The potential of Digital Twin (DT) technology to revolutionize industry by enabling virtual simulations of physical systems in real-time has garnered significant attention in recent years. However, current DT research is facing several challenges such as being highly conceptual and lacking practical understanding, lack of remote accessibility, and high cost in implementation. To solve these challenges, this thesis proposes a cloud-based DT framework that enables real-time monitoring and control for a legacy robotic assembly system. The framework features by the cloud infrastructure, web-based DT environment, and open-access tools. A proof-of-concept system is developed with demonstrated scenes of job status monitoring and remote feedback control on a web browser. To further understand and characterize the synchrony status between the physical system and its digital twin, a computer vision (YOLO) -based approach is developed to quantitatively study the delay effect across the assembly cycle. Overall, this thesis contributes to a practical and efficient solution for integrating DT technology into a legacy system, which potentially can enable better operational decisions in manufacturing.