Digital Twins Supported by Adaptive Simulation-Optimization Techniques

Traditional simulations rely on fixed assumptions, but in dynamic industrial environments, static models fall short. That’s where Adaptive Simulation-Optimization Models and Digital Twins come into play!

🚀 Imagine a system where a 𝗗𝗶𝗴𝗶𝘁𝗮𝗹 𝗧𝘄𝗶𝗻 𝗰𝗼𝗻𝘁𝗶𝗻𝘂𝗼𝘂𝘀𝗹𝘆 𝗰𝗼𝗹𝗹𝗲𝗰𝘁𝘀 𝗿𝗲𝗮𝗹-𝘄𝗼𝗿𝗹𝗱 𝗰𝗼𝗻𝘀𝘁𝗿𝗮𝗶𝗻𝘁𝘀—machine status, energy consumption, process variables—and feeds them into an 𝗔𝗱𝗮𝗽𝘁𝗶𝘃𝗲 𝗦𝗶𝗺𝘂𝗹𝗮𝘁𝗶𝗼𝗻-𝗢𝗽𝘁𝗶𝗺𝗶𝘇𝗮𝘁𝗶𝗼𝗻 𝗠𝗼𝗱𝗲𝗹. But it doesn’t stop there.

🔄 𝗧𝘄𝗼-𝘄𝗮𝘆 𝗶𝗻𝘁𝗲𝗿𝗮𝗰𝘁𝗶𝗼𝗻: If a new constraint is introduced in the digital environment, the optimization model instantly 𝗿𝗲𝗰𝗮𝗹𝗰𝘂𝗹𝗮𝘁𝗲𝘀 𝗮𝗻𝗱 𝗿𝗲-𝗼𝗽𝘁𝗶𝗺𝗶𝘇𝗲𝘀 to align with real-world conditions. This simulation-optimization framework was developed using The AnyLogic Company, enabling dynamic real-time adjustments.

𝗛𝗼𝘄 𝗱𝗼𝗲𝘀 𝘁𝗵𝗶𝘀 𝘄𝗼𝗿𝗸 𝗶𝗻 𝗮𝗰𝘁𝗶𝗼𝗻?

In our Homogenizing Line Simulation project, this approach is applied to optimize steel processing:

✅ 𝗟𝗶𝘃𝗲 𝘁𝗿𝗮𝗰𝗸𝗶𝗻𝗴 𝗼𝗳 𝗺𝗮𝗰𝗵𝗶𝗻𝗲 𝗽𝗲𝗿𝗳𝗼𝗿𝗺𝗮𝗻𝗰𝗲 𝗮𝗻𝗱 𝗲𝗻𝗲𝗿𝗴𝘆 𝘂𝘀𝗮𝗴𝗲

✅ 𝗜𝗺𝗺𝗲𝗱𝗶𝗮𝘁𝗲 𝗿𝗲-𝗼𝗽𝘁𝗶𝗺𝗶𝘇𝗮𝘁𝗶𝗼𝗻 𝘄𝗵𝗲𝗻 𝗰𝗼𝗻𝘀𝘁𝗿𝗮𝗶𝗻𝘁𝘀 𝗰𝗵𝗮𝗻𝗴𝗲

✅ 𝗥𝗲𝗮𝗹-𝘁𝗶𝗺𝗲 𝗱𝗲𝗰𝗶𝘀𝗶𝗼𝗻-𝗺𝗮𝗸𝗶𝗻𝗴 𝗳𝗼𝗿 𝗲𝗳𝗳𝗶𝗰𝗶𝗲𝗻𝗰𝘆 𝗮𝗻𝗱 𝗾𝘂𝗮𝗹𝗶𝘁𝘆

💡 The result?

⚡ Smarter, more adaptive operations

📈 Optimized performance in real time

🏭 A game-changer for manufacturing, logistics, and energy systems

How do you see real-time adaptive simulation shaping the future of your industry? Let’s discuss in the comments! 👇