Intelligent Systems for Industry 4.0

Dear Colleagues,

The advent of information and communication technology has been shaping new realities in many fields, including manufacturing. Consequently, a concept of manufacturing called the fourth industrial revolution (known as Industry 4.0, Smart Manufacturing, and Connected Factory) has emerged. Industry 4.0 does not mean achieving mere automation among product realization enablers (e.g., machine tools, robots, assembly lines, CAD/CAM/CAE systems, ERP systems, and SCM systems), as was the case for its predecessor. It, instead, embarks on achieving autonomy and harmony among the enablers. Thus, the enablers must be capable of performing high-level intellectual tasks, such as understanding (i.e., why is it happening), prediction (what will happen), and adaptation (what decisions should be taken and implemented to choose the right course of action). Therefore, artificially intelligent systems must empower the enablers. The intelligent systems create a vast ecosystem that integrates human learning, machine learning, logical inferences (deduction, induction, and abduction), experimental data, sensor signals, analytical results, simulations, creative thinking, cognitive reflections, and big data analytics. Policymakers, practitioners, and researchers around the globe have been acting in a coordinated manner yet remaining independent to achieve the goals of Industry 4.0 with the aid of various intelligent systems. This Special Issue showcases some of the relevant studies. Thus, the Special Issue solicits original articles, reviews, and perspectives on the following topics (but not limited to):

• Artificial Narrow Intelligence for Industry 4.0;
• Artificial Super Intelligent for Industry 4.0;
• Semantically Annotated Linked Data for Industry 4.0;
• Intelligent Systems for Digital Twins;
• Intelligent Systems for Learning Factory;
• Intelligent System for Cyber-Physical Systems;
• Intelligent Systems for Big Data Analytics;
• Intelligent Systems for Sensor Signal Processing;
• Knowledge Engineering for Industry 4.0;
• Intelligent Systems for Digital Manufacturing Commons;
• Intelligent Systems for Implementing Industry 4.0 in SMEs;
• Intelligent Systems for Mitigating Big Data Inequalities.

Prof. Dr. Sharifu Ura
Dr. Angkush Kumar Ghosh
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. AI 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 1600 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.

• artificial narrow intelligence
• artificial super intelligent
• semantic annotation
• linked data
• big data
• data analytics
• digital twins
• cyber-physical systems
• sensor signals
• digital manufacturing commons
• knowledge-based systems
• SMEs
• big data inequalities
• learning factory