Machine Learning-Based Intelligent Industry 4.0 Control Systems for Manufacturing

A special issue of Processes (ISSN 2227-9717). This special issue belongs to the section "Process Control and Monitoring".

Deadline for manuscript submissions: 20 November 2024 | Viewed by 39

Special Issue Editors


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Guest Editor
Department of Engineering and Mathematics, Sheffield Hallam University, Sheffield, UK
Interests: artificial intelligence; machine learning; Industry 4.0; internet-of-things; food manufacturing
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
National Centre of Excellence for Food Engineering, Sheffield Hallam University, Howard Street, Sheffield S1 1WB, UK
Interests: advanced process control; sustainable food processing; Industry 4.0; artificial intelligence
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Artificial intelligence (AI) and machine learning (ML) techniques have huge potential to transform manufacturing industries, with a diverse range of applications from machinery condition monitoring to product quality control. The promise of integrating AI/ML with Industry 4.0 control systems to create intelligent processes has attracted significant interest from researchers in the last 5 years. These intelligent control systems have vast potential across manufacturing industries: from high-value manufacturing, such as automotive and aerospace, to fast-moving consumer goods such as food.

This Special Issue on “Machine Learning-Based Intelligent Industry 4.0 Control Systems for Manufacturing” aims to cover recent advances in the development of intelligent AI/ML-based control systems for manufacturing processes. Topics of interest include, but are not limited to:

  • AI-based computer vision applications for quality control in manufacturing processes;
  • Intelligent machine monitoring systems;
  • Edge applications of AI/ML for manufacturing processes;
  • Data issues (such as federated data sharing, de-duplication, data privacy and ethical concerns);
  • Intelligent systems for enabling low-carbon (and net-zero) manufacturing processes.

Dr. Alex Shenfield
Dr. Hongwei 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. 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

  • artificial intelligence
  • machine learning
  • sustainable manufacturing
  • Industry 4.0
  • internet of things

Published Papers

This special issue is now open for submission.
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