Data-Driven Digital Transformation in Industry 4.0
A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Computer Science & Engineering".
Deadline for manuscript submissions: closed (31 July 2024) | Viewed by 2721
Special Issue Editors
Interests: industrial informatics; smart grid; blockchain; IoT platforms
Special Issue Information
Dear Colleagues,
Digital technologies are transforming industrial frameworks. Recent technology breakthroughs in fields such as AI, robotics, and the Internet of Things, often under the umbrella term of Industry 4, have shown to be significant in allowing organizations to adopt new manufacturing processes using real-time data analytics. Digital manufacturing technologies, including the real-time management of assets, have provided new insights for manufacturers to better understand the root cause of issues and therefore embrace and adopt Industry 4 technologies. At the core of Industry 4 is the ability to link networks together as one system to allow a real-time flow of information via a secure and reliable digital infrastructure. The MDPI Electronics journal seeks submissions for a Special Issue on data-driven digital transformation in Industry 4.0. We welcome submissions from researchers working in the field of data-driven digital transformation and Industry 4.0 applications. Contributions should include discussions on real-life applications and new research perspectives.
The topics of interest include, but are not limited to, the following:
- Big Data applied to Industry 4.0;
- Machine learning applied to asset management;
- Predictive maintenance and condition-based maintenance;
- Industrial communication protocols;
- Communication middleware for Industry 4.0;
- Ontologies for data management;
- Cybersecurity issues of industry 4.0;
- Industry 4 and 5 emerging
Dr. Michele Albano
Prof. Dr. David Baglee
Guest Editors
Manuscript Submission Information
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Keywords
- CBM
- digitalization
- industrial cyber security
- emerging technologies
- Industry 4.0
- Industry 5.0
- MIMOSA
- Big Data
- asset management
- predictive mainte-nance
- industrial protocols
- ontologies
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