Implementation of a Digital Twin in an Industrial Production Line: Real-Time Visualization and Monitoring

Oualid Karim, Houda Lahyani (), Ahmad AL Khatib and Abdelfettah Sedqui
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Oualid Karim: Innovative Technologies Laboratory, National School of Applied Sciences of Tangier, Abdelmalek Essaâdi University, Department of Industrial and Electrical Engineering
Houda Lahyani: Innovative Technologies Laboratory, National School of Applied Sciences of Tangier, Abdelmalek Essaâdi University, Department of Industrial and Electrical Engineering
Ahmad AL Khatib: ECAM-Louis de Broglie, Department of Industrial and Mechanical Engineering, Material and Mechanics Laboratory
Abdelfettah Sedqui: Innovative Technologies Laboratory, National School of Applied Sciences of Tangier, Abdelmalek Essaâdi University, Department of Industrial and Electrical Engineering

A chapter in Technological Innovations for Sustainable Development, 2025, pp 197-208 from Springer

Abstract: Abstract Industry 4.0 has revolutionized industrial innovation, driving companies to digitize their manufacturing processes. This transformation integrates technologies such as IoT, AI, cloud computing, system integration, cyber security, big data, and digital twins, enhancing efficiency, quality, and responsiveness across the value chain. Among these innovations, digital twins (DTs) have gained significant attention from both industry and academia. A DT is a dynamic digital model that mirrors a physical asset or system, enabling real-time monitoring and synchronization with its real-world counterpart. This research first introduces a general DT architecture, defining its key modules within an industrial environment. Based on this architecture, an innovative DT for real-time monitoring of industrial processes is developed. It integrates an interactive dashboard within Grafana, allowing operators to efficiently monitor and control production systems. Node-RED serves as the integration platform, connecting PLCs via OPC UA, ensuring real-time data acquisition. This data is stored in Influx DB, a time-series database optimized for fast processing and real-time analysis, enabling better decision-making and process optimization. Additionally, the project incorporates FlexSim, a powerful commercial simulation tool that creates a real-time virtual representation of the production process. This digital model allows users to explore various operational scenarios, assess performance predictions, and anticipate possible disruptions, thereby improving overall efficiency in industrial settings. By combining real-time data acquisition, visualization, and simulation, this research contributes to the evolution of smart manufacturing, offering a comprehensive tool for process optimization and decision-making.

Keywords: Digital twin; Simulation; visualization; real-time; performance (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/978-3-032-06725-8_17

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