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Micromachines
Special Issues
Advanced Manufacturing Technology and Systems, 4th Edition
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Advanced Manufacturing Technology and Systems, 4th Edition

A special issue of Micromachines (ISSN 2072-666X). This special issue belongs to the section "D：Materials and Processing".

Deadline for manuscript submissions: 31 May 2026 | Viewed by 742

Special Issue Editors

Dr. Guochao Li

E-Mail Website
Guest Editor
School of Mechanical Engineering, Jiangsu University of Science and Technology, Zhenjiang 212100, China
Interests: cutting tool CAD/CAM/CAE; manufacturing process monitoring; in situ measurement
Special Issues, Collections and Topics in MDPI journals
Dr. Zhaoju Zhu

E-Mail Website
Guest Editor
School of Mechanical Engineering and Automation, Fuzhou University, Fuzhou 350108, China
Interests: high-performance manufacturing; biomedical design and manufacturing; process condition monitoring
Special Issues, Collections and Topics in MDPI journals
Dr. Youqiang Xing

E-Mail Website
Guest Editor
School of Mechanical Engineering, Southeast University, Nanjing 211189, China
Interests: tool coatings; green machining; additive manufacturing; micro/nano machining
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Advanced manufacturing technology and systems (AMTS) combine principles of mechanical engineering with design innovation to create products and processes that are better, faster and more precise. The core of AMTS is the design, fabrication, and application of original and effective solutions related to manufacturing machines, process integration and systems to keep up with the dynamic needs of today's ever-evolving industries. In this Special Issue, we seek papers in advanced manufacturing technology and systems that cover a broad scope involving manufacturing processes, machine tool design, system optimization, smart and flexible manufacturing, theoretical study and metrology. In addition, multidisciplinary (physical, chemical, micro/nano and biomedicine) manufacturing technologies and systems are welcome, including micro-/nanofabrication, nanomaterial processes, biomedical fabrication, intelligent control, energy conversion, etc. All papers, such as original research papers and review articles, are welcome.

Dr. Guochao Li
Dr. Zhaoju Zhu
Dr. Youqiang Xing
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. Micromachines 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 2100 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

  • additive manufacturing
  • machining and forming technology
  • micro- and nanofabrication
  • smart manufacturing
  • non-traditional manufacturing processes
  • energy-efficient manufacturing
  • computer-integrated manufacturing systems
  • process monitoring
  • AI for manufacturing
  • system optimization
  • system reliability analysis

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Related Special Issue

Published Papers (2 papers)

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Research

18 pages, 7712 KB  
Article
Prediction Model and Experimental Verification of Surface Roughness of Single Crystal Diamond Chemical Mechanical Polishing Based on Archimedes Optimization Algorithm
by Zhaoze Li, Xiaoguang Guo, Guanghui Fan, Yueming Deng, Renke Kang and Xuefei Wang
Micromachines 2025, 16(10), 1121; https://doi.org/10.3390/mi16101121 - 30 Sep 2025
Viewed by 316
Abstract
Chemical mechanical polishing (CMP) is a critical technique for fabricating ultra-smooth and high-quality surfaces of single crystal diamond (SCD), where processing parameters profoundly influence polishing performance. To achieve superior diamond surface finishes, this study first investigates the effects of key process parameters, including [...] Read more.
Chemical mechanical polishing (CMP) is a critical technique for fabricating ultra-smooth and high-quality surfaces of single crystal diamond (SCD), where processing parameters profoundly influence polishing performance. To achieve superior diamond surface finishes, this study first investigates the effects of key process parameters, including oxidant concentration, catalyst type, and abrasive particle size, on surface quality through single-factor experiments. Subsequently, an Archimedes optimization algorithm (AOA)-based prediction model for diamond CMP surface roughness (Sa) is developed and validated experimentally. Results reveal that high-concentration oxidants, fine-particle abrasives, and dual-catalyst polishing systems synergistically enhance surface quality. The AOA-based prediction model demonstrates a root-mean-square error (RMSE) of 0.006 and a correlation coefficient (R) of 0.98 between the predicted and experimental Sa values. Under the conditions of a dual-catalyst type, 35% oxidant concentration, and 500 nm abrasive particle size, the model predicts a surface roughness of 0.128 nm, with an experimental value of 0.125 nm and a relative error of less than 3%. These findings highlight the capability of the model to accurately forecast surface roughness across diverse process parameters, offering a novel predictive framework for precision CMP of SCD. Full article
(This article belongs to the Special Issue Advanced Manufacturing Technology and Systems, 4th Edition)
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22 pages, 9020 KB  
Article
Hybrid Inductively Coupled Plasma and Computer-Controlled Optical Surfacing Polishing for Rapid Fabrication of Damage-Free Ultra-Smooth Surfaces
by Wei Li, Peiqi Jiao, Dawei Luo, Qiang Xin, Bin Fan, Xiang Wu, Bo Gao and Qiang Chen
Micromachines 2025, 16(9), 1073; https://doi.org/10.3390/mi16091073 - 22 Sep 2025
Viewed by 307
Abstract
The polymer deposition layer (PDL) formed during inductively coupled plasma (ICP) processing significantly limits the figuring accuracy and surface quality of fused silica optics. This study investigates the formation mechanism, composition, and evolution of the PDL under varying dwell times and proposes an [...] Read more.
The polymer deposition layer (PDL) formed during inductively coupled plasma (ICP) processing significantly limits the figuring accuracy and surface quality of fused silica optics. This study investigates the formation mechanism, composition, and evolution of the PDL under varying dwell times and proposes an innovative dwell time gradient strategy to suppress roughness deterioration. A significant disparity in hardness and elastic modulus between the deposition layer and the substrate is revealed, explaining its preferential removal and protective buffering effect in computer-controlled optical surfacing (CCOS). A hybrid ICP-CCOS polishing process was developed for processing a ϕ100 mm fused silica mirror. The results show that within 33 min, the surface graphic error RMS was significantly reduced from 58.006 nm to 12.111 nm, and within 90 min, the surface roughness was ultra-precisely reduced from Ra 1.719 nm to Ra 0.151 nm. The average processing efficiency was approximately 0.63 cm2/min. Critically, a damage-free, ultra-smooth surface without subsurface damage (SSD) was successfully achieved. This hybrid process enables the simultaneous optimization of figure accuracy and roughness, eliminating the need for iterative figuring cycles. It provides a novel theoretical framework for high-precision figuring and post-ICP polymer removal, advancing the efficient fabrication of high-performance optics. Full article
(This article belongs to the Special Issue Advanced Manufacturing Technology and Systems, 4th Edition)
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