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A special issue of Materials (ISSN 1996-1944). This special issue belongs to the section "Manufacturing Processes and Systems".

Deadline for manuscript submissions: 20 March 2025 | Viewed by 8074

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Special Issue Editors

Prof. Dr. Vitalii Ivanov

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Department of Manufacturing Engineering, Machines and Tools, Sumy State University, 40007 Sumy, Ukraine
Interests: manufacturing technology; design engineering; manufacturing systems; product design and development
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Prof. Dr. Ivan Pavlenko

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Department of Computational Mechanics named after V. Martsynkovskyy, Sumy State University, 40007 Sumy, Ukraine
Interests: dynamics and strength of machines; numerical simulation; parameter identification; artificial neural networks; design engineering
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Prof. Dr. Szymon Wojciechowski

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Faculty of Mechanical Engineering, Poznan University of Technology, 60-965 Poznan, Poland
Interests: cutting process; surface roughness; micromachining; tool wear; carbide tools; mechanical properties; advanced materials; numerical simulation
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Dr. Jinyang Xu

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School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
Interests: fibrous composites; metallic alloys; hybrid composite stacks; high-performance materials; functional surfaces; multilayer coatings; coating evaluation; coated tools; mechanical machining; materials processing; numerical modeling surface texturing
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Special Issue Information

Dear Colleagues,

The application of novel approaches in the design, simulation, and manufacturing of engineering products ensures the effectiveness of manufacturing systems. Modeling the materials’ structure leads to the production of a predetermined set of their properties and ensures the designed parts’ reliability. This modeling is essential for cutting tools, fixtures and tooling, friction pairs, highly loaded parts of machines and equipment, etc. Implementation of the abovementioned issues must ensure the functionality and assigned operating parameters of the designed parts and units in terms of wear resistance, stress–strain modes and dynamic behavior, loading capacity, etc. Advanced material processing approaches can be applied (plasma deposition, electro spark, chemical-thermocycling treatment, strengthening, etc.). Additionally, novel approaches can be implemented in designing advanced materials (polymers, composites, ceramics, nanomaterials, etc.). At the design stage of materials, it is essential to predict the functional, rheological, and tribological properties using numerical simulation and experimental studies. The developed innovative approaches and methods must significantly improve the properties of the surfaces of the parts for cutting tools, machine parts, friction pairs, etc., characterized by improved wear resistance and enhanced surface quality. Overall, the mentioned approaches could improve the machinability, reliability, and productivity of the designed manufacturing systems.

Prof. Dr. Vitalii Ivanov
Prof. Dr. Ivan Pavlenko
Prof. Dr. Szymon Wojciechowski
Dr. Jinyang Xu
Guest Editors

Manuscript Submission Information

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Keywords

advanced materials
chemical-thermal treatment
composites
design engineering
industrial growth
manufacturing technology
multilayer coatings
numerical simulation
polymers
process innovation
wear resistance

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Published Papers (6 papers)

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Research

18 pages, 3354 KiB

Open AccessArticle

Tool Wear Prediction in Machining of Aluminum Matrix Composites with the Use of Machine Learning Models

by Adam Hamrol, Maciej Tabaszewski, Agnieszka Kujawińska and Jakub Czyżycki

Materials 2024, 17(23), 5783; https://doi.org/10.3390/ma17235783 - 25 Nov 2024

Viewed by 447

Abstract

This paper discusses the diagnostic models of tool wear during face milling of Aluminum Matrix Composite (AMC), classified as a difficult-to-cut material. Prediction and classification models were considered. The models were based on one-dimensional simple regression or on multidimensional regression trees, random forest, nearest neighbor and multilayer perceptron neural networks. Measures of diagnostic signals obtained from measurements of cutting forces and vibration accelerations of the workpiece were used. The study demonstrated that multidimensional models outperformed one-dimensional models in terms of prediction accuracy and classification performance. Specifically, multidimensional predictive models exhibited lower maximum and average absolute prediction errors (0.036 mm vs. 0.050 mm and 0.026 mm vs. 0.045 mm, respectively), and classification models recorded fewer Type I and Type II errors. Despite the increased complexity, the higher predictive accuracy (up to 0.97) achieved with multidimensional models was shown to be suitable for industrial applications. However, simpler one-dimensional models offered the ad-vantage of greater reliability in signal acquisition and processing. It was also highlighted that the advantage of simple models from a practical point of view is the reduced complexity and consequent greater reliability of the system for acquiring and processing diagnostic signals. Full article

(This article belongs to the Special Issue Novel Approaches in the Design, Simulation, and Manufacturing for Processes and Systems)

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15 pages, 5299 KiB

Open AccessArticle

Corrosion Resistance of Coatings Based on Chromium and Aluminum of Titanium Alloy Ti-6Al-4V

by Tetiana Loskutova, Michael Scheffler, Ivan Pavlenko, Kamil Zidek, Inna Pohrebova, Nadiia Kharchenko, Iryna Smokovych, Oleksandr Dudka, Volodymyr Palyukh, Vitalii Ivanov and Yaroslav Kononenko

Materials 2024, 17(15), 3880; https://doi.org/10.3390/ma17153880 - 5 Aug 2024

Viewed by 1041

Abstract

Improvement of wear, corrosion, and heat-resistant properties of coatings to expand the operational capabilities of metals and alloys is an urgent problem for modern enterprises. Diffusion titanium, chromium, and aluminum-based coatings are widely used to solve this challenge. The article aims to obtain the corrosion-electrochemical properties and increase the microhardness of the obtained coatings compared with the initial Ti-6Al-4V alloy. For this purpose, corrosion resistance, massometric tests, and microstructural analysis were applied, considering various aggressive environments (acids, sodium carbonate, and hydrogen peroxide) at different concentrations, treatment temperatures, and saturation times. As a result, corrosion rates, polarization curves, and X-ray microstructures of the uncoated and coated Ti-6Al-4V titanium alloy samples were obtained. Histograms of corrosion inhibition ratio for the chromium–aluminum coatings in various environments were discussed. Overall, the microhardness of the obtained coatings was increased 2.3 times compared with the initial Ti-6Al-4V alloy. The corrosion-resistant chromaluminizing alloy in aqueous solutions of organic acids and hydrogen peroxide was recommended for practical application in conditions of exposure to titanium products. Full article

(This article belongs to the Special Issue Novel Approaches in the Design, Simulation, and Manufacturing for Processes and Systems)

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17 pages, 4815 KiB

Open AccessArticle

Analytical Approach for Forecasting the Load Capacity of the EN AW-7075-T6 Aluminum Alloy Joints Created Using RFSSW Technology

by Rafał Kluz, Magdalena Bucior, Andrzej Kubit, Tomasz Trzepieciński, Katarzyna Antosz and Koen Faes

Materials 2024, 17(7), 1529; https://doi.org/10.3390/ma17071529 - 27 Mar 2024

Cited by 2 | Viewed by 870

Abstract

To ensure the high reliability of aircraft structures, the Refill Friction Stir Spot Welding (RFSSW) process must be characterized by a high load capacity of the welds and a small standard deviation of the load capacity spread. This allows us to obtain uniform functional properties in the connections, ensuring the high quality of the process. This work aims to select the most favorable technological parameters for the welding process of EN AW-7075-T6 Alclad aluminum alloy sheets, which are used for the production of aircraft structures. The best networks were calculated using the Statistica 13.3 program. The obtained results were compared with the results of previous investigations. It has been shown that a model using neural networks allows for the determination of connection parameters with much greater accuracy than the classical model. The maximum error in estimating the load capacity of the connection for the mathematical model was 6.13%, and the standard deviation was 14.51%. In the case of neural networks, the maximum error value did not exceed 1.55%, and the standard deviation was 3.74%. It was shown that, based on the neural model, it is possible to determine the process parameters that ensure the required quality capacity of the process, ensuring a probability of obtaining the required load capacity of the connections amounting to P = 0.999935 with a defect rate of 0.0065%. This possibility is not provided by the classical model due to its large error in estimating the process spread and the high sensitivity of the process input parameters to the output parameters. Full article

(This article belongs to the Special Issue Novel Approaches in the Design, Simulation, and Manufacturing for Processes and Systems)

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19 pages, 8130 KiB

Open AccessArticle

Numerical Simulation and Experimental Analysis on Seam Feature Size and Deformation for T-Joint Laser–GMAW Hybrid Welding

by Nai-Kun Wei, Jin Shi, Run-Dang Yang, Jun-Tong Xi, Xiao-Meng Luo, Xu-Yue Yin and Rui-Xue Zhang

Materials 2024, 17(1), 228; https://doi.org/10.3390/ma17010228 - 31 Dec 2023

Viewed by 1332

Abstract

As an innovative technique, laser–GMAW hybrid welding manifests significant superiority in enhancing welding productivity and quality, albeit the optimization of process parameters poses a challenge for practical application. The present manuscript elucidates the influence of process parameters on the dimensional characteristics of the welding seam and the distortion of 8 mm T-joints in the context of laser–GMAW hybrid welding, and channels both simulation and experimentation. The outcomes denote that the dual conical model serves as an efficacious aid for the numerical simulation of T-joint laser–GMAW hybrid welding. Furthermore, the repercussions of process parameters on welding seam dimensional characteristics remain consistently similar in both the simulation and experimental results. From the simulation outcomes, it becomes apparent that the distortion of the base material can be efficiently managed by implementing anti-distortion measures. This inquiry offers both a theoretical and experimental foundation for optimizing process parameters of T-joint laser–GMAW hybrid welding, presenting certain engineering applicability. Full article

(This article belongs to the Special Issue Novel Approaches in the Design, Simulation, and Manufacturing for Processes and Systems)

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17 pages, 7664 KiB

Open AccessArticle

Diffusion Nitride Coatings for Heat-Resistant Steels

by Khrystyna Berladir, Tetiana Hovorun, Vitalii Ivanov, Djordje Vukelic and Ivan Pavlenko

Materials 2023, 16(21), 6877; https://doi.org/10.3390/ma16216877 - 26 Oct 2023

Cited by 1 | Viewed by 1233

Abstract

The effect of ion nitriding and nitriding in a melamine-based powder mixture on the structure and properties of AISI A290C1M steel was studied in the paper. Using ion nitriding made it possible to shorten the technological cycle’s duration by 5–6 times compared to two-stage nitriding, optimize the diffusion layer’s composition, provide a technologically simple process automation scheme, and improve the quality of nitride coatings. After the proposed mode of ion nitriding, a saturated layer depth of 0.25–0.32 mm, hardness up to 1000 HV, and an increase in wear resistance by 2.17 times were obtained. Using 95% melamine + 5% sodium fluoride during nitriding in a powder mixture significantly simplified the technological process. It did not require additional expensive equipment, which in turn significantly simplified the nitriding process with energy savings. The proposed technology and the composition of the mixture contributed to a significant acceleration of the nitriding process of AISI A290C1M steel, compared to traditional gas nitriding, and to obtain a hardness of the nitride layer of 970 HV and an increase in wear resistance by 2.6 times. A nitriding speed is explained by a significantly higher amount of atomic nitrogen when using melamine instead of ammonia and by the almost simultaneous disintegration of nanodispersed particles when the nitriding temperature was reached. After nitriding in a powder mixture, steel was subject to the slightest wear. Full article

(This article belongs to the Special Issue Novel Approaches in the Design, Simulation, and Manufacturing for Processes and Systems)

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14 pages, 4227 KiB

Open AccessArticle

Analyzing the Potential of Drill Bits 3D Printed Using the Direct Metal Laser Melting (DMLM) Technology to Drill Holes in Polyamide 6 (PA6)

by Lukasz Nowakowski, Michal Skrzyniarz, Slawomir Blasiak, Jaroslaw Rolek, Dimka Vasileva and Tanya Avramova

Materials 2023, 16(8), 3035; https://doi.org/10.3390/ma16083035 - 12 Apr 2023

Cited by 3 | Viewed by 1854

Abstract

Drilling with standard twist drill bits is the most common method to create cylindrical holes. With the constant development of additive manufacturing technologies and easier access to additive manufacturing equipment, it is now possible to design and fabricate solid tools suitable for various machining applications. Specially designed 3D printed drill bits seem more convenient for standard and nonstandard drilling operations than conventionally made tools. The study described in this article aimed to analyze the performance of a solid twist drill bit made from steel 1.2709 using direct metal laser melting (DMLM), which was compared with that of a drill bit manufactured conventionally. The experiments involved assessing the dimensional and geometric accuracy of the holes made by the two types of drill bits and comparing the forces and torques occurring during the drilling of holes in cast polyamide 6 (PA6). Full article

(This article belongs to the Special Issue Novel Approaches in the Design, Simulation, and Manufacturing for Processes and Systems)

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