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Machines
Special Issues
Towards a New Era for Smart Manufacturing
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Towards a New Era for Smart Manufacturing

A special issue of Machines (ISSN 2075-1702). This special issue belongs to the section "Robotics, Mechatronics and Intelligent Machines".

Deadline for manuscript submissions: closed (31 January 2023) | Viewed by 2361

Special Issue Editors

Dr. Marcos de Sales Guerra Tsuzuki

E-Mail Website
Guest Editor
Department of Mechatronics and Mechanical Systems Engineering, Universidade de São Paulo, São Paulo 2231, Brazil
Interests: CAD/CAM; computer graphics; industry 4.0; cutting and packing and optimization problems
Special Issues, Collections and Topics in MDPI journals
Dr. Yuval Cohen

E-Mail Website
Guest Editor
Department of Industrial Engineering, Afeka Tel-Aviv College of Engineering, Tel-Aviv 69988, Israel
Interests: smart intelligent systems; service science; Industry 4.0; human–machine interaction; artificial emotional intelligence; operations management
Special Issues, Collections and Topics in MDPI journals
Dr. Ahmad Barari

E-Mail Website
Guest Editor
Department of Automotive, Mechanical and Manufacturing Engineering, Faculty of Engineering and Applied Science, University of Ontario Institute of Technology, Oshawa, ON L1H 7K4, Canada
Interests: precision manufacturing; advanced manufacturing technologies; digital manufacturing; precision manufacturing; measurement uncertainty; 3D coordinate metrology
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The authors from the conference IFAC IMS 2022, held in Telaviv, Israel, are invited to submit an expanded version of their papers to Machines. The selected papers are related to the industrial applications discussed in several major topics of the conference, including: life support systems, robotics and mechatronics, Industry 4.0, Internet of Things, additive manufacturing, ultrasound techniques, electrical machines and drives, electric vehicles, autonomous vehicles and drones, industrial lightning, deep learning, machine learning, intelligent support systems, smart quality assurance, augmented reality, vision systems, Big Data analytics, fusion of sensor information, digital twins, and so on.

Prof. Dr. Marcos de Sales Guerra Tsuzuki
Dr. Yuval Cohen
Prof. Dr. Ahmad Barari
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. 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.

Published Papers (1 paper)

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Research

22 pages, 568 KiB  
Article
Skills Intelligence in the Steel Sector
by Karina Maldonado-Mariscal, Mathias Cuypers, Adrian Götting and Michael Kohlgrüber
Machines 2023, 11(3), 335; https://doi.org/10.3390/machines11030335 - 01 Mar 2023
Cited by 1 | Viewed by 1715
Abstract
The ecological and digital transformations of the steel industry intensify already existing skill shortages and create specific skill demands that are currently not being met. One of the main problems in this sector lies in the lack of sufficient information on which skills [...] Read more.
The ecological and digital transformations of the steel industry intensify already existing skill shortages and create specific skill demands that are currently not being met. One of the main problems in this sector lies in the lack of sufficient information on which skills companies need and which skills trainings are suitable for today’s challenges. In addition, more information is needed to provide more and better information for policy-making processes for getting the sector’s workforce well-equipped for digitalisation and decarbonisation. This paper uses the framework of skills intelligence in the steel sector, reflecting on theoretical developments and the application of concrete tools in the European projects BEYOND 4.0 and ESSA. The main research questions guiding this work are: To what extent is the concept of skills intelligence useful in the steel sector, and how can it be applied in the steel sector in Europe? This paper provides empirical data based on qualitative and quantitative research carried out in the mentioned projects. The main contribution of this paper is the development of concrete reflections on the concept of skills intelligence based on tools in the steel sector. This work operationalises the skills intelligence approach at sectoral level, namely for the steel industry, and shows how this sector approach can be implemented at the European, national and regional levels. The main findings suggest that skills intelligence in the steel sector is not limited to the preparation and presentation of data but creates a governance structure to mitigate skills imbalances. Full article
(This article belongs to the Special Issue Towards a New Era for Smart Manufacturing)
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