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Cutting Processes for Materials in Manufacturing
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Cutting Processes for Materials in Manufacturing

A special issue of Materials (ISSN 1996-1944). This special issue belongs to the section "Manufacturing Processes and Systems".

Deadline for manuscript submissions: 20 May 2024 | Viewed by 2841

Special Issue Editors

Dr. Jian Weng

E-Mail Website
Guest Editor
Institute of Machining Technology (ISF), TU Dortmund University, 44227 Dortmund, Germany
Interests: metal cutting; cutting mechanics; surface integrity; tool wear
Dr. Kejia Zhuang

E-Mail Website
Guest Editor
School of Mechanical and Electronic Engineering, Wuhan University of Technology, Wuhan 430070, China
Interests: superalloy; metal cutting; surface integrity; cutting edge geometry
Special Issues, Collections and Topics in MDPI journals
Dr. Dongdong Xu

E-Mail Website
Guest Editor
School of Mechanical Engineering, Tongji University, Shanghai, China
Interests: cutting; wear; alloy fatigue
Dr. Benkai Li

E-Mail Website
Guest Editor
School of Mechanical & Automotive Engineering, Qingdao University of Technology, Qingdao, China
Interests: cutting; superalloy; powder
Dr. Hongguang Liu

E-Mail Website
Guest Editor
State Key Laboratory for Manufacturing System Engineering, Xi'an Jiaotong University, 99 Yanxiang Road, Xi'an 710054, China
Interests: numerical modeling; material removal processes; surface integrity; cryogenic machining; difficult-to-cut materials
Special Issues, Collections and Topics in MDPI journals
Dr. Gang Wang

E-Mail Website
Guest Editor Assistant
College of Mechanical and Vehicle Engineering, Chongqing University, Chongqing, China
Interests: deep learning

Special Issue Information

Dear Colleagues,

This Special Issue aims to collect research on recent progress in cutting processes of materials in manufacturing, not only for metals but also for composites, optic glass or any other key engineering materials. High-efficiency and high-performance cutting of difficult-to-cut materials has been an important topic for over one hundred years. Our knowledge constantly needs to be updated as the emergence of new machining techniques and materials brings us towards a deeper understanding of cutting processes. Works on any topic within this scope are welcome for submission, for instance, material removal mechanisms, chip formation, cutting force, temperature, surface integrity, etc. The methods can be diverse and over multiple scales based on theoretical models, finite element methods, experiments, artificial intelligence, etc.

Both research papers and review articles are welcome. We look forward to your contributions on (but not limited to) the following topics:

  • Conventional and non-conventional cutting processes;
  • Material removal mechanisms in cutting;
  • Multi-physics in cutting (strain, stress, force, temperature, etc.);
  • Machining-induced surface integrity;
  • Chip formation in cutting processes;
  • Tool performance and design of cutting tools or coatings;
  • Manufacturing of components with complex features;
  • Functional performance of machined components.

Dr. Jian Weng
Dr. Kejia Zhuang
Dr. Dongdong Xu
Dr. Benkai Li
Dr. Hongguang Liu
Guest Editors

Dr. Gang Wang
Guest Editor Assistant

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

  • cutting processes
  • material removal mechanisms
  • cutting mechanics
  • surface integrity
  • chip formation
  • tool performance
  • functional surface

Published Papers (4 papers)

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Research

19 pages, 72798 KiB  
Article
Experimental Investigation of Water Jet-Guided Laser Micro-Hole Drilling of Cf/SiC Composites
by Binying Bao, Guangyi Zhang, Zhongan Chen, Yang Chao, Chunhai Guo and Wenwu Zhang
Materials 2024, 17(9), 1975; https://doi.org/10.3390/ma17091975 - 24 Apr 2024
Viewed by 246
Abstract
In this paper, water jet-guided laser (WJGL) drilling of Cf/SiC composites was employed and the effects of the processing parameters on the depth and quality of the micro-holes were systematically investigated. Firstly, the depth measurement showed that the increase in [...] Read more.
In this paper, water jet-guided laser (WJGL) drilling of Cf/SiC composites was employed and the effects of the processing parameters on the depth and quality of the micro-holes were systematically investigated. Firstly, the depth measurement showed that the increase in processing time and power density led to a significant improvement in micro-hole drilling depth. However, the enhancement of the water jet speed resulted in a pronounced decrease in the depth due to the phenomenon of water splashing. In contrast, the scanning speed, path overlap ratio, pulse frequency, and helium pressure exhibited less effect on the micro-hole depth. Secondly, the microstructural analysis revealed that the increase in power density resulted in the deformation and fracture of the carbon fibers, while the augmentation in water jet speed reduced the thermal defects. Finally, based on the optimization of the processing parameters, a micro-hole of exceptional quality was achieved, with a depth-to-diameter ratio of 8.03 and a sidewall taper of 0.72°. This study can provide valuable guidance for WJGL micro-hole drilling of Cf/SiC composites. Full article
(This article belongs to the Special Issue Cutting Processes for Materials in Manufacturing)
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25 pages, 17845 KiB  
Article
A Study of 2D Roughness Periodical Profiles on a Flat Surface Generated by Milling with a Ball Nose End Mill
by Mihaita Horodinca, Florin Chifan, Emilian Paduraru, Catalin Gabriel Dumitras, Adriana Munteanu and Dragos-Florin Chitariu
Materials 2024, 17(6), 1425; https://doi.org/10.3390/ma17061425 - 20 Mar 2024
Viewed by 472
Abstract
This paper presents a study of 2D roughness profiles on a flat surface generated on a steel workpiece by ball nose end milling with linear equidistant tool paths (pick-intervals). The exploration of the milled surface with a surface roughness tester (on the pick [...] Read more.
This paper presents a study of 2D roughness profiles on a flat surface generated on a steel workpiece by ball nose end milling with linear equidistant tool paths (pick-intervals). The exploration of the milled surface with a surface roughness tester (on the pick and feed directions) produces 2D roughness profiles that usually have periodic evolutions. These evolutions can be considered as time-dependent signals, which can be described as a sum of sinusoidal components (the wavelength of each component is considered as a period). In order to obtain a good approximate description of these sinusoidal components, two suitable signal processing techniques are used in this work: the first technique provides a direct mathematical (analytical) description and is based on computer-aided curve (signal) fitting (more accurate); the second technique (synthetic, less accurate, providing an indirect and incomplete description) is based on the spectrum generated by fast Fourier transform. This study can be seen as a way to better understand the interaction between the tool and the workpiece or to achieve a mathematical characterisation of the machined surface microgeometry in terms of roughness (e.g., its description as a collection of closely spaced 2D roughness profiles) and to characterise the workpiece material in terms of machinability by cutting. Full article
(This article belongs to the Special Issue Cutting Processes for Materials in Manufacturing)
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27 pages, 12548 KiB  
Article
Investigations on the Surface Integrity and Wear Mechanisms of TiAlYN-Coated Tools in Inconel 718 Milling Operations
by Francisco J. G. Silva, Naiara P. V. Sebbe, Rúben D. F. S. Costa, André F. V. Pedroso, Rita C. M. Sales-Contini, Marta L. S. Barbosa and Rui P. Martinho
Materials 2024, 17(2), 443; https://doi.org/10.3390/ma17020443 - 17 Jan 2024
Cited by 2 | Viewed by 775
Abstract
Inconel 718 is a Ni superalloy with superior mechanical properties, even at high temperatures. However, due to its high hardness and low thermal conductivity, it is considered a difficult-to-machine material. This material is widely used in applications that require good dimensional stability, making [...] Read more.
Inconel 718 is a Ni superalloy with superior mechanical properties, even at high temperatures. However, due to its high hardness and low thermal conductivity, it is considered a difficult-to-machine material. This material is widely used in applications that require good dimensional stability, making the milling process the most used in machining this alloy. The wear resulting from this process and the quality of the machined surface are still challenging factors when it comes to Inconel 718. TiAlN-based coating has been used on cutting tools with Yttrium as a doping element to improve the process performance. Based on this, this work evaluated the machined surface integrity and wear resistance of cutting tools coated using Physical Vapor Deposition (PVD) HiPIMS with TiAlYN in the end milling of Inconel 718, varying the process parameters such as cutting speed (vc), feed per tooth (fz), and cutting length (Lcut). It was verified that the Lcut is the parameter that exerts the most significant influence since, even at small distances, Inconel 718 already generates high tool wear (TW). Furthermore, the main wear mechanisms were abrasive and adhesive wear, with the development of a built-up edge (BUE) under a125 m/min feed rate (f) and a Lcut = 15 m. Chipping, cracking, and delamination of the coating were also observed, indicating a lack of adhesion between the coating and the substrate, suggesting the need for a good interlayer or the adjustment of the PVD parameters. Full article
(This article belongs to the Special Issue Cutting Processes for Materials in Manufacturing)
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14 pages, 4485 KiB  
Article
Surface Roughness Prediction of Titanium Alloy during Abrasive Belt Grinding Based on an Improved Radial Basis Function (RBF) Neural Network
by Kun Shan, Yashuang Zhang, Yingduo Lan, Kaimeng Jiang, Guijian Xiao and Benkai Li
Materials 2023, 16(22), 7224; https://doi.org/10.3390/ma16227224 - 18 Nov 2023
Cited by 4 | Viewed by 744
Abstract
Titanium alloys have become an indispensable material for all walks of life because of their excellent strength and corrosion resistance. However, grinding titanium alloy is exceedingly challenging due to its pronounced material characteristics. Therefore, it is crucial to create a theoretical roughness prediction [...] Read more.
Titanium alloys have become an indispensable material for all walks of life because of their excellent strength and corrosion resistance. However, grinding titanium alloy is exceedingly challenging due to its pronounced material characteristics. Therefore, it is crucial to create a theoretical roughness prediction model, serving to modify the machining parameters in real time. To forecast the surface roughness of titanium alloy grinding, an improved radial basis function neural network model based on particle swarm optimization combined with the grey wolf optimization method (GWO-PSO-RBF) was developed in this study. The results demonstrate that the improved neural network developed in this research outperforms the classical models in terms of all prediction parameters, with a model-fitting R2 value of 0.919. Full article
(This article belongs to the Special Issue Cutting Processes for Materials in Manufacturing)
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