Topic: Machine Learning and AI in Industry Applications

The rapid advancement of Machine Learning (ML) and Artificial Intelligence (AI) is fundamentally transforming industrial applications across sectors such as manufacturing, logistics, energy, healthcare, transportation, and smart cities. The integration of ML and AI techniques into industrial processes enables improved automation, intelligent decision-making, predictive maintenance, and overall system optimization. These developments are key to enhancing efficiency, reducing operational costs, and driving innovation across complex engineering systems. However, the adoption of ML and AI techniques in industrial environments presents numerous challenges, including handling noisy and heterogeneous data, ensuring model interpretability, adapting to dynamic system changes, and addressing concerns related to safety, security, and scalability in real-world deployments.

This Special Issue aims to explore cutting-edge research, innovative methodologies, and practical solutions for applying ML and AI in various industrial domains. It will focus on both theoretical advancements and real-world implementations that tackle challenges in system modeling, optimization, fault detection, quality control, and intelligent automation. Topics of interest include, but are not limited to:

● ML Applications in Manufacturing and Smart Factories;

● AI-Driven Predictive Maintenance and Fault Diagnosis;

● Industrial Robotics and Intelligent Automation;

● Optimization Techniques for Industrial Processes;

● Data-Driven Modeling and Control in Complex Engineering Systems;

● Real-Time Monitoring and Decision Support Systems;

● Digital Twin and AI Integration for Industry 4.0;

● ML for Supply Chain and Logistics Optimization;

● AI Applications in Energy Systems and Smart Grids;

● Safety, Security, and Trustworthy AI in Industrial Applications;

● Explainable AI (XAI) in Industrial Systems;

● Human-AI Collaboration in Complex Engineering Systems;

● Industrial IoT and Edge Computing with AI Integration;

● Case Studies of AI Deployment in Industrial Environments;

● AI-Based Process Control and Adaptive Systems.

We invite academics, research students, and professionals to submit their original work. Extended conference papers with at least 50% new content are also welcome.

Machine learning (ML), artificial intelligence (AI), industrial applications, predictive maintenance, smart factories, digital twin, explainable AI (XAI), engineering systems