Production and Industrial Engineering in Metal Processing

A special issue of Processes (ISSN 2227-9717). This special issue belongs to the section "Manufacturing Processes and Systems".

Deadline for manuscript submissions: 31 January 2025 | Viewed by 1194

Special Issue Editor


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Guest Editor
Department of Mechanical Manufacturing, Faculty of Technology, CEETEPS—State Center of Technological Education “Paula Souza”, Campus Mauá, Av. Antônia Rosa Fioravante 804, Mauá 09390-120, São Paulo, Brazil
Interests: mechanical manufacturing; tribology; abrasive wear; wear test

Special Issue Information

Dear Colleagues,

Extrusion, wire drawing, forging, rolling, plastic forming of metals, turning, milling, drilling, additive manufacturing, welding, and metal casting are all important mechanical and metallurgical manufacturing processes used in the mechanical and metallurgical industries. Studying, researching, and understanding the metallurgical, physical–mechanical, chemical, and tribological factors and behaviours that influence—“positively” or “negatively”—the processing of metallic materials when they are under these metallurgical and mechanical industrial manufacturing processes are important to improve their chemical, metallurgical, mechanical, and tribological performance.

Thus, this Special Issue, titled “Production and Industrial Engineering in Metal Processing”, aims to curate novel advances related to metallurgical and mechanical industrial manufacturing processes, involving the metallurgical and mechanical analysis of metallic materials submitted to plastic forming, machining, and additive manufacturing, in addition to factors related to corrosion, tribological behaviours, as well as the use of modeling and simulation. The topics of interest for this Special Issue include, but are not limited to, the following:

  • Extrusion process;
  • Wire drawing process;
  • Forging process;
  • Rolling process;
  • Plastic deformation of metals—general aspects;
  • Turning process;
  • Milling process;
  • Drilling process;
  • Additive manufacturing;
  • Welding process;
  • Metal casting process;
  • Tribological aspects related to mechanical processes of manufacturing;
  • Industrial lubrication.

Dr. Ronaldo Câmara Cozza
Guest Editor

Manuscript Submission Information

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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. Processes 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 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

  • metallurgical processes of manufacturing
  • mechanical processes of manufacturing
  • plastic deformation of metals
  • machining
  • additive manufacturing
  • wear
  • lubrication

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Published Papers (1 paper)

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Research

17 pages, 1209 KiB  
Article
An Experimental Analysis of Taguchi-Based Gray Relational Analysis, Weighted Gray Relational Analysis, and Data Envelopment Analysis Ranking Method Multi-Criteria Decision-Making Approaches to Multiple-Quality Characteristic Optimization in the CNC Drilling Process
by Fitore Abdullahu, Fatlume Zhujani, Georgi Todorov and Konstantin Kamberov
Processes 2024, 12(6), 1212; https://doi.org/10.3390/pr12061212 - 13 Jun 2024
Cited by 1 | Viewed by 716
Abstract
The goal of this research is to optimize the input parameters utilized in dry CNC drilling of forging steel to attain sustainable machining. Particular emphasis will be placed on achieving high productivity while minimizing the impact on surface quality. To achieve the aforementioned [...] Read more.
The goal of this research is to optimize the input parameters utilized in dry CNC drilling of forging steel to attain sustainable machining. Particular emphasis will be placed on achieving high productivity while minimizing the impact on surface quality. To achieve the aforementioned goal, three Taguchi-based multi-criteria decision-making (MCDM) approaches, such as traditional gray relational analysis (GRA), weighted gray relational analysis (WGRA), and data envelopment analysis ranking (DEAR), were used for simultaneous optimization of the MRR and Ra. In Taguchi’s L12 (24) orthogonal array design, the cutting mode parameters—such as cutting speed, depth of cut, feed rate, and point angle—have been chosen as the input parameters for the modeling and analysis of the drilling process characteristics. The process of determining the effect of the input parameters on the output parameters was carried out with the use of analysis of variance (ANOVA). The best results from the studies were Ra = 2.19 and MRR = 375 mm3/s, which corresponded to Taguchi’s single optimization levels, S2F1D1A2 and S2F2D2A1, respectively. In the next step, the performance values obtained for each MCDM technique were reoptimized using the Taguchi method, and the optimal levels were obtained: for traditional GRA, the level S2F1D2A1 (Ra = 2.52 µm, MRR = 125 mm3/s); for WGRA, the level S2F1D1A1 (Ra = 2.31 µm, MRR = 83 mm3/s); and for DEAR, the level S2F2D2A1 (Ra = 4.42 µm, MRR = 375 mm3/s), respectively. Lastly, in order to compare the experiments’ performance, validation tests were carried out. The results of the experiments using multi-objective optimization show that traditional GRA improved the overall quality response characteristics by 29.86% compared to the initial setup parameters, while weighted GRA improved them by 34.48%, with the DEAR method providing an improvement of 96%. Based on the findings of this investigation, the DEAR optimization method outperforms the GRA method. As a result, the proposed methods are useful tools for multi-objective optimization of cutting parameters. Full article
(This article belongs to the Special Issue Production and Industrial Engineering in Metal Processing)
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