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Development 2023

Put The Pieces Of The Puzzle Together Correctly During Development

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Put The Pieces Of The Puzzle Together Correctly During Development
Put The Pieces Of The Puzzle Together Correctly During Development

Video: Put The Pieces Of The Puzzle Together Correctly During Development

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Video: What Makes a Good Puzzle? | Game Maker's Toolkit 2023, January

Manufacturers are under great pressure today. You always have to bring high-quality, energy-efficient products to the market quickly and as cost-effectively as possible. There are also completely new trends on the market. Customers want intelligent products that can interact with their environment and can be customized, that include forecast functions for autonomous operation and that can also integrate software updates even when in use. Modern product behavior means the integration of mechanical properties with software, electronics and control.

If you want to survive on the market, you have to keep up with globalization. Manufacturers therefore need flexible processes that enable broad, global diversification and efficient collaboration with colleagues and suppliers around the world.

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How does Simcenter remedy this?

Most of the time the development works like this: First the concept is defined with 1D simulation tools, then a model for 3D CAE is gradually developed. Finally, a prototype is built and tested. The individual steps are often carried out by different departments. In addition, due to the large amount of time required for some 3D CAE applications, some important decisions flow into the development too late, so that much has to be improved.

We are convinced that, firstly, 3D CAE tools have to be further improved and secondly, due to the high complexity of today's products, 1D simulation, 3D CAE and tests have to be closely interlinked. If you want to find the right balance between the individual performance requirements right from the start, you need exact models as early as possible. These should be based on 1D and 3D technologies as well as test results. Only then can the multidisciplinary properties of complex products and innovative lightweight materials be successfully integrated. The basis for this should be a powerful data management system so that global, role-independent collaboration is possible.

With Simcenter we offer a portfolio that links 1D simulation, 3D CAE and tests and brings them into harmony. We bundle our simulation solutions with our know-how for measuring performance data and then apply the right analyzes to the data so that they can be used for simulations.

How does this relate to the vision of "Predictive Engineering Analytics"?

With Simcenter, manufacturers can take the step from classic verification to more efficient development based on future forecasts. This allows you to create exact models earlier - also by combining 1D and 3D simulation technologies with tests. It also provides an environment where these models can evolve when the product is slowly taking shape, or when production is already in progress and operational data is available or the product needs to be revised.

This is what the vision of "Predictive Engineering Analytics" stands for. Using this concept, a so-called digital twin can be created. It is a virtual replica of the real product with the same behavior. The twin is continuously matched with its physical counterpart and can thus predict product behavior over the entire life cycle. Such a development strategy ultimately ensures faster, more reliable innovations for complex products.


This is how the digital twin increases efficiency

Can you give an application example?

There are countless use cases for real-time and offline use for the creation of digital twin models with realistic performance. For example, real-time models are used that calculate the behavior of a vehicle on the next bend based on the current driving situation and a live view of the road conditions and can then correct it proactively. Another example is the wear forecast, which enables better maintenance planning based on the accumulation of actual operating conditions instead of theoretical assumptions.

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