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Photonics
Special Issues
Innovative Optical Technologies in Advanced Manufacturing
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Innovative Optical Technologies in Advanced Manufacturing

A special issue of Photonics (ISSN 2304-6732).

Deadline for manuscript submissions: 31 January 2026 | Viewed by 1275

Special Issue Editors

Dr. Ci Song

E-Mail Website
Guest Editor
College of Intelligent Science and Technology, National University of Defense Technology, Changsha 410073, China
Interests: ultra-precision polishing; magnetorheological finishing; ion beam polishing; AR; precision engineering; ultra smooth; advanced optical fabrication; low damage
Special Issues, Collections and Topics in MDPI journals
Dr. Xing Peng

E-Mail Website
Guest Editor
College of Intelligent Science and Technology, National University of Defense Technology, Changsha 410073, China
Interests: defect inspection; optical design; illumination design; machine vision; image processing
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The field of advanced manufacturing has seen significant advancements in recent years, driven by the increasing demand for high-performance optical systems in diverse applications. New materials, fabrication techniques, and computational tools are enabling researchers to explore novel approaches to optical design that have the potential to revolutionize the field. This Special Issue on "Innovative Optical Technologies in Advanced Manufacturing" showcases the latest research and developments in optical technology, highlighting innovative concepts, methodologies, and practical applications. Key areas covered in this Special Issue include but are not limited to advanced materials, measurement and metrology, precision manufacturing, optical design, computational imaging, image processing, and advanced manufacturing.

We believe that this collection of articles will serve as an invaluable resource for professionals seeking to advance the frontiers of advanced manufacturing through innovative optical technologies. We hope it will inspire further innovation and foster collaboration among scientists, researchers, and engineers, ultimately leading to new perspectives and breakthroughs in this field. It is within this context that we announce the Special Issue of Photonics on “Innovative Optical Technologies in Advanced Manufacturing”.

This Special Issue intends to provide a timely opportunity for experts to discuss and summarize the most recent advancements and challenges in innovative optical technologies for advanced manufacturing. We invite submissions that include but are not limited to the topics mentioned above. Both theoretical and experimental studies, along with comprehensive review and survey papers, are welcome.

Dr. Ci Song
Dr. Xing Peng
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. Photonics 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

  • advanced materials
  • measurement and metrology
  • precision manufacturing
  • optical design
  • computational imaging
  • image processing
  • advanced manufacturing
  • detection technology
  • process monitoring
  • machine learning

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Published Papers (1 paper)

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20 pages, 4326 KiB  
Article
Real-Time Polarimetric Imaging and Enhanced Deep Learning Model for Automated Defect Detection of Specular Additive Manufacturing Surfaces
by Dingkang Li, Xing Peng, Hongbing Cao, Yuanpeng Xie, Shiqing Li, Xiang Sun and Xinjie Zhao
Photonics 2025, 12(3), 243; https://doi.org/10.3390/photonics12030243 - 9 Mar 2025
Viewed by 667
Abstract
Additive manufacturing (AM) technology has found extensive applications in aerospace, medical, and automotive fields. Defect detection technology remains a research focus in AM process monitoring. While machine learning and neural network algorithms have recently achieved significant advancements in innovative applications for AM defect [...] Read more.
Additive manufacturing (AM) technology has found extensive applications in aerospace, medical, and automotive fields. Defect detection technology remains a research focus in AM process monitoring. While machine learning and neural network algorithms have recently achieved significant advancements in innovative applications for AM defect detection, practical implementations still face challenges, including insufficient detection accuracy and poor system robustness. To address these limitations, this study proposes the YOLOv5-CAD defect detection model. Firstly, the convolutional block attention module (CBAM) is introduced into the core feature extraction module C3 of the backbone network to enhance attention to critical information and improve multi-scale defect target adaptability. Secondly, the original CIoU loss function is replaced with the Alpha-IoU loss function to accelerate network convergence and strengthen system robustness. Additionally, a fully decoupled detection head substitutes the original coupled head in the YOLOv5s model, separating the object classification and bounding box regression tasks to improve detection accuracy. Finally, a polarization technology-based visual monitoring system is developed to acquire defect images of laser AM workpieces, establishing the model’s training sample database. Compared with YOLOv5, the proposed model demonstrates a 2.5% improvement in precision (P), 2.2% enhancement in recall (R), 3.1% increase in mean average precision (mAP50), and 3.2% elevation in mAP50-95. These quantitative improvements confirm the model’s capability to provide robust and real-time technical solutions for industrial AM quality monitoring, effectively addressing current limitations in defect detection accuracy and system reliability. Full article
(This article belongs to the Special Issue Innovative Optical Technologies in Advanced Manufacturing)
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