Papers
1
Total Citations
53
H-Index
1
About
Liliana Stan is a prominent researcher in intelligent manufacturing and robotics, with a focus on integrating digital twin technology and web services to enhance automated production processes. Her most-cited work, "Digital Twin and web services for robotic deburring in intelligent manufacturing" (2022), has garnered 53 citations, reflecting its significant impact on advancing real-time simulation and control in manufacturing environments. Stan’s major contributions lie in bridging the gap between physical robotic systems and their digital counterparts, enabling more precise, efficient, and adaptable deburring operations—a critical step in finishing metal components. By leveraging web services, she has facilitated seamless data exchange and remote monitoring, pushing the boundaries of Industry 4.0 applications. Her research not only improves manufacturing accuracy but also reduces downtime and waste, offering practical solutions for smart factories. Stan’s work is widely recognized for its interdisciplinary approach, combining robotics, computer science, and mechanical engineering. She continues to influence the field through collaborative projects and publications that emphasize the transformative potential of digital twins in industrial automation.
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