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Advanced Manufacturing Processes: Technologies and Applications

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

Deadline for manuscript submissions: 31 May 2025 | Viewed by 1600

Special Issue Editors


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Guest Editor
1. Department of Industrial Engineering, University of Florence, Via di Santa Marta 3, 50139 Firenze, Italy
2. CEMMPRE, Department of Mechanical Engineering, University of Coimbra, Rua Luís Reis Santos, 3030-788 Coimbra, Portugal
Interests: explosive welding; welding; additive manufacturing; WAAM; metallurgy; metallurgical characterization
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
1. ISEL, Department of Mechanical Engineering, Polytechnic Institute of Lisbon, Rua Conselheiro Emídio Navarro, 1959-007 Lisboa, Portugal
2. CEMMPRE, Department of Mechanical Engineering, University of Coimbra, Rua Luís Reis Santos, 3030-788 Coimbra, Portugal
Interests: solid-state welding; friction stir welding; explosion welding; dissimilar materials welding; solid-state processing
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
1. ESAD.CR, Polytechnic Institute of Leiria, Rua Isidoro Inácio Alves de Carvalho, 2500-321 Caldas da Rainha, Portugal
2. CEMMPRE, Department of Mechanical Engineering, University of Coimbra, Rua Luís Reis Santos, 3030-788 Coimbra, Portugal
Interests: welding technology; processing technology; microstructural and mechanical characterization; friction stir welding; explosion welding
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The current advancement of all engineering fields and the emergence of individualized applications with stricter requirements increase the need to improve the current manufacturing processes or even develop new manufacturing processes capable of delivering the required features for each specific application. This development creates the need for new research areas addressing these novel and developing processes, which usually differ from current and conventional ones. Therefore, there is a need for specific research regarding these processes, not only from a process point of view, but also including research addressing material science and characterizations, corrosion properties, numerical simulations, case studies, and so on, related to these processes.

This Special Issue will publish high-quality, original research and review papers addressing manufacturing processes that have been developed more recently or that present new features or variations regarding conventional processes. Some examples include additive manufacturing technologies, solid-state welding processes (e.g., friction stir welding, explosive welding, and magnetic pulse welding), advanced fusion welding and coating processes, powder metallurgy, and machining, among others. Many aspects related to these processes may be addressed, such as process development, metallurgical characterization, machining, tool wear, corrosion resistance, industrial applications, case studies, improvements in energy efficiency, sustainability and environmental impact, heat treatment and post-processing, surface analysis, and numerical modeling and simulation.

Dr. Gustavo H. S. F. L. Carvalho
Dr. Ivan Galvão
Dr. Rui Manuel Leal
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. 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
  • solid-state welding
  • impact welding processes
  • explosive welding
  • magnetic pulse welding
  • diffusion bonding
  • advanced fusion welding processes
  • powder metallurgy/sintering
  • machining, numerical modelling and simulation

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Published Papers (2 papers)

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Research

16 pages, 15909 KiB  
Article
Microstructure Evolution and Forming Characteristics of Post-Weld Composite Treatment of 6061 Aluminum Alloy Tailor Welded Blanks
by Xiaonan Dong, Gang Song and Liming Liu
Appl. Sci. 2024, 14(19), 8998; https://doi.org/10.3390/app14198998 - 6 Oct 2024
Viewed by 743
Abstract
The mechanical properties and cross-sectional geometric dimensions of the fusion zone (FZ), heat affected zone (HAZ), and base metal (BM) of 6xxx series aluminum alloys are inconsistent after filler wire welding, which reduces the formability of aluminum alloy tailor welded blanks (TWBs). This [...] Read more.
The mechanical properties and cross-sectional geometric dimensions of the fusion zone (FZ), heat affected zone (HAZ), and base metal (BM) of 6xxx series aluminum alloys are inconsistent after filler wire welding, which reduces the formability of aluminum alloy tailor welded blanks (TWBs). This paper proposes a post-weld cold rolling-solution heat treatment (PWCR-SHT) composite process, and the effects of weld excess metal, plastic deformation, and SHT on the formability of aluminum alloy TWBs are studied. The results show that the PWCR-SHT composite process eliminates the weld excess metal and internal pores, reduces the stress concentration at the weld toe, eliminates the local strain hardening behavior, and causes recrystallization in the FZ region. The cupping value of aluminum alloy TWBs using SHT is 105% of BM, in comparison, the cupping value of aluminum alloy TWBs using the PWCR-SHT composite process is 119% of BM, which is the result of the combined effect of geometric dimensions consistency and mechanical properties consistency. Full article
(This article belongs to the Special Issue Advanced Manufacturing Processes: Technologies and Applications)
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20 pages, 3756 KiB  
Article
Research on Critical Quality Feature Recognition and Quality Prediction Method of Machining Based on Information Entropy and XGBoost Hyperparameter Optimization
by Dongyue Qu, Chaoyun Gu, Hao Zhang, Wenchao Liang, Yuting Zhang and Yong Zhan
Appl. Sci. 2024, 14(18), 8317; https://doi.org/10.3390/app14188317 - 15 Sep 2024
Viewed by 652
Abstract
To address the problem of predicting machining quality for critical features in the manufacturing process of mechanical products, a method that combines information entropy and XGBoost (version 2.1.1) hyperparameter optimization is proposed. Initially, machining data of mechanical products are analyzed based on information [...] Read more.
To address the problem of predicting machining quality for critical features in the manufacturing process of mechanical products, a method that combines information entropy and XGBoost (version 2.1.1) hyperparameter optimization is proposed. Initially, machining data of mechanical products are analyzed based on information entropy theory to identify critical quality characteristics. Subsequently, a quality prediction model for these critical features is established using the XGBoost machine learning framework. The model’s hyperparameters are then optimized through Bayesian optimization. This method is applied as a case study to a medium-speed marine diesel engine piston. After the critical quality characteristics in the machining process are identified, the machining quality of these vital characteristics is predicted, and the results are compared with those obtained from a machine learning model without hyperparameter optimization. The findings demonstrate that the proposed method effectively predicts the machining quality of mechanical products. Full article
(This article belongs to the Special Issue Advanced Manufacturing Processes: Technologies and Applications)
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