage applications, with a discernible threshold at which the layer thickness stabilizes. Additionally, energy-dispersive X-ray spectroscopy (EDX) was utilized to characterize the elemental composition of the cataphoretic layer, providing deeper insights into the coating structure and its relationship to process parameters. This work provides valuable insights into the optimization of cataphoretic processes, offering a framework for enhancing the quality and uniformity of coatings in industrial applications. The findings underscore the importance of the precise control over process parameters to achieve the desired material characteristics, thereby advancing the field of surface engineering and coating technologies. Full article

(This article belongs to the Special Issue Advanced Digital Design and Intelligent Manufacturing)

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22 pages, 3439 KiB

Open AccessArticle

Technical Diagnostics of Industrial Robots Using Vibration Signals: Case Study on Detecting Base Unfastening

by Daria Fedorova, Vladimír Tlach, Ivan Kuric, Tomáš Dodok, Ivan Zajačko and Karol Tucki

Appl. Sci. 2025, 15(1), 270; https://doi.org/10.3390/app15010270 - 30 Dec 2024

Cited by 2 | Viewed by 1085

Abstract

In the domain of modern manufacturing digitalization, artificial intelligence tools are increasingly employed for condition monitoring and technical diagnostics. However, the majority of existing methodologies primarily concentrate on the technical diagnosis of rotating machines, with a noticeable lack of research addressing these issues in sequential machines. In this paper, we deal with the selection of suitable vibration signal characteristics for the detection of an industrial robot’s release from its base during a handling operation. Statistical methods, including one-way ANOVA and t-tests, were used to identify the most significant features, which allowed us to isolate vibration metrics with significant predictive potential. These selected features were then used as inputs to various machine learning models to evaluate the hypothesis that these parameters can reliably indicate fastening releasing events. The results show that the optimized parameters significantly improve the detection accuracy, thus providing a reliable basis for future applications in predictive maintenance and monitoring. The findings represent an advance in robotic condition monitoring, providing a structured approach to feature selection that improves the reliability of disconnection detection in automated systems with potential applicability in various industrial environments. Full article

(This article belongs to the Special Issue Advanced Digital Design and Intelligent Manufacturing)

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20 pages, 5869 KiB

Open AccessArticle

Calculation of Trusses System in MATLAB—Multibody

by Štefan Ondočko, Jozef Svetlík, Rudolf Jánoš, Ján Semjon and Miroslav Dovica

Appl. Sci. 2024, 14(20), 9547; https://doi.org/10.3390/app14209547 - 19 Oct 2024

Viewed by 879

Abstract

This article discusses the software tool (Simscape—Multibody program of MATLAB) primarily intended for dynamic and kinematic processes with practical applications in static calculations. Currently, there are few published scientific works utilizing this tool for tasks like basic static calculations of truss systems. We were interested in comparing the calculation using the tools we use in our work and research activities for theoretical calculation; the potential reliance on simulations in the future could help to avoid the necessity of complex theoretical calculations, which can be time-consuming and prone to errors. Despite the fact that the structure may appear simple, in practice, there may not always be time for a verification calculation in the theoretical field (proper model creation, inclusion of all conditions, etc.). The beam system is intentionally both externally and internally statically indeterminate. For this reason, it is logically necessary to also consider deformation conditions. The achieved results were interesting in terms of accuracy compared to SOLIDWORKS, which was used for computation verification. Through very simple optimization, we were able to further increase the calculation accuracy without complicating other parameters. Full article

(This article belongs to the Special Issue Advanced Digital Design and Intelligent Manufacturing)

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