This study explores the evolution of the Digital Factory in the context of Industry 4.0, focusing on progression through the Digital Model, Digital Shadow and Digital Twin stages. It addresses a gap in the literature by differentiating these concepts, identifying their objectives and the technologies associated with each level. For this, a systematic review of the literature was carried out, using keyword combinations to identify relevant articles in the Scopus, Web of Science and Science Direct databases. In total, 47 articles were analyzed, allowing the development of a comprehensive understanding of the Digital Factory's technological internships and enablers. The study presents a conceptual framework that illustrates the transition from the Digital Model to the Digital Shadow and the Digital Twin, highlighting its transformative impact on manufacturing processes, with capabilities such as dynamic simulations, real-time monitoring, and predictive analytics. Technologies such as sensors, IoT, simulation, and artificial intelligence are analyzed at different levels of maturity. The results offer actionable insights for decision-makers, shedding light on the capabilities, hierarchies, and taxonomies of Digital Factory stages. In addition, a modular approach is proposed, which allows flexibility to meet the specific needs of projects, while ensuring scalability. The findings also serve as a resource for the development of roadmaps and budgets, facilitating successful implementations of the Digital Factory. This study contributes in an innovative way by systematically differentiating the concepts of Digital Model, Digital Shadow and Digital Twin, advancing both the theoretical understanding and the practical application of the Digital Factory in Industry 4.0.