Modeling in Industry 4.0: Key Tools and Techniques for Optimization

The advent of Industry 4.0 has revolutionized production and maintenance systems, driving unprecedented levels of efficiency, sustainability, and reliability. However, this review also considers the evolving landscape with the emergence of Industry 5.0, where human ingenuity and machine capabilities collaborate more seamlessly. This review examines the transformative tools and technologies integral to Industry 4.0, including digital twins, federated learning, agent AI, and cyber-physical systems. By synthesizing insights from peer-reviewed articles, technical reports, and case studies, the study provides a comprehensive exploration of these advanced methodologies, emphasizing their practical applications in intelligent manufacturing. The analysis highlights the significant benefits— such as enhanced operational performance, predictive maintenance, and real-time decision-making—while addressing challenges like data privacy, computational demands, and system scalability. It offers insights into solutions that can pave the way for smoother transitions into Industry 5.0. The findings aim to establish a foundation for the development of innovative, adaptive models tailored to the dynamic, interconnected ecosystems of Industry 4.0.