Revolutionizing MEMS CAD: How AI and Fast Reduced-Order Modeling Transform Sensor Design

With the rise of artificial intelligence (AI) and large language models (LLMs) in various applications, there is growing interest in leveraging these technologies for MEMS development. A key requirement for AI-driven design is the ability to evaluate large-scale MEMS sensor configurations rapidly while considering intricate details such as manufacturing tolerances and perforation layouts. Traditional FEM-based methods, though precise, are often too slow and manually intensive, making them unsuitable for AI-assisted MEMS design workflows.

The i-ROM Modelbuilder addresses this challenge by combining high-precision FEM-based analysis with advanced reduced-order modeling (ROM) techniques tailored specifically for electrostatic MEMS, including gyroscopes, resonators, accelerometers, and micro-mirrors. With nearly seamless automated workflows - from layout sketching with library elements to full 3D designs incorporating realistic processing tolerances - i-ROM enables users to create fast-executing models that accurately predict sensor performance.

These computationally efficient models serve as a foundation for AI-assisted optimization, allowing users to explore extensive parameter spaces and identify the most promising design cases in a fraction of the time required by conventional FEM approaches. As MEMS development accelerates to meet increasing demands for high-precision sensors, AI-driven workflows powered by rapid, high-fidelity modeling will be essential in shaping the next generation of MEMS design.