Smart Machining and Machine Tools

A special issue of Machines (ISSN 2075-1702). This special issue belongs to the section "Advanced Manufacturing".

Deadline for manuscript submissions: 31 August 2025 | Viewed by 1127

Special Issue Editors


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Guest Editor
Key Laboratory of Education Ministry for Modern Design & Rotor-Bearing System, Xi’an Jiaotong University, Xi’an, China
Interests: intelligent machining; operation and maintenance

E-Mail Website
Guest Editor
School of Mechanical and Precision Instrument Engineering, Xi’an University of Technology, Xi’an 710048, China
Interests: Intelligent spindle service performance monitoring

Special Issue Information

Dear Colleagues,

With the significant adjustment of global manufacturing models and industrial patterns, new manufacturing models with intelligent manufacturing as their core feature are gradually emerging. Intelligent manufacturing is not only a trend in the future development of the manufacturing industry, but also a factor shaping the world's manufacturing industry. At present, advanced manufacturing is developing towards high speed, high precision, automation, intelligence, networking, and intelligent computerized manufacturing. On the one hand, manufacturing technology is moving towards intelligence, and more and more manufacturing technologies are based on intelligence, such as intelligent monitoring, intelligent diagnosis, intelligent decisionmaking, and intelligent control in the manufacturing process. Meanwhile, an increasing number of new machine tools have intelligent functions, including intelligent machine tool components, greatly improving processing efficiency and quality.

This is a call for papers for a Special Issue on "Smart Machining and Machine Tools". This Special Issue will provide a venue for scholars and researchers to share their most recent theoretical and technical successes, as well as to highlight key topics and difficulties for future study in the field. The submitted papers are expected to present original ideas and potential contributions to theory and practice. Possible research topics include, but are not limited to:

  • Smart machining;
  • Intelligent monitoring in the manufacturing process;
  • Intelligent diagnosis in the manufacturing process;
  • Intelligent decision-making in the manufacturing process;
  • Intelligent control in the manufacturing process;
  • Intelligent machine tools;
  • Intelligent machine tool components.

Prof. Dr. Xiaohu Li
Dr. Yanfei 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. Machines 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

  • machine tools
  • smart machines
  • monitoring
  • diagnosis
  • control
  • manufacturing
  • decisionmaking

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Published Papers (1 paper)

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Research

21 pages, 6098 KiB  
Article
A Novel Method for Identifying Tool–Holder Interface Dynamics Based on Receptance Coupling
by Dingtang Zhao, Xiaohu Li, Shaoke Wan, Qiangqiang Zhao and Jun Hong
Machines 2024, 12(12), 911; https://doi.org/10.3390/machines12120911 - 12 Dec 2024
Viewed by 524
Abstract
The structural dynamics of a machine tool play a significant role in chatter occurrence, which significantly deteriorates the metal-cutting performance. The receptance coupling substructure analysis (RCSA) is known for eliminating the experimental dependency on repetitive impact hammer testing. However, the identified contact parameters [...] Read more.
The structural dynamics of a machine tool play a significant role in chatter occurrence, which significantly deteriorates the metal-cutting performance. The receptance coupling substructure analysis (RCSA) is known for eliminating the experimental dependency on repetitive impact hammer testing. However, the identified contact parameters between the holder and tool, which are necessary for RCSA, usually lose accuracy in predicting tool point dynamics when applied to other tool clamping lengths or to combinations with other tools. To this end, a new method based on conventional impact hammer testing and RCSA technique to identify these parameters is proposed. Two descriptions of the proposed method are presented for different tool combinations and different clamping lengths, respectively. This new method eliminates the need for specialized experimental setups. The predicted tool point dynamics, using the identified contact parameters from the proposed method, show deviations below 3% with one exception, indicating that the identifications are accurate for various clamping lengths. The new approach yields significant advancements in the predicted tool point dynamics and stability boundaries compared to a traditional identification method reported in the literature. Full article
(This article belongs to the Special Issue Smart Machining and Machine Tools)
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