1st edition
conjunction with ICANN
1 Day
Workshop
3
Workshop Organizers
2026
Padua (near Venice), Italy
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Workshop Description

AI-Driven Manufacturing in the Industry 5.0 Era

Bridging neural network research and real-world industrial deployment

The transition toward Industry 5.0 introduces a new paradigm for manufacturing systems, shifting the focus from pure automation to human-centric, sustainable and resilient industrial ecosystems. In this evolving landscape, production environments are increasingly modeled as complex cyber-physical systems characterized by multi-scale interactions, nonlinear dynamics, uncertainty and strong interdependencies between physical processes, digital infrastructures and human operators.

Recent advances in Artificial Neural Networks and Deep Learning are redefining Advanced Manufacturing by enabling intelligent, data-driven and self-optimizing production processes. Among manufacturing technologies, Additive Manufacturing (AM) stands out as one of the most promising and challenging domains for the deployment of Artificial Intelligence.

Neural networks, Physics-Informed Neural Networks (PINNs) and hybrid physics–data-driven approaches are emerging as key enablers for high-fidelity surrogate modeling, learning under limited data regimes, real-time control architectures, autonomous defect detection and multi-objective optimization, including energy efficiency and sustainability metrics.

Topics of Interest

  • Neural and hybrid models for AM process simulation
  • Physics-informed and knowledge-guided learning
  • Data-driven digital twins for AM systems
  • Real-time monitoring, control, and anomaly detection
  • Multi-objective and sustainability-aware process optimization
  • Robotics integration in intelligent AM environments
  • Robustness, interpretability and certification of AI in safety-critical contexts

By fostering an interdisciplinary and application-oriented dialogue, the workshop seeks to bridge the gap between methodological advances in neural networks and their reliable deployment in industrial AM systems contributing to the evolution of Additive Manufacturing toward intelligent, sustainable and resilient Industry 5.0 production paradigms.

General Information

The proceedings of ICANN 2026 will be published in the Springer Lecture Notes in Computer Science (LNCS) series and indexed as a peer-reviewed publication in the Web of Science.

Accepted papers from the International Workshop on Artificial Intelligence for Industry 5.0: Neural Models, Hybrid Intelligence and Resilient Complex Systems will be included in the same LNCS volume alongside the ICANN 2026 proceedings.

For detailed submission guidelines, please visit: https://e-nns.org/icann2026/submission/

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Submission Guidelines

Submission Guidelines

Submissions must comply with the official ICANN 2026 formatting rules. Detailed instructions are available at: ICANN Submission Page.

  • Paper Format Full papers (max 12 pages, references included) and short extended abstracts (max 2 pages, non-archival) are accepted. Templates are available in the official guidelines.
  • Submission System Submit via CMT Portal, selecting the “Workshops” track and the session: Artificial Intelligence for Industry 5.0: Neural Models, Hybrid Intelligence and Resilient Complex Systems.
  • Peer Review All submissions are peer-reviewed. Accepted papers will appear in the official workshop proceedings.
  • Originality Requirement Submissions must be original and not under review or published elsewhere.
  • Supplementary Material Up to two files (1 PDF + 1 ZIP) may be included. These are optional and not guaranteed to be reviewed or published.
  • Workshop Assignment Each workshop is managed independently. Submissions sent to the wrong track may not be considered.
  • Extended Abstracts Accepted but non-archival (they will not be published in proceedings).

Anonymization Guidelines

The review process is double-blind. Authors must ensure complete anonymity.

  • Remove Author Details Do not include names, affiliations, or identifying information. Use “Anonymous submission”.
  • Avoid Self-Identification Refer to your previous work in third person, as you would cite any other paper.
  • Keep References Intact Do not remove author names from citations. Avoid placeholders like “removed for review”.
  • Omit Acknowledgements Remove funding details or acknowledgements in the submitted version.
  • Compliance Non-anonymized submissions may be rejected without review.
Team

Workshop Organizers

Portrait of Dr. Fabrizia Devito
CMT Management

Dr. Fabrizia Devito, Ph.D.

University of Bari Aldo Moro

Researcher at the Department of Computer Science. Her research focuses on Additive Manufacturing technologies and advanced data processing, with particular emphasis on AI and computational techniques for complex manufacturing challenges.

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Portrait of Prof. Donato Impedovo Organizer

Prof. Donato Impedovo

University of Bari Aldo Moro

Associate Professor at the Department of Computer Sciences. His research focuses on pattern recognition, Machine Learning and signal and image processing, with applications in intelligent systems and human–machine interaction.

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Portrait of Prof. Fulvio Lavecchia Organizer

Prof. Fulvio Lavecchia

Polytechnic University of Bari

Associate Professor at the Department of Mechanics, Mathematics and Management. His research bridges advanced manufacturing systems, Additive Manufacturing and industrial process optimization, promoting high-impact engineering solutions.

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Contacts

Reach out for any questions about the workshop

Email

AI4industry.icann@outlook.com

Location

School of Psychology, University of Padua (near Venice), Italy

ICANN 2026 Website

e-nns.org/icann2026 ↗