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Simulation and Optimization Methods in Machining and Metallic Structure/Material Design...
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Simulation and Optimization Methods in Machining and Metallic Structure/Material Design (2nd Edition)

A special issue of Metals (ISSN 2075-4701). This special issue belongs to the section "Computation and Simulation on Metals".

Deadline for manuscript submissions: 31 December 2025 | Viewed by 1437

Special Issue Editors

Prof. Dr. Wuyi Ming

E-Mail Website
Guest Editor
1. Department of Electromechanical Science and Engineering, Zhengzhou University of Light Industry, Zhengzhou 450002, China
2. Guangdong HUST Industrial Technology Research Institute, HUST, Dongguang 523808, China
Interests: precision machining; difficult-to-machine materials; green manufacturing; process optimization; artificial intelligence; machine vision
Special Issues, Collections and Topics in MDPI journals
Dr. Zhen Zhang

E-Mail Website
Guest Editor
School of Aerospace Engineering, Huazhong University of Science and Technology, Wuhan 430074, China
Interests: precision machining of composite materials; laser processing; glass molding; process optimization
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Finite element simulation, in addition to other numerical simulation methods, are effective methods to evaluate product performance, and thus have great application prospects in many fields. Conducting parameter optimization based on numerical simulation can further enhance its potential to bring huge economic benefits in machining, structure design, or material design. Furthermore, the continuous development of artificial intelligence can accelerate the process of numerical simulation, structural design, and machining process.

Based on the success of Volume I, this Special Issue calls for papers (i.e., research articles, reviews, and perspectives) which deal with simulation or optimization methods in machining and metallic structure, or in material design.

Priority areas of interest are as follows:

  • Finite element and other numerical simulation methods in traditional and nontraditional machining;
  • Finite element and other numerical simulation methods in metallic structure/material design;
  • Optimization methods in structural parameters, process parameters, or material parameters;
  • Machining method and optimization design in functional structure;
  • AI methods or algorithms to accelerate the above topics.

Papers on process-related topics such as structure or material design, as well as those on the relationship between design parameters and product performance, will also be considered.

Prof. Dr. Wuyi Ming
Dr. Zhen Zhang
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. Metals is an international peer-reviewed open access monthly 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 2600 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

  • finite element method
  • numerical simulation
  • metallic structural optimization
  • process optimization
  • simulation modeling
  • material optimization
  • artificial intelligence (AI)-assisted

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Further information on MDPI's Special Issue policies can be found here.

Published Papers (2 papers)

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Research

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21 pages, 6582 KB  
Article
Research on the Application of the Taguchi-TOPSIS Method in the Multi-Objective Optimization of Punch Wear and Equivalent Stress in Cold Extrusion Forming of Thin-Walled Special-Shaped Holes
by Zhan Liu, Yuhong Yuan and Quan Wu
Metals 2025, 15(11), 1192; https://doi.org/10.3390/met15111192 (registering DOI) - 26 Oct 2025
Abstract
In the cold extrusion forming of thin-walled, specially shaped holes in aviation motor brush boxes, non-uniform metal flow can easily induce local stress concentrations on the punch, thereby accelerating wear. Reducing the punch wear and equivalent stress is therefore critical for ensuring the [...] Read more.
In the cold extrusion forming of thin-walled, specially shaped holes in aviation motor brush boxes, non-uniform metal flow can easily induce local stress concentrations on the punch, thereby accelerating wear. Reducing the punch wear and equivalent stress is therefore critical for ensuring the forming quality of such thin-walled features and extending the service life of the mold. In this study, a slender punch with a specially shaped cross-section was selected as the research object. The Deform-3D Ver 11.0 software, incorporating the Archard wear model, was employed to investigate the effects of five process parameters—extrusion speed, punch cone angle, punch transition filet, friction coefficient, and punch hardness—on the wear depth and equivalent stress of the punch during the compound extrusion process. A total of 25 orthogonal experimental groups were designed, and the simulation results were analyzed using the Taguchi method combined with range analysis to determine the optimal parameter combination. Subsequently, a multi-objective correlation analysis of the signal-to-noise ratios for wear depth and equivalent stress was conducted using the TOPSIS approach. The analysis revealed that the optimal combination of process parameters was an extrusion speed of 12 mm·s−1, a punch cone angle of 50°, a punch transition filet radius of 1.8 mm, a friction coefficient of 0.12, and a punch hardness of 55 HRC. Compared with the initial process conditions, the integrated application of the Taguchi–TOPSIS method reduced the punch wear depth and equivalent stress by 21.68% and 42.58%, respectively. Verification through actual production confirmed that the wear conditions of the primary worn areas were in good agreement with on-site production observations. Full article
(This article belongs to the Special Issue Simulation and Optimization Methods in Machining and Metallic Structure/Material Design (2nd Edition))
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Review

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42 pages, 5637 KB  
Review
Research Progress on Process Optimization of Metal Materials in Wire Electrical Discharge Machining
by Xinfeng Zhao, Binghui Dong, Shengwen Dong and Wuyi Ming
Metals 2025, 15(7), 706; https://doi.org/10.3390/met15070706 - 25 Jun 2025
Viewed by 1248
Abstract
Wire electrical discharge machining (WEDM), as a significant branch of non-traditional machining technologies, is widely applied in fields such as mold manufacturing and aerospace due to its high-precision machining capabilities for hard and complex materials. This paper systematically reviews the research progress in [...] Read more.
Wire electrical discharge machining (WEDM), as a significant branch of non-traditional machining technologies, is widely applied in fields such as mold manufacturing and aerospace due to its high-precision machining capabilities for hard and complex materials. This paper systematically reviews the research progress in WEDM process optimization from two main perspectives: traditional optimization methods and artificial intelligence (AI) techniques. Firstly, it discusses in detail the applications and limitations of traditional optimization methods—such as statistical approaches (Taguchi method and response surface methodology), Adaptive Neuro-Fuzzy Inference Systems, and regression analysis—in parameter control, surface quality improvement, and material removal-rate optimization for cutting metal materials in WEDM. Subsequently, this paper reviews AI-based approaches, traditional machine-learning methods (e.g., neural networks, support vector machines, and random forests), and deep-learning models (e.g., convolutional neural networks and deep neural networks) in aspects such as state recognition, process prediction, multi-objective optimization, and intelligent control. The review systematically compares the advantages and disadvantages of traditional methods and AI models in terms of nonlinear modeling capabilities, adaptability, and generalization. It highlights that the integration of AI by optimization algorithms (such as Genetic Algorithms, particle swarm optimization, and manta ray foraging optimization) offers an effective path toward the intelligent evolution of WEDM processes. Finally, this investigation looks ahead to the key application scenarios and development trends of AI techniques in the WEDM field for cutting metal materials. Full article
(This article belongs to the Special Issue Simulation and Optimization Methods in Machining and Metallic Structure/Material Design (2nd Edition))
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