Charting the Future with Modeling, Simulation and Virtual Twins

The convergence of the physical and digital worlds is reshaping industries worldwide. Virtual twins underpinned by modeling and simulation play a key role in this transformation journey

By Pierre Leroux

The physical and digital worlds are rapidly converging in every facet of our life. Fortnite fans are already enjoying immersive virtual experiences blending gaming, interactivity and music performance from artists such as Ariana Grande. In traditional industries like long-haul trucking, the physical and virtual worlds are also becoming one. For instance, the Volvo SuperTruck 2 development project leverages a sophisticated virtual twin to achieve performance enhancements over the 2009 ST1 baseline. This is crucial for the trucking sector, responsible for 27% of on-road greenhouse gas emissions while representing only 1% of all the vehicles in the USA alone. In our last post of the series, we explore how virtual twins and the central role modeling and simulation (MODSIM) plays are reshaping the innovation landscape.

Building Virtual Twins

A virtual twin can be created from scratch when a new product or innovation is initiated. It can also be derived from an existing physical object, system or complex environment using technologies like sensors, 3D scanners, existing digital models, etc. The first step is to collect data from the real-world entity, capturing its size, shape, behavior, performance and characteristics. This data is then processed and fed into a 3D digital model that replicates the physical and functional aspects of the entity. Machine learning and simulation are used to refine and update this digital representation, ensuring it remains an accurate reflection of its real-world counterpart. Modeling and simulation are undeniably better together, but why are they so critical to virtual twins? Without accurate representations that follow the laws of physics from multiple domains, virtual twins cannot exist.

  1. 3D models as accurate representations: Models are the foundation for creating a virtual replica of a physical entity, such as a machine, a complex infrastructure, or even the human body. Using precise mathematical models, the real-world system’s structure, behavior and interactions are captured. See an example for a product line definition.
  2. Data-driven simulations: Models are designed and calibrated using the laws of physics from relevant domains and real-world data. This means the mathematical models are refined and fine-tuned to match real-world performance. Through this calibration process, any discrepancies between the digital and the physical systems are minimized or eliminated.
  3. Analytics: Visualizing the data related to the twin is essential for comprehension and decision-making. 3D data visualization and advanced analytics make the experience more engaging and collaborative, as both technical experts and business people access and share the insights.

Operating Virtual Twins

Virtual twins are not merely static digital replicas of physical entities. They embody dynamic, interactive entities capable of processing in real-time, predicting and planning throughout the product life cycle.

  1. Real-time processing and monitoring: Virtual twins facilitate real-time monitoring by integrating data from sensors and other sources- such as an ERP system. As a result, the virtual twin stays in sync with the current state of the physical system and is fully integrated with other essential enterprise systems. This synchronization enables operators to monitor the physical system and make informed decisions based on up-to-the-minute data.
  2. Predictive analysis and scenario planning: Modeling and simulation empower virtual twins to look ahead. They enable the virtual twin to anticipate how the physical entity will respond under various conditions or changes. This predictive capability allows organizations to explore different decision outcomes and adapt their strategies accordingly, ensuring proactive decision-making and effective response to challenges.
  3. Throughout the product life cycle and across the value chain

Historical data collected throughout the system’s lifecycle is critical for identifying long-term trends, assessing the impact of maintenance decisions, and informing upgrade or redesign efforts. Staff uses the virtual twin to simulate the impact of changes, ensuring new components or configurations will integrate seamlessly with the existing system. For example, the global auto manufacturer Renault is using a virtual twin to make informed decisions about selecting an alternative for a door bracket and ensuring its availability and compatibility with the existing car design and engineering requirements.

Why Virtual Twins Are Essential to Future Innovations

Virtual twins are not only powerful tools for operating physical systems, but also for creating value and solving future challenges faces by many industries. Here are some of the ways that virtual twins can enable innovation and transformation across various industries.

  1. Always-on services and personalization: Virtual twins allow companies to monitor individual systems and deliver personalizations and recommendations based on real-time data. That leads to greater customer satisfaction and brand loyalty. For example, IKEA is offering twins of your living space to generate new business opportunities by offering their Swedish-design furniture and accessories in a personalized way.  
  2. Sustainability and Environmental Impact: Virtual twins can be used to model the environmental impact of products and processes. This helps organizations make more sustainable choices by optimizing resource usage and minimizing waste.
  3. Continuous Improvement: Virtual twins allow organizations to continuously improve their processes. By analyzing data from virtual twins, organizations identify areas for enhancement and innovation, leading to ongoing improvements in performance and quality of service. For instance, TESLA gathers operational information from all TESLA vehicles and deliver regular updates over the air.
  4. Collaboration and Communication: Virtual twins facilitate collaboration among teams and stakeholders. They provide a shared virtual environment where different parties collaborate, visualize, discuss designs, plans and strategies. This is particularly important in complex projects such as construction and infrastructure development where aligning the different stakeholders determine on-time completion and on-budget success.

Conclusion

The convergence of the physical and digital worlds is reshaping industries worldwide. Virtual twins underpinned by modeling and simulation play a key role in this transformation journey. As accurate digital 3D representations that follow the laws of physics from multiple domains, they will drive innovation throughout their lifecycle and enabling continuous improvement and collaboration, shaping a more sustainable future for all of us.