Real-time Implementation of Digital Twin for Robot Based Production Line

Abstract

With significant advancement in information technologies due to Industry 4.0, Digital Twin (DT) has gained increasing attention as it offers an enabling tool to realize digitally-driven and cloud-enabled production systems. The idea of DT involves the concrete realization of mirroring the physical entities in the virtual world. Given the nonlinear dynamics and uncertainty involved in production systems, the proper design, and adaptability of a DT model remain a challenge. To address this issue, the given study proposes a methodology to develop the DT model for production systems, mainly focusing on robot-based production lines. The implementation and validation of the model are carried through a case study within a Learning Factory that involves data extraction from a physical pick and place robotic production line and using it as an input for the virtual entity to determine and analyze lean process parameters such as cycle time and total lead time. The proposed study also facilitates Lean Industry 4.0 concepts. The gathered results show that DT technology not only enables remote monitoring but also improves the performance of the production system.