AI-Enabled Industrial Robotics and Production Automation for Smart Manufacturing Transformation

A special issue of Machines (ISSN 2075-1702). This special issue belongs to the section "Automation and Control Systems".

Deadline for manuscript submissions: 31 December 2026 | Viewed by 82

Editor


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Guest Editor
1. Institute of Automation and Info-Communication, University of Miskolc, Miskolc, Hungary
2. College of Engineering and Technology, University of Doha for Science and Technology, Doha, Qatar
Interests: automation and control processes in addition to robotics and artificial intelligence

Special Issue Information

Dear Colleagues,

Recent advances in industrial robotics, production automation, artificial intelligence, sensing technologies, and smart manufacturing are transforming modern manufacturing systems. Industrial machines and robotic systems are increasingly expected to operate with higher autonomy, flexibility, accuracy, safety, and adaptability in dynamic production environments. These developments are essential for improving productivity, quality, energy efficiency, predictive maintenance, human–robot collaboration, and decision-making in advanced manufacturing systems.

We are pleased to invite you to contribute to this Special Issue, which focuses on recent research advances in industrial robotics and production automation for manufacturing transformation and upgrading. The topic is strongly aligned with the scope of Machines, as it addresses the design, modelling, control, optimization, monitoring, diagnostics, and implementation of advanced machines and automated production systems. This Special Issue aims to bring together theoretical developments, simulation-based studies, experimental validation, industrial case studies, and review papers that support the next generation of intelligent, connected, and autonomous manufacturing systems.

In this Special Issue, original research articles and reviews are welcome. Research areas may include, but are not limited to, industrial robotics, production automation, AI-based control, collaborative robotics, machine vision for quality inspection, predictive maintenance, fault diagnosis, sensor fusion, digital twins, smart manufacturing, Industry 4.0/5.0, human–robot collaboration, robotic manipulation, automated assembly, and intelligent decision-support systems for production environments.

We look forward to receiving your contributions.

Dr. Rabab Benotsmane
Guest Editor

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 250 words) can be sent to the Editorial Office for assessment.

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-anonymized 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

  • industrial robotics
  • production automation
  • smart manufacturing
  • artificial intelligence
  • collaborative robotics
  • predictive maintenance
  • digital twins
  • machine vision
  • Industry 4.0
  • fault diagnosis

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Published Papers

This special issue is now open for submission.
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