Solving Industrial Production Scheduling Challenges in the Era of Industry 4.0 and Green Manufacturing

The evolution of production scheduling in the context of Industry 4.0 and green manufacturing has become a focal point in contemporary industrial research. Efficient scheduling, essential for optimal resource utilization and cost-effectiveness, faces new challenges due to the digital revolution and the green industry paradigm. This study conducts a comprehensive analysis of existing literature on scheduling problems, incorporating the dual perspectives of Industry 4.0 and green production. The research delves into diverse problem formulations and solution approaches, ranging from mathematical programming techniques to heuristic methods and machine learning concepts. The review reveals a scarcity of studies addressing the complexities arising from the integration of Industry 4.0 technologies and ecological considerations in production scheduling. Bridging this gap is crucial, urging further research at the intersection of Industry 4.0 and sustainable manufacturing practices. The study emphasizes the significance of addressing these challenges, considering the complexities of real-world scheduling scenarios, where practical problems involve operations ranging from thousands to hundreds of thousands. By exploring advanced solutions, encompassing machine learning, constraint programming, and metaheuristic methods, the research underscores the need for continued exploration and development of robust strategies applicable to large-scale, practical settings. This interdisciplinary approach is pivotal in shaping the future of industrial scheduling, ensuring efficiency, sustainability, and resilience in the face of evolving technological landscapes and environmental imperatives.