Artificial Intelligence for Engineering and Industry: Methods, Systems and Emerging Applications
A Special Issue of AI (ISSN 2673-2688) belonging to the section "AI in Autonomous Systems".
Deadline for manuscript submissions: 31 May 2027 | Viewed by 655
Editors
Interests: data driven optimization; soft sensors; low-carbon engines; machine learning; artificial intelligence
Special Issues, Collections and Topics in MDPI journals
Interests: deep reinforcement learning; sensor signal processing for intelligent transportation systems; vehicle sensor data analytics
Special Issues, Collections and Topics in MDPI journals
Interests: deep reinforcement learning; multi-agent control; energy-saving driving; energy and thermal management; optimal control
Interests: data driven optimization; performance degradation; low-carbon engines; AI applications in engineering
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Artificial intelligence is becoming a core enabling technology across modern engineering and industry, transforming how engineers design products, monitor equipment, optimize processes and operate complex systems—from smart manufacturing and energy engineering to transportation, aerospace and civil infrastructure. Industrial deployment raises distinctive challenges: limited and noisy data, strict safety and reliability requirements, real-time and on-device constraints, interpretability for domain experts and regulators and the need to fuse physics-based models with data-driven methods.
This Special Issue provides a focused platform for advances in artificial intelligence methods, systems and applications for engineering and industry. We welcome original research and review articles that address real engineering constraints and present convincing case studies in industrial settings, fostering dialogue among artificial intelligence researchers, domain engineers and practitioners.
Topics of interest include, but are not limited to:
- Machine learning and deep learning methods tailored to engineering data (limited, noisy, or multi-modal);
- Fault diagnosis, anomaly detection, prognostics and predictive maintenance;
- Intelligent control, optimization and reinforcement learning for engineering systems;
- Physics-informed machine learning and hybrid data-driven/model-based approaches;
- Industrial large models and generative artificial intelligence for engineering workflows, documentation and knowledge management;
- Artificial intelligence applications in smart manufacturing, energy and power systems, transportation, aerospace and civil infrastructure;
- Edge artificial intelligence, real-time inference and embedded intelligence for industrial equipment and autonomous systems
We look forward to receiving your contributions.
Dr. Huaiyu Wang
Dr. Qun Wang
Dr. Fei Ju
Dr. Dai Liu
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 250 words) can be sent to the Editorial Office for assessment.
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-anonymized 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 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 1800 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.
Keywords
- artificial intelligence for engineering
- industrial artificial intelligence
- machine learning
- deep learning
- fault diagnosis and predictive maintenance
- intelligent control
- digital twin
- physics-informed machine learning
- smart manufacturing
- trustworthy artificial intelligence
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