Using a digital twin in the design process has enabled engineers to refine product designs through models and simulations. Most digital twin systems are centered around modeling the operation of a product, but Altair has a different perspective that incorporates two separate digital twins.
Altair’s Digital Twin Concept
Altair takes a two-pronged approach to implementing the digital twin. The first prong uses operational product data to help teams predict performance and improve the design of future products. The second prong consists of physics-based simulations that mimic actual product behavior. By incorporating both simulated and operational data, design teams using Altair’s digital twin software can extend the operating life of a new product and avoid catastrophic product failure. As a result, they can offer customers unmatched product performance.
Managing Product Operational Data: The Data Twin
In today’s connected world, more companies are taking advantage of the internet of things (IoT) to monitor their products in operational environments. As a result, the amount of data that sensors generate has steadily increased. That volume of data can overwhelm many design teams, who then may not use it to the fullest potential. But if teams could manage and visualize that data, they could make informed operating decisions for products working in the field. For example, they could schedule maintenance before a failure is predicted to occur. Engineers could also apply this information to improve the design of new products in the pipeline.
Altair’s software offers the tools necessary to build a digital data twin based on data gathered from sensors and real-world product operation. First, engineers can use Monarch to gather data from various sources and manipulate and clean that data to suit their needs. Once the data is ready, Knowledge Studio can apply artificial intelligence (AI) and machine learning (ML), allowing users to perform predictive analysis. Then engineering managers can visualize the streaming data in real time using Panopticon, and make decisions based on that data.
The combined power of Altair’s Monarch, Knowledge Studio, and Panopticon enables team members to gather, refine, and visualize real-world data. Then they can make informed decisions about existing product operations. These software solutions also allow companies to apply this same operational data to the design of future products. The end result is a new product with a longer lifecycle and lower risk of failure.
Running Production Simulations: The Physics Twin
Designing advanced products that meet requirements across a variety of engineering disciplines is a complicated task. For example, as the electronics of a product are optimized, the heat they generate may pose another problem. To improve the optimization process and the time required for optimization, engineers can turn to simulations and system models.
Altair’s HyperWorks products allow design teams to develop digital twins using physics-based simulations. These simulations provide design and optimization capability for structural mechanics, fluid flow, electromagnetics, system design, and manufacturing processes. As engineers build their physics digital twin, Altair’s software tests the product designs against the requirements. Engineers can also simulate large-scale systems using Altair’s Activate software.
Integrating the Data Twin and Physics Twin
Using a digital data twin or a digital physics twin alone helps the engineering team evaluate current or future product designs. But combining the capabilities of both digital twins using Altair’s software boosts productivity further. Organizations that make full use of large amounts of data and physics-based simulations gain new engineering insights for product development.
Individually, the physics twin and the data twin enable a new paradigm in product engineering. The physics twin can illustrate ideal product operation based on simulated product models. The data twin can further improve the accuracy of these simulation models through the application of real-world data.
Integrating the two twins takes the benefits further. Using the combined capabilities of the physics and data twins, engineering teams can predict how their products will operate in real-world environments even before they are deployed. They can use the operational data from the data twin to refine the responses of the physics twin. In this way, companies can calibrate their simulations against that real-world data. Then their engineers can build a physics digital twin that is nearly identical to the final functional product.
Altair’s SmartWorks provides engineering design teams with a native cloud platform for combining physics and data twins. Using the data from real sensors and simulation models, engineers can use SmartWorks to apply data analytics, AI, and the IoT to improve product development processes.
Altair’s suite of software solutions provides engineers at all levels of an organization with access to tools that add value to the design process. These tools enable real-time viewing of operational data that AI/ML has processed. They allow product designers to evaluate existing designs and devise potential improvements for future designs. Physics-based models and simulations let engineers simplify the design process for next-generation products.
When design teams take full advantage of Altair’s digital twin solutions, combining the data twin and physics twin enables a new scale of engineering analysis. Engineering teams will find that applying Altair’s digital twin concept can enhance the processes of creating new products and improving existing ones.