A Review on Digital Twin Technology in Robotics - Rohit Raval; Rishabh Makwana; Darshan Bhalodia; Heena Patel (International Journal of Manufacturing and Production Engineering, 2026)
Digital Twin (DT) technology has emerged as a transformative concept in robotics and automation, enabling virtual representation of physical systems, real-time monitoring, and performance optimization. This review explores the foundations of Digital Twin, its integration in robotic systems, key enabling technologies, applications, current challenges, and future research directions. The paper concludes by highlighting how Digital Twin transforms design, control, prediction, and human-robot collaboration.Digital Twin technology is transforming the field of robotics by enabling the development of real-time virtual representations of physical robotic systems. Through the integration of advanced sensors, data analytics, artificial intelligence, and simulation tools, Digital Twins create a synchronized connection between physical robots and their digital counterparts. This capability significantly enhances production planning and control by enabling predictive analysis, process optimization, and efficient resource allocation. In manufacturing environments, particularly within evolving casting trends, Digital Twins support quality improvement, defect reduction, and real-time process monitoring, thereby increasing operational reliability.For small and medium-sized enterprises (SMEs), Digital Twin technology offers opportunities to improve productivity, reduce downtime, and optimize cost management without extensive physical prototyping. Although challenges such as high initial investment, data integration complexity, and cybersecurity concerns remain, the adoption of Digital Twins in robotics demonstrates strong potential to enhance smart manufacturing practices. This review explores the architecture, enabling technologies, industrial applications, and future research directions of Digital Twin technology, highlighting its growing significance in modern robotic systems and manufacturing ecosystems.the integration of Digital Twin technology with cloud computing and Industrial Internet of Things (IIoT) platforms enables scalable and data-driven decision-making across distributed manufacturing systems. Its adoption is expected to accelerate the digital transformation of robotics-driven industries, fostering sustainable growth, improved competitiveness, and enhanced operational agility in both large enterprises and SMEs.
Keywords: Casting trend; Production planning and control; SMEs; physical system human-robot collaboration; virtual representation