In this research work, we examine thoroughly the application of Digital Twin (DT) technology for scheduling management automation in manufacturing systems. It starts with a DT definitional context as a continuously updated, real-time virtual representation of a physical object or system that interacts with, and is constantly synchronized with, the physical counterpart. The advances of DT in manufacturing are analyzed through a systematic literature review focusing on its development, application domains, and methodological trends. Particular emphasis was placed on areas where DT is contributing significantly, such as production optimization, quality assurance, healthcare, autonomous systems, and supply chain analytics. In addition, the paper discusses DT vis-à-vis Manufacturing Execution Systems and analyzes overlaps and gaps of their synergistic and distinct interrelations in intelligent manufacturing. This work presents some last suggestions in the report, integrating engineering analysis with those of scaling up and implementing real-world systems in support of adaptive and predictive scheduling for Industry 4.0.