Introduction
In the design and production process of electronic products, the design of PCB (Printed Circuit Board) mounting locations is one of the key factors in ensuring product stability and reliability. With the continuous advancement of AI technology, we can now use AI tools to assist the optimization of PCB mounting locations, thereby improving product performance and service life.
This article introduces how to use Altair AI tools for the optimization design of PCB mounting locations, and analyzes the resulting outcomes and technical features.
Background
As the core component of electronic products, a PCB may be exposed to different temperatures during operation, resulting in internal thermal expansion and non-uniform deformation. These non-uniform deformation behaviors can lead to solder or solder ball fatigue, which in turn causes product failures. Therefore, how to configure the PCB mounting locations to minimize deformation under operating temperatures is an important design challenge.
In this context, we can leverage AI technology to assist optimization analysis. In particular, applying Altair AI tools can greatly improve analysis efficiency and enable more accurate optimization design.
Results
In this case, we used Altair AI tools to perform a comprehensive optimization analysis of PCB mounting locations. First, using the Electronics feature in SimLab, we imported ECAD (Electronic Computer-Aided Design) data and built an equivalent material model of the PCB. A steady-state thermo-structural coupled analysis was then carried out to obtain the deformation distribution of the PCB under the original design.
Next, in HyperMesh we created a movable mounting-location variable model, and used Design Explorer to perform DOE (Design of Experiments) analysis to explore the displacement distributions of the PCB under various mounting configurations. Afterwards, we applied the clustering function of Expert AI to classify multiple DOE analysis results and identify the optimal displacement distribution pattern.
Finally, by applying these classified results in subsequent optimization analyses, we successfully achieved a 37% reduction in maximum displacement and realized a more uniform displacement distribution.
Technical Features
Fully automated data processing
Using the Electronics feature in SimLab, ECAD data can be automatically processed to generate equivalent material models, saving a significant amount of time and labor costs.
Efficient clustering
Expert AI provides powerful clustering capabilities that can effectively categorize DOE analysis results, helping engineers quickly determine the optimal design direction.
Accurate optimization design
AI-based optimization analysis enables more precise configuration of mounting locations, improving product reliability and service life.
User-friendly interface
Altair AI tools are integrated into the HyperMesh environment with a user-friendly interface and simple operations, allowing even non-AI-specialist engineers to easily get started.
Conclusion
Through this case, we can see that using Altair AI tools for the optimization design of PCB mounting locations not only significantly improves the uniformity of displacement distribution, but also effectively reduces the maximum displacement. This AI-based optimization approach provides new possibilities for electronic product design and will become an important tool in future engineering design.
We hope this sharing has been helpful to you. If you have any questions or would like to learn more about the application of AI technology in electronic product design, please feel free to contact us. Looking forward to seeing you next time!
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