Guest Editors
Prof. Dr. Filipe Alexandre de Sousa Pereira
Email: fal@isep.ipp.pt
Affiliation: LAETA – INEGI - Instituto de Ciência e Inovação em Engenharia Mecânica e Engenharia Industrial, 4200-465 Porto, Portugal
Homepage:
Research Interests: automation & industrial control, industry 4.0/5.0, mechatronics, artificial intelligence, industrial networks & protocols, mobile, collaborative and industrial robotics
Prof. Dr. José Machado
Email: jmachado@dem.uminho.pt
Affiliation: Mechanical Engineering Department, MEtRICs Research Center, University of Minho, 4800-058 Guimarães, Portugal
Homepage:
Research Interests: industry 4.0, cyber-physical systems, dependable controllers, dependable mechatronic systems, mechatronic systems design, manufacturing industry, medical applications, biomedical applications, wellbeing, rehabilitation
Prof. Dr. Paulo Leitão
Email: pleitao@ipb.pt
Affiliation: Research Centre in Digitalization and Intelligent Robotics (CeDRI), Laboratório Associado para a Sustentabilidade e Tecnologia em Regiões de Montanha (SusTEC), Instituto Politécnico de Bragança, 5300-253 Bragança, Portugal
Homepage:
Research Interests: simulation and advanced data analytics, cyber-physical systems and robotics
Prof. Dr. António Ramos Silva
Email: ars@fe.up.pt
Affiliation: INEGI - Instituto de Ciência e Inovação em Engenharia Mecânica e Engenharia Industrial, 4200-465 Porto, Portugal
Homepage:
Research Interests: automation, evolutionary neural networks, learning models, dynamic modelling of systems and automatic control
Prof. Dr. António Mendes Lopes
Email: aml@fe.up.pt
Affiliation: LAETA/INEGI, Faculty of Engineering, University of Porto, Rua Dr. Roberto Frias, 4200-465 Porto, Portugal
Homepage:
Research Interests: complex systems, fractional calculus, robotics and machine design
Summary
The integration of Artificial Intelligence (AI) into industrial systems is revolutionizing how machines, humans, and data interact across production ecosystems. As industries transition from Industry 4.0 to Industry 5.0, the convergence of AI with robotics, cyber-physical systems (CPS), and industrial networks becomes essential for achieving intelligent, resilient, and sustainable automation.
This Special Issue aims to explore advanced research contributions that address the design, implementation, and validation of AI-driven technologies in modern manufacturing environments. We welcome original research and review articles that demonstrate how AI enables adaptive control, predictive maintenance, autonomous robotics, explainable decision-making, and secure IIoT communications. The scope covers both theoretical innovations and applied industrial use cases that foster more flexible, efficient, and human-centric production systems.
Suggested Themes include:
· AI-Powered Cyber-Physical Production Systems (CPPS)
· Intelligent Industrial Robotics and Human-Machine Collaboration
· AI-Based Computer Vision for Quality Inspection and Control
· Secure and Real-Time Industrial Networks (OPC UA, TSN, MQTT)
· Digital Twins and Self-Adaptive Manufacturing Systems
· Edge AI and Federated Learning in Smart Factories
· Sustainable and Resilient Automation for Industry 5.0
Graphic Abstract
Keywords
Artificial Intelligence (AI); Industry 4.0; Industry 5.0; Intelligent Robotics; Cyber-Physical Systems; Industrial Automation; Industrial Internet of Things (IIoT); Industrial Networks and Communication (OPC UA, TSN, MQTT); Edge AI and Explainable AI (XAI)
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