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Digital Twin

Digital twins help organizations optimize product performance, gain visibility into the in-service life of a product, know when and where to perform predictive maintenance, and how to extend a product’s remaining useful life (RUL). The Altair digital twin integration platform blends physics- and data-driven twins to support optimization throughout the products lifecycle. We take a complete, open, and flexible approach that enables your digital transformation vision on your terms.

The Physics Twin

The physics based, simulation-driven digital twin leverages standardized, tool independent interfaces like the Functional Mock-up Interface (FMI), co-simulation methods with geometry-based 3D CAE tools, and reduced order modelling approaches to derive low fidelity models from detailed simulations.

The Data Twin

The data-driven twin uses machine learning algorithms and data science to optimize product performance. Looking at the problem through this lens allows you to get fast, real-time insights about the status of the product then make the appropriate operational adjustments to improve the life of the product and avoid failures.

Fundamental Platform

At the core of our digital twin integration platform is foundational software for executing twins in production and connecting them to real-world data in real-time. This platform provides building blocks for digital twin developers to get started fast, scale up efficiently, and continue to improve over time.

Make Better Product Decisions

Deploying a digital twin means you can make stronger, data-driven decisions about your product’s future. The detailed and in-depth information a digital twin provides empowers you to convert empirical insights to action, improving customer satisfaction through increased product reliability and improved performance. Altair provides you with the digital twin building blocks that allow you to connect disparate development disciplines and enable simulation-driven teamwork.

Electrical engineers, controls specialists, system engineers, structural designers, dynamics specialists, manufacturing experts, software developers and data scientists are provided with a new way to collaborate and gain holistic system understanding. Altair helps you understand how your product truly behaves in the real-world so you can make better decisions for your products future.

Validate Your Product Quickly and Reliably

Digital twins are especially powerful for product validation when physical prototype validation is unrealistic. Sometimes prototypes are too expensive, or operate in difficult to replicate environments, or require human intervention. In these scenarios, using a digital twin instead of a physical twin can help you understand your products behavior for substantially less investment.

Additionally, digital twins can be subjected to many more experiments at much higher frequencies. They are the cost-effective, safe, and accurate way of testing your hypotheses before committing to print for manufacturing, patent for prosthetics, grid for racing, or go for launch.

Improve Asset Performance and Efficiency

In production, digital twins improve your asset’s performance, efficiency and remaining useful life. They are a digital window into your asset’s operation, applying physics and machine learning in real time so you can gain otherwise inscrutable information into behavior then translate it directly to action. This reduces the cost of operation, avoids production stoppages from catastrophic failures, and extends the working life of individual assets.

The Altair digital twin integration platform is the only solution that can give you a window which addresses the full complexity of your assets operation: machine learning insights blended with physics simulation to help you find hidden inefficiencies and correct them.

Get the Whole Picture

While digital twin’s usefulness is unquestioned, their effective implementation can be difficult – every problem to be addressed with a digital twin needs a different approach to find the optimal solution. Altair addresses this complexity through a unique blend of physical simulation methods, data analytics, and machine learning techniques to provide a complete picture of the status of a product in the real world. Our approach can help you add virtual sensors where physical sensors are impossible, intuit maintenance needs ahead of catastrophic breakdowns, and optimize test rig performance - all using the same toolset.

We know the best way to solve your problem with the help of a digital twin, because we can see it from every angle.

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