Digital Modelling of Robotic Arm Workcell towards Digital Twin

Wong, Julius Joe Yew (2025) Digital Modelling of Robotic Arm Workcell towards Digital Twin. Final Year Project (Bachelor), Tunku Abdul Rahman University of Management and Technology.

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Abstract

The evolution of Industry Revolution 4.0 has led to the widespread adoption of digital twins, offering enhanced monitoring, simulation, and optimization capabilities. However, existing digital twin implementations often face challenges in latency, communication inefficiencies, and inaccuracies in robotic arm movement replication. This research addresses these challenges by developing a robust digital twin framework tailored for precise robotic arm control, specifically focusing on inverse kinematics utilizing tool-center-point (TCP) positions. Implemented on the UFactory xArm6 within the 3DEXPERIENCE platform, the methodology involves creating a high-fidelity digital model, developing an optimized digital twin architecture, and performing performance evaluations. Experimental validation demonstrated exceptional positional accuracy, with an observed average deviation of approximately 10.9 μm, significantly surpassing industrial standards of ±0.5 mm. Latency assessments confirmed the framework’s compliance with ISO 23247 standards for real-time synchronization. The manual capture functionality further validated the system’s precision and practical applicability in industrial tasks such as assembly and calibration. Future research should explore dynamic payload scenarios, higher-speed operations, and multi-robot configurations, alongside implementing real-time bidirectional synchronization through 3DEXPERIENCE’s automation APIs to expand the digital twin’s capabilities and industrial relevance.