Closed-loop Digital Twins: When IoT and Simulation Converge

The use of closed-loop digital twins is becoming one of the core elements in digitalization. Implementing it and having the ability to pull live data into simulations, or in other words, of utilizing IoT data to feed digital models, is shaking up the manufacturing industry. How does it work?

With an industrial IoT solution like MindSphere, you can get live performance data from products, plants and production line machines. Then, you can analyze this data to virtually validate the performance of assets in the real world and understand how they act under various conditions. And, once you have done that, you can execute extensive testing on updated simulations to understand machines at a deeper level in a fraction of the time and cost of physical efforts.

Join us for the fourth episode of our podcast mini-series, “Future-proof with the IoT,” as our experts talk about the three different digital twins: the digital twin of the product, of production and of performance.

In this episode, learn how closed-loop digital twins can optimize your assets in production, influence your future product designs, and improve the productivity of your actual machines. Which allows you to minimize the risk of failure and maximize performance levels. The benefits of this are particularly pronounced during difficult situations, such as the global pandemic we are currently experiencing.

During the podcast, Heiko Dickas, team leader of the digitalization team at the electric motor factory Siemens Bad Neustadt, shares their positive experience using the different digital twins. “With a digital twin of the performance, we identified productivity gaps in specific areas like our mechanical prefabrication [getting] up to 25% more utilization… And we used the digital twin [of product] for optimization of existing CNC programs and had benefits up to more than 20% of reduced machining time.”