AI and Machine Learning Applications in Industrial Automation

Dear Colleagues,

In the context of Industry 4.0, production systems are updated to a smart level, taking advantage of the Internet of Things (IoT), cyberphysical systems (CPS), big data, cloud computing, and cognitive systems to achieve flexible, smart, and reconfigurable manufacturing operations to address a dynamic and global market. On this subject, AI and machine learning emerge as effective tools capable of making critical decisions during industrial processes allowing manufacturing operations and control systems to learn from experiences and sensing devices to optimize industrial practice. These innovative systems thus allow increasing quality, productivity, flexibility, information accuracy, and safety through CNC machines, robotics, sensing devices, and data-driven control systems.

This Special Issue aims at analyzing relevant industrial demands for AI and machine learning applications. The chosen focus is providing the state of the art and trends and understanding the main research challenges in AI and machine learning tools applied to industrial automation systems. The topics include but are not limited to industrial applications of deep learning and artificial neural networks, expert systems, fuzzy and neuro-fuzzy systems, genetic algorithms, multi-agent systems, bio-inspired algorithms, and hybrid approaches. Application examples to industrial processes include intelligent manufacturing systems, intelligent control systems, intelligent machines and robots, AI in cybersecurity, AI for predictive maintenance, smart sensors and sensing technology, AI-based condition monitoring, IoT-enabled smart systems, and intelligent signal processing and data analyses.

Prof. Dr. Pedro Oliveira Conceição Junior
Prof. Dr. Doriana Marilena D'Addona
Guest Editors

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