Digital Twin Platform for Optimized Product Performance | Altair
Altair’s definition of a Digital Twin is a digital representation of a product that supports decision making during the development phase, helps to optimize the performance of the product during operation and provides insights for closing the feedback loop in the sense of continuous development, either driven by simulation models or historical data.

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.

SYSTEMS OF SYSTEMS

Smarter Ways for Optimizing Product Performance

Explore the building blocks that form Altair’s Digital Twin Platform.

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A Digital Twin of a Robot that is representing the physical effects, structural performance and dynamic behavior.

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.

Physics Twin Examples
A Digital Twin of a Robot that is representing its behavior through the aggregation of the operational data of the motors, drives, sensors and control units.

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.

Data Twin Examples
The Altair digital twin integration platform is foundational software to create Systems of Systems models and connecting them to real-world data. Different digital twins are connected through the integration platform that combines: CAE Models, reduced order modeling, Functional Mockup Interface (FMU), Machine Learning, Data Analytics and IoT.

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.

Connect Digital Twins

How can digital twins help your product development and operation?

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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.

A digital twin of a machine is used for virtual testing and helps to validate the product quickly and reliably.

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.

Digital Twin Infographic representing a digital twin integration platform connecting all the assets in operation: machine learning insights blended with physics simulation to help you find hidden inefficiencies and correct them.

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.

Different digital twins derived from physical simulation data and operational measured data are connected through an integration platform combining: CAE, reduced order modelling, Functional Mockup Interface (FMU), Machine Learning, Data Analytics and IoT.

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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Featured Resources

From Know How to Know Why! - Digital Twin Design Process opening new horizons for Investment Casting

Development based on experience often means that you know what happens, but you don‘t know why! The use of Digital Twins in development helps convert empirical knowledge into physical. This creates a valid basis for optimization and caters the need for rising performance, lightweight or cost requirements.
Watch the webinar recording "From Know How to Know Why!" - Digital Twin Design Process opening new horizons for Investment Casting presented jointly with Feinguss Blank, one of the leading investment casting foundries in Europe and the EICF.
In this webinar recording you will learn how Feinguss Blank applies smart cast processes to address development challenges. The presentation will:

  • demonstrate the application of simulation-driven design and additive manufacturing to drive next generation lightweight designs through an investment casting process.
  • show an integrated workflow on simulation-driven-design and manufacturability, to obtain lightweight parts in a single environment.
  • feature how to apply this digital twin platform for investment casting, sand-casting and within additive manufacturing or hybrid manufacturing processes.

Webinars

Applying large-scale 3D Printing and Digital Twin technologies to the factory floor

ABB, MX3D, and Altair demonstrate how Industry 4.0 will deliver customized manufacturing equipment.

Webinars

Ford Enhances Manufacturing Efficiency

Sheet metal stamping is fundamental to the automotive manufacturing industry. A vast array of different tool, die, and process combinations are employed to create an equally diverse array of components. Traditionally, identifying the optimum approach for each part has been a labor intensive and time-consuming task that requires engineering teams with high levels of skill and experience. This case study demonstrates how Altair Knowledge Studio, a general-purpose data analytics tool, can enable engineering managers and data analysts to deliver clear and quantifiable benefits in the manufacturing domain. For Ford, this is reflected in dramatic improvements in the speed and efficiency with which the best possible sheet metal stamping processes were selected.

Customer Stories, Use Cases

Socomec

France-based Socomec’s specialty is providing low-voltage energy installations, from equipment to monitoring, where energy is critical – robust and ultra-reliable solutions for buildings like datacenters, solar plants, utilities, and hospitals. Using Altair SmartWorks™, has enabled Socomec to implement increasingly sophisticated power setups and services, offering their customers the up-to-the-minute technology they need to power their businesses.

Customer Stories, Customer Testimonials
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