CAE - A Strategy for a Large Scale Virtual Vehicle Engineering Factory

For many years, the computer aided math model has been the foundation for lowering cost and reducing time to market for many manufacturing industries. The automotive industry applies a variety of tools and methods to evaluate the expected vehicle performance to a forever expanding set of requirements. These mathematical predictions of performance are then repeated for both a set of design cycles and a multitude of vehicles in the product portfolio.

This paper presents a CAE perspective of the unique problems of the large scale virtual vehicle engineering factory and a set of solutions. Different strategies to create the various complex math models required are explored. These strategies include using COTS FEA pre-processers, producing FEA models internal to the CAD tools, as well as custom built tools, macros and process automation tools. The goal is to be able to produce a set of coordinated FEA models tailored to each domain of analysis that are both high quality and generate results fast enough to impact the design cycle. The process which will allow a team to produce a large volume of models very efficiently is described.