Digital Twins

A New Era of Operational Efficiency

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Transform Operations with Real-Time Digital Twins 

Digital twins are virtual representations of physical assets, systems, or processes that operate in sync with their real-world counterparts. Powered by Concurrent Real-Time’s advanced real-time computing platforms, digital twin technology provides a foundation for smarter, more responsive operations across industries such as manufacturing, energy, transportation, and aerospace. 

By integrating live data streams with high-fidelity models, digital twins offer continuous visibility into system behavior, performance, and anomalies helping teams move from reactive troubleshooting to proactive control. Whether simulating system states, predicting outcomes, or validating operational changes before deployment, digital twins provide a powerful tool for reducing downtime, increasing efficiency, and supporting data-driven decisions. 

Concurrent’s real-time infrastructure built on RedHawk Linux, SIMulation Workbench (SimWB), and our iHawk computing platforms ensures deterministic response, low-latency data handling, and compatibility with complex modeling environments. Combined with our engineering services and integration capabilities, we enable customers to develop scalable, domain-specific digital twin architectures. 

Key benefits of Concurrent-powered digital twins: 

  • Real-time synchronization with physical assets 
  • Support for Hardware-in-the-Loop and Model-in-the-Loop testing 
  • Predictive analytics based on real-time and historical data 
  • Scalable deployment across distributed environments 

Key Capabilities of Concurrent-Powered Digital Twins 

Concurrent Real-Time’s digital twin solutions are built on a foundation of real-time performance, precise synchronization, and robust modeling tools. These capabilities enable organizations to bridge the gap between physical systems and their virtual counterparts unlocking a wide range of operational advantages. From continuous monitoring and predictive analytics to simulation and collaborative decision-making, our platform delivers the core functionality needed to support critical, data-driven operations across complex environments. 

Digital twins continuously ingest and reflect real-world data, providing immediate insight into system performance and asset health. By eliminating data lag, organizations gain real-time operational awareness for monitoring equipment status, identifying anomalies, and adjusting controls in the moment. 

Leveraging both historical trends and live data, digital twins facilitate early detection of patterns that could indicate future issues. This allows for condition-based maintenance and process optimization. When paired with machine learning or AI models, digital twins can evolve over time improving accuracy, identifying new correlations, and adapting to changing conditions automatically. 

Before implementing changes in production environments, digital twins allow engineers to model and test various scenarios including failure modes, configuration changes, and environmental variables. This helps de-risk decisions and accelerates innovation by enabling safe, low-cost experimentation. 

By replacing physical trials with digital simulation, organizations can reduce material waste, energy usage, and labor requirements. Accurate system models also improve planning, reduce asset downtime, and extend equipment life—resulting in measurable cost savings and more sustainable practices. 

Digital twins provide a shared operational picture accessible across teams and geographic locations. Engineers, operators, and stakeholders can collaborate using the same model and real-time data improving communication, accelerating troubleshooting, and enhancing strategic alignment across departments.