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Additive Manufacturing and Machining Technologies for Engineering Materials
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Additive Manufacturing and Machining Technologies for Engineering Materials

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

Deadline for manuscript submissions: 20 January 2026 | Viewed by 2071

Special Issue Editor

Dr. Pierpaolo Iovane

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Guest Editor
ENEA, Laboratory Smart Components and Systems for Sustainable Manufacturing, Department for Sustainability, Division Technologies and Materials for Sustainable Manufacturing Industry, 80055 Portici, Italy
Interests: additive manufacturing; advanced materials; energy conversion; materials chemistry

Special Issue Information

Dear Colleagues,

The development of new materials with remarkable properties has led to the enhancement of traditional machining technologies. Moreover, changing market dynamics have shifted the focus from mass production to customized mass production, and from the product to the end consumer. As a result, the optimization of production is becoming increasingly fundamental. Additive manufacturing is rapidly emerging as a key element for manufacturing companies in this evolving landscape. Advances in hybrid machining processes are on the rise, combining the benefits of both methods—the efficiency of traditional machining and the precision of modern techniques—enabling applications in aerospace, biomedical, and automotive industries. Additionally, future research is expected to focus on AI-driven process control, novel composite materials, and further integration of Industry 4.0 technologies.

This Special Issue aims to address the current trends and research gaps regarding novel materials, emerging technologies, advanced applications, and innovations in process and post-processing for additive manufacturing.

Dr. Pierpaolo Iovane
Guest 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 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. 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

  • additive manufacturing
  • engineering materials
  • 3D printing
  • process optimization

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Published Papers (2 papers)

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Research

19 pages, 9214 KiB  
Article
Tribological Performance of Direct Metal Laser Sintered 20MnCr5 Tool Steel Countersamples Designed for Sheet Metal Forming Applications
by Krzysztof Żaba, Marcin Madej, Beata Leszczyńska-Madej, Tomasz Trzepieciński and Ryszard Sitek
Appl. Sci. 2025, 15(15), 8711; https://doi.org/10.3390/app15158711 - 6 Aug 2025
Viewed by 1554
Abstract
This article presents the results of the tribological performance of 20MnCr5 (1.7147) tool steel countersamples produced by Direct Metal Laser Sintering (DMLS), as a potential material for inserts or working layers of sheet metal forming tools. Tribological tests were performed using a roller-block [...] Read more.
This article presents the results of the tribological performance of 20MnCr5 (1.7147) tool steel countersamples produced by Direct Metal Laser Sintering (DMLS), as a potential material for inserts or working layers of sheet metal forming tools. Tribological tests were performed using a roller-block tribotester. The samples were sheet metals made of materials with significantly different properties: Inconel 625, titanium-stabilised stainless steel 321, EN AW-6061 T0 aluminium alloy, and pure copper. The samples and countersamples were analysed in terms of their wear resistance, coefficient of friction (COF), changes in friction force during testing, and surface morphology after tribological contact under dry friction conditions. The tests were performed on DMLSed countersamples in the as-received state. The largest gain of countersample mass was observed for the 20MnCr5/EN AW-6061 T0 friction pair. The sample mass loss in this combination was also the largest, amounting to 19.96% of the initial mass. On the other hand, in the 20MnCr5/Inconel 625 friction pair, no significant changes in the mass of materials were recorded. For the Inconel 625 sample, a mass loss of 0.04% was observed. The basic wear mechanism of the samples was identified as abrasive wear. The highest friction forces were observed in the 20MnCr5/Cu friction pair (COF = 0.913) and 20MnCr5/EN AW-6061 T0 friction pair (COF = 1.234). The other two samples (Inconel 625, 321 steel) showed a very stable value of the friction force during the roller-block test resulting in a COF between 0.194 and 0.213. Based on the changes in friction force, COFs, and mass changes in friction pair components during wear tests, it can be concluded that potential tools in the form of inserts or working layers manufactured using 3D printing technology, the DMLS method, without additional surface treatment can be successfully used for forming sheets of 321 steel and Inconel 625. Full article
(This article belongs to the Special Issue Additive Manufacturing and Machining Technologies for Engineering Materials)
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17 pages, 1635 KiB  
Article
Predicting Relative Density of Pure Magnesium Parts Produced by Laser Powder Bed Fusion Using XGBoost
by Kristijan Šket, Snehashis Pal, Janez Gotlih, Mirko Ficko and Igor Drstvenšek
Appl. Sci. 2025, 15(15), 8592; https://doi.org/10.3390/app15158592 - 2 Aug 2025
Viewed by 297
Abstract
In this work, Laser Powder Bed Fusion (LPBF), an additive manufacturing (AM) process, was optimised to produce pure magnesium components. The focus of the presented work is on the prediction of the relative product density using the machine learning model XGBoost to improve [...] Read more.
In this work, Laser Powder Bed Fusion (LPBF), an additive manufacturing (AM) process, was optimised to produce pure magnesium components. The focus of the presented work is on the prediction of the relative product density using the machine learning model XGBoost to improve the production process and thus the usability of the material for practical use. Experimental tests with different parameters, laser power, scanning speed and layer thickness, and fixed parameters, track overlapping and hatching distance, were analysed and resulted in relative material densities between 89.29% and 99.975%. The XGBoost model showed high predictive power, achieving an R2 test result of 0.835, a mean absolute error (MAE) of 0.728 and a root mean square error (RMSE) of 0.982. Feature importance analysis showed that the interaction of laser power and scanning speed had the largest influence on the predictions at 35.9%, followed by laser power × layer thickness at 29.0%. The individual contributions were laser power (11.8%), scanning speed (10.7%), scanning speed × layer thickness (9.0%) and layer thickness (3.6%). These results provide a data-based method for LPBF parameter settings that improve manufacturing efficiency and component performance in the aerospace, automotive and biomedical industries and identify optimal parameter regions for a high density, serving as a pre-optimisation stage. Full article
(This article belongs to the Special Issue Additive Manufacturing and Machining Technologies for Engineering Materials)
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