Abstract
A CAE simulation process was developed to quantify the variability of vehicle attributes such as safety, durability, vehicle dynamics, NVH and weight. The process was integrated with the Ford multi-function optimization (MFO) tool — MOVE (Multi-Function Optimization Visualization Environments) in order to facilitate the robust design of vehicles, systems and components. The statistics of vehicle attribute responses are computed given the statistics of the design parameters. The response surface approximation was used to simplify the input and output relationships. A variety of statistical distributions can be selected to match the statistics of the design parameters which are continuous or discrete. In addition to parametric statistical analysis methods, nonparametric statistical analysis approaches were also available. To achieve robust design, a series of robust targets were used in the search for the optimized design. The method also ranks the contribution of individual design parameter variability to a specific vehicle attribute variability. The ranking was used to set up a tolerance strategy for reducing the variability and the total cost of the product. The integrated MFO/robust design process has been applied in several Ford vehicle programs for robust and reliable optimized design. A couple of applications are described here.
Recommended Citation
L. D. Liaw et al., "An Mdo-Compatible Method for Robust Design of Vehicles, Systems, and Components," 7th AIAA/USAF/NASA/ISSMO Symposium on Multidisciplinary Analysis and Optimization, pp. 609 - 619, American Institute of Aeronautics and Astronautics, Jan 1998.
The definitive version is available at https://doi.org/10.2514/6.1998-4786
Department(s)
Mechanical and Aerospace Engineering
Document Type
Article - Conference proceedings
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2024 American Institute of Aeronautics and Astronautics, All rights reserved.
Publication Date
01 Jan 1998
