Auto OEMs have been using Computer Aided Engineering (CAE) for vehicle development and virtual validation for many years. The current changes in trend and market competition in developing electrical, autonomous and eco-friendly cars are forcing automakers to explore optimized methodologies that reduce time & cost in product development. While it is clear that CAE helps produce better quality vehicles with greater reliability and durability, there are a number of challenges in data management. These include:
EinNel’s Data-driven CAE platform
EinNel data-driven CAE solutions elevate auto industries from Simulation-Driven Engineering to Objective-Driven Engineering by utilizing the power of Big Data, Artificial Intelligence (AI) and GPU computing.
We provide Big Data solution to store, manage and to perform scalable query-driven processing of scientific data. EinNel’s CAE data lake ingests both structured and unstructured numerical simulation data from automotive Crash, Durability, NVH, Aerodynamics, and UHTM.
EinNel AI based Data driven CAE platform gives flexibility in carrying out DoE explorations, sensitivity analysis, MOO, MDO and reliability studies more efficiently and economically without any constraints to identify the optimal robust model.