Developing Artificial Intelligence and Other Digital Tools to Improve Manufacturing Operations
A special issue of Machine Learning and Knowledge Extraction (ISSN 2504-4990). This special issue belongs to the section "Learning".
Deadline for manuscript submissions: 30 November 2025
Special Issue Editors
Interests: manufacturing technology; fixture design; machining; smart manufacturing
Special Issues, Collections and Topics in MDPI journals
Interests: mathematics; algorithms; artificial intelligence
Special Issues, Collections and Topics in MDPI journals
2. INEGI—Institute of Science and Innovation in Mechanical and Industrial Engineering, Pólo FEUP, Rua Dr. Roberto Frias, 400, 4200-465 Porto, Portugal
Interests: composite materials; joining processes; automation
Special Issues, Collections and Topics in MDPI journals
Interests: tribology; coatings; manufacturing processes
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
The constant focus on increasing production efficiency and democratizing the implementation of smart manufacturing principles has contributed significantly to the development of artificial intelligence, which, when applied in diverse situations, can contribute to faster decision-making and judiciousness. In fact, artificial intelligence, when applied to production systems or services, can contribute significantly to increasing productivity—in many cases, no longer requiring human intervention in decision-making—through the creation of algorithms that respond to decisions that are necessary to make, considering a given line of reasoning or a previous set of events that trace a trend. Machine learning or deep learning strategies are increasingly widespread in the most diverse activities linked to production, from scheduling production orders, decision-making when replacing end-of-life tools, and collecting and selecting products based on their observed qualities, among many other tasks that can be automated in terms of decision-making.
Given the constant development of new algorithms and applications linked to manufacturing, this Special Issue, in collaboration with the “8th International Conference on Design, Simulation, Manufacturing: The Innovation Exchange (DSMIE-2025)" (https://dsmie.sumdu.edu.ua/), aims to contribute to cutting-edge research developments that allow for significant advances in this field. High-quality contributions that aim to develop new solutions based on artificial intelligence and machine learning are welcome, clearly showing significant advances in this area of expertise.
Prof. Dr. Vitalii Ivanov
Dr. Isabel Cristina Pinto
Prof. Dr. Raul D. S. G. Campilho
Dr. Francisco J. G. Silva
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. Machine Learning and Knowledge Extraction is an international peer-reviewed open access quarterly 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 1800 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
- deep learning
- algorithms
- production systems
- manufacturing
- services
- decision-making
- smart manufacturing
- process optimization
- digital transformation
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