Guest Editors
Prof. Mohamed Louzazni
Email: louzazni.m@ucd.ac.ma
Affiliation: National School of Applied Sciences, Chouaïb Doukkali University of El Jadida, El Jadida, 24000, Morocco
Homepage:
Research Interests: energy management and efficiency, photovoltaic optimization, control management and forecasting, IoT applications, renewable energy integration in manufacturing, intelligent control systems for energy saving, digital twins and industry 4.0, prognostics and health management, predictive maintenance, performance analysis
Assist. Prof. Tariq Kamal
Email: tariq.kamal@uwasa.fi
Affiliation: School of Technology and Innovations, Electrical Engineering, University of Vaasa, Vaasa, 65101, Finland
Homepage:
Research Interests: solar irradiation forecasting, prediction, modelling, computational physics, experimental physics, mathematical physics
Dr. Brahim Belmahdi
Email: belmahdi.brahim@gmail.com
Affiliation: Energetics Laboratory, ETEE, Faculty of Sciences, Abdelmalek Essaadi University, Tetouan, 93000, Morocco
Homepage:
Research Interests: mathematical modelling, optimisation and meta-heuristic algorithm, computational intelligence, photovoltaic & power energy, forecasting, fuel cell, GPR, radio frequency, electromagnetic and electronic, renewable energy technologies
Summary
In the face of rising energy costs, stringent environmental regulations, and the global push for sustainable development, industrial manufacturing is experiencing a transformative shift. This special issue aims to bring together innovative research and technological advancements that support energy efficiency, process optimization, predictive maintenance, and sustainable practices across industrial sectors.
The issue emphasizes the integration of Industry 4.0 technologies-such as AI, IoT, digital twins, and advanced analytics-into industrial energy and maintenance systems. These tools are pivotal in developing intelligent, adaptive, and efficient production environments. Contributions that showcase real-world applications, data-driven strategies, and case studies are particularly encouraged.
This special issue welcomes original research, reviews, and practical case studies in areas including, but not limited to:
· Energy Monitoring and Real-Time Management
· Process Optimization in Thermal and Mechanical Systems
· Predictive Maintenance and Maintenance 4.0 Solutions
· Integration of Smart Sensors, IoT, and AI for Industrial Automation
· Digital Twins for Modeling, Simulation, and Decision Making
· Sustainable Manufacturing and Life Cycle Assessment (LCA)
· Industrial Data Analytics and Fault Detection
· Renewable Energy Integration in Manufacturing Processes
· Smart Logistics and Production Planning in the Context of Industry 4.0
Keywords
energy management, industrial optimization, predictive maintenance, smart manufacturing, digital twins, industry 4.0, process efficiency, renewable energy integration, machine learning, vibration analysis
Published Papers
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