- Machines | An Open Access Journal from MDPI
Machines is an international, peer-reviewed, open access journal on machinery and engineering published monthly online by MDPI The IFToMM is affiliated with Machines and its members receive a discount on the article processing charges
- Machines | Aims Scope - MDPI
About Machines Aims Machines (ISSN 2075-1702) is an international, peer-reviewed journal on machinery and engineering It publishes research articles, reviews and communications
- Machines | Editorial Office - MDPI
Machines Editorial Office MDPI, Grosspeteranlage 5, 4052 Basel, Switzerland Tel : +41 61 683 77 34 (MDPI HQ Basel, Switzerland 9:00 - 17:00 CET) For queries regarding Special Issues, submission deadlines, editorial policies, discounts and vouchers, please contact the journal’s Editorial Office: machines@mdpi com Managing Editor Ms Missy Wu
- Machines | Instructions for Authors - MDPI
Manuscripts for Machines should be submitted online at susy mdpi com The submitting author, who is generally the corresponding author, is responsible for the manuscript during the submission and peer review process
- Machines | Editorial Board - MDPI
Interests: electrical machines; fault diagnosis; reliability; signal processing * Section: Electrical Machines and Drives Special Issues, Collections and Topics in MDPI journals
- Machines | Special Issues - MDPI
Machines publishes Special Issues to create collections of papers on specific topics, with the aim of building a community of authors and readers to discuss the latest research and develop new ideas and research directions
- Machines | Announcements - MDPI
We are pleased to share that Machines (ISSN: 2075-1702) has received an increased CiteScore of 4 7 in June 2025 The CiteScore ranks the journal 28 out of 160 titles (Q1) in the “Control and Optimization” category, an impressive achievement
- The Path to Smart Farming: Innovations and Opportunities in . . . - MDPI
Machines with ‘eyes’ in agricultural activities are called machine vision (MV) This, also known as agro-vision or the ‘eyes’ of robots, provides non-destructive, robust, rapid, and steady methods to monitor cultivation processes
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