A Proof-of-Concept Digital Twin for Real-Time Simulation: Leveraging a Model-Based Systems Engineering Approach

Abstract

This paper presents a proof-of-concept digital twin designed to enhance industrial process monitoring and maintenance through real-time and bidirectional communication. The integrated approach combines a physical twin—constructed using LEGO ${}^{\unicode {0x00A9}} $ Spike Prime kits and multiple Raspberry Pi 4 microcontrollers—with a digital twin modeled in FlexSim discrete-event simulation software package. Data is continuously synchronized via the MQTT protocol, allowing the digital twin to accurately mirror key operational parameters such as object sorting status, conveyor speed, and splitter position. The system leverages Model-Based Systems Engineering (MBSE) techniques, implemented with Capella and the Arcadia methodology, to support a robust design and integration of physical and digital components. Experimental scenarios, including normal operation and simulated malfunctions, demonstrate the system’s ability to trigger corrective actions and provide valuable insights for predictive maintenance. The results confirm that such a modular digital twin approach can improve real-time simulation, fault detection, and operational efficiency in industrial applications.

Keywords

• Digital twin
• real-time communication
• model-based systems engineering
• industrial automation
• cyber-physical systems