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Recent Advances in Metal Forming Technology (Second Volume)
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Recent Advances in Metal Forming Technology (Second Volume)

A special issue of Materials (ISSN 1996-1944). This special issue belongs to the section "Metals and Alloys".

Deadline for manuscript submissions: closed (10 January 2023) | Viewed by 8652

Special Issue Editor

Prof. Dr. Dong Won Jung

E-Mail Website
Guest Editor
School of Mechanical Engineering, Jeju National University, Jeju 63243, Republic of Korea
Interests: constitutive modeling at hot working conditions; cold- and hot-roll forming; incremental sheet forming; cold and hot stamping; computational modeling for metal forming applications; formability in sheet metal forming; friction stir welding
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

We would like to bring your attention to a Special Issue of Materials on "Recent Advances in Metal Forming Technology". Plastic deformation is always a crucial part of the metal forming process. By achieving proper plastic deformation in the work material, the formed parts tend to be a better product in terms of quality and reliability. Producing the most efficient and economical manufacturing process in any forming division is one of the most challenging tasks. Research challenges in metal forming processes remain the same and are growing day by day in terms of minimizing product defects and waste management.

The purpose of this Special Issue is to collect valuable research articles in which improved techniques are presented with significant contributions to the forming process. The goal of this Issue is to improve the understanding of the forming process by presenting both positive and negative aspects. For example, by explaining the advantages and disadvantages of procedures involved in the forming process, it will allow the reader to understand more about the process and will help them to think and develop more optimized procedures in the near future. As research about metal forming methods never ends, some aspects will always require continuous improvement. Topics of interest include but are not limited to the following:

  • Recent developments in the metal forming process;
  • Constitutive modeling at hot working conditions;
  • Optimized computational procedures for metal forming applications;
  • Formability improvement in incremental sheet forming process;
  • Formability improvement in roll forming process;
  • Formability improvement in stamping process;
  • Hybrid metal forming process;
  • Spring back modeling methods;
  • Optimization procedures of forming process;
  • Damage models (cold and hot);
  • Tool wear and fracture;
  • Friction stir welding process.

I am looking forward to your contributions.

Prof. Dr. Dong Won Jung
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. Materials 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 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

  • metal forming process
  • material modeling
  • formability improvement
  • spring back and fracture model estimation
  • optimization procedures
  • sheet metal forming
  • friction stir welding

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Published Papers (3 papers)

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Research

14 pages, 3172 KiB  
Article
Optimization of Wire Electric Discharge Machining (WEDM) Process Parameters for AISI 1045 Medium Carbon Steel Using Taguchi Design of Experiments
by Uzair Khaleeq uz Zaman, Usman Ahmed Khan, Shahid Aziz, Aamer Ahmed Baqai, Sajid Ullah Butt, Danish Hussain, Ali Siadat and Dong Won Jung
Materials 2022, 15(21), 7846; https://doi.org/10.3390/ma15217846 - 7 Nov 2022
Cited by 13 | Viewed by 3386
Abstract
With the growth of the manufacturing industry, the demand for alloy materials with high hardness, toughness, and impact strength has increased. Since products from such alloy materials are extremely difficult to manufacture with high accuracy and reduced surface roughness using traditional machining techniques, [...] Read more.
With the growth of the manufacturing industry, the demand for alloy materials with high hardness, toughness, and impact strength has increased. Since products from such alloy materials are extremely difficult to manufacture with high accuracy and reduced surface roughness using traditional machining techniques, wire electric discharge machining can be used to machine such complex parts with more precision. In this case-study-based research, machining factors such as current, pulse-on time, and voltage are studied to determine their effects on the material removal rate for AISI 1045 medium carbon steel. The Taguchi L9 orthogonal array is used in the design of experiments for optimization. Statistical techniques such as analysis of variance and signal-to-noise ratio are used to identify the control parameters that matter most in bringing about optimal results. Based on the results, the current is the most crucial control variable in this investigation. Moreover, the maximum material removal rate obtained was 0.7112 mm3/min with the obtained optimized values of current (I) = 16 A, voltage (V) = 50 V, and pulse-on time (Ton) = 100 µs. Full article
(This article belongs to the Special Issue Recent Advances in Metal Forming Technology (Second Volume))
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22 pages, 7392 KiB  
Article
Magnetic, Electrical, and Physical Properties Evolution in Fe3O4 Nanofiller Reinforced Aluminium Matrix Composite Produced by Powder Metallurgy Method
by Negin Ashrafi, Azmah Hanim Mohamed Ariff, Dong-Won Jung, Masoud Sarraf, Javad Foroughi, Shamsuddin Sulaiman and Tang Sai Hong
Materials 2022, 15(12), 4153; https://doi.org/10.3390/ma15124153 - 11 Jun 2022
Cited by 8 | Viewed by 2405
Abstract
An investigation into the addition of different weight percentages of Fe3O4 nanoparticles to find the optimum wt.% and its effect on the microstructure, thermal, magnetic, and electrical properties of aluminum matrix composite was conducted using the powder metallurgy method. The [...] Read more.
An investigation into the addition of different weight percentages of Fe3O4 nanoparticles to find the optimum wt.% and its effect on the microstructure, thermal, magnetic, and electrical properties of aluminum matrix composite was conducted using the powder metallurgy method. The purpose of this research was to develop magnetic properties in aluminum. Based on the obtained results, the value of density, hardness, and saturation magnetization (Ms) from 2.33 g/cm3, 43 HV and 2.49 emu/g for Al-10 Fe3O4 reached a maximum value of 3.29 g/cm3, 47 HV and 13.06 emu/g for the Al-35 Fe3O4 which showed an improvement of 41.2%, 9.3%, and 424.5%, respectively. The maximum and minimum coercivity (Hc) was 231.87 G for Al-10 Fe3O4 and 142.34 G for Al-35 Fe3O4. Moreover, the thermal conductivity and electrical resistivity at a high weight percentage (35wt.%) were 159 w/mK, 9.9 × 10−4 Ω·m, and the highest compressive strength was 133 Mpa. Full article
(This article belongs to the Special Issue Recent Advances in Metal Forming Technology (Second Volume))
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17 pages, 4632 KiB  
Article
Flow Behavior of AA5005 Alloy at High Temperature and Low Strain Rate Based on Arrhenius-Type Equation and Back Propagation Artificial Neural Network (BP-ANN) Model
by Sijia Li, Wenning Chen, Krishna Singh Bhandari, Dong Won Jung and Xuewen Chen
Materials 2022, 15(11), 3788; https://doi.org/10.3390/ma15113788 - 26 May 2022
Cited by 18 | Viewed by 2225
Abstract
To realize the purpose of energy saving, materials with high weight are replaced by low-weight materials with eligible mechanical properties in all kinds of fields. Therefore, conducting research works on lightweight materials under specified work conditions is extremely important and profound. To understand [...] Read more.
To realize the purpose of energy saving, materials with high weight are replaced by low-weight materials with eligible mechanical properties in all kinds of fields. Therefore, conducting research works on lightweight materials under specified work conditions is extremely important and profound. To understand the relationship of aluminum alloy AA5005 among flow stress, true strain, strain rate, and deformation temperature, hot isothermal tensile tests were conducted within the strain rate range 0.0003–0.03 s−1 and temperature range 633–773 K. Based on the true stress-true strain curves obtained from the experiment, a traditional constitutive regression Arrhenius-type equation was utilized to regress flow behaviors. Meanwhile, the Arrhenius-type equation was optimized by a sixth-order polynomial function for compensating strain. Thereafter, a back propagation artificial neural network (BP-ANN) model based on supervised machine learning was also employed to regress and predict flow stress in diverse deform conditions. Ultimately, by introducing statistical analyses correlation coefficient (R2), average absolute relative error (AARE), and relative error (δ) to the comparative study, it was found that the Arrhenius-type equation will lose accuracy in cases of high stress. Additionally, owning higher R2, lower AARE, and more concentrative δ value distribution, the BP-ANN model is superior in regressing and predicting than the Arrhenius-type constitutive equation. Full article
(This article belongs to the Special Issue Recent Advances in Metal Forming Technology (Second Volume))
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