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Machines | An Open Access Journal from MDPI Journal Cluster of Mechanical Manufacturing and Automation Control: Aerospace, Automation, Drones, Journal of Manufacturing and Materials Processing, Machines, Robotics and Technologies
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 | 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 | 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 Our aim is to encourage scientists to publish their experimental and theoretical results in as much detail as possible
Machines | Editorial Board - MDPI Interests: design of high precision machines; ultraprecision machining systems; micro-cutting mechanics and physics; multiscale multiphysics modelling and analysis; smart cutting tools and smart machining; physical AI for manufacturing systems
Machines | Article Processing Charges - MDPI All articles published in Machines (ISSN 2075-1702) are published in full open access An article processing charge (APC) of CHF 2400 (Swiss francs) applies to papers accepted after peer review
Machines | January 2025 - Browse Articles - MDPI This study explores the optimization of the machining time in CNC milling machines by varying the machine parameters and toolpath strategies Using the ICAM3D simulation software version 3 1 0, this approach focuses on minimizing the machining time while adhering to operational constraints
Machines | Section Electrical Machines and Drives - MDPI This section invites paper submissions on the emerging research and technologies related to electrical machines and drives (design, control, materials, optimization and diagnosis)
Advances in Noise and Vibrations for Machines - MDPI This collection reflects a still-developing research landscape where data-driven diagnostics, AI-enhanced modeling, and advanced simulation frameworks converge to deliver quieter and more reliable machines or predict problems before they occur