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  6. Surrogate model

Surrogate model

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last updated:Oct 27, 2023

アストライアーソフトウエア
アストライアーソフトウエア
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Replace CAE analysis with an AI model! It is possible to significantly reduce the time required for analysis execution.

Our company, which is engaged in AI×CAE activities, is also researching and investigating "surrogate models." As the application range of CAE expands and the pursuit of higher accuracy in simulation results becomes more prominent, the complexity of the considerations has increased, leading to issues such as excessive computation time in simulations that start from scratch. With "surrogate models," the time required for analysis execution can be significantly reduced, and utilizing pre-trained models does not require specialized knowledge, making them easy to use. 【Issues with CAE Simulation】 ■ The complexity of CAE considerations has increased, resulting in excessive computation time in simulations that start from scratch. ■ Rising costs of software and hardware, shortage of specialized engineers, and increasing education costs. ■ Maintenance costs for software are also rising. *For more details, please refer to the PDF document or feel free to contact us.

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Surrogate model

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**Addressing Issues with CAE Simulation** ■ Replacing CAE analysis (simulation) with AI models - Since AI does not perform analysis calculations from scratch, the time required for analysis execution can be significantly reduced. - Utilizing pre-trained models does not require specialized knowledge and is easy to use. *For more details, please refer to the PDF document or feel free to contact us.*

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アストライアーソフトウエア

アストライアーソフトウエア

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In the manufacturing industry, the use of three-dimensional data such as 3D CAD data is becoming widespread, but in AI, the use of two-dimensional data is mainstream, and the use of three-dimensional data is still not in sight. Our company is considering how to make better use of 3D CAD data in the manufacturing industry and contribute to improving QCD, and we are conducting research and development on three-dimensional shape recognition technology using AI and deep learning. Based on the latest AI research results, our company has successfully developed a three-dimensional AI model that can recognize three-dimensional shape data. With this groundbreaking three-dimensional AI technology, we will spread three-dimensional AI throughout the engineering chain centered on CAD, CAM, and CAE, contributing to the improvement of QCD. Moreover, three-dimensional AI is a new technology, and its potential is limitless. We will promote research and development of three-dimensional AI and spread this pioneering three-dimensional AI technology not only in the manufacturing industry but also in many other industries, contributing to the improvement of QCD.

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