Artificial Intelligence

How to Utilize Parametric Design in Engineering Product Development Today, engineers must balance performance, manufacturability, cost, reliability, weight, thermal behavior, and regulatory requirements simultaneously to achieve optimal design. Parametric design offers a systematic approach to exploring these trade-offs by defining design variables and automatically evaluating the impact of changes on performance. Evolving from a useful

Using AI and Machine Learning to Improve Design Optimization Modern engineering teams face increasing pressure to deliver optimized, high-performance products faster while managing growing model complexity and data volume. Traditional optimization workflows often struggle to scale due to limitations in data handling, computational cost, and integration challenges. Ansys optiSLang AI+ addresses these issues by embedding

What Are Surrogate Models in Engineering Simulation? Engineering teams rely on simulation to make design decisions earlier and with greater confidence. As model fidelity increases, however, simulation cost and turnaround time often become limiting factors. Surrogate models address this challenge by enabling faster exploration of complex design spaces without sacrificing engineering rigor. By allowing engineers