Space-filling designs for computer experiments: A review

ABSTRACT

Improving the quality of a product/process using a computer simulator is a much less expensive option than the real physical testing. However, simulation using computationally intensive computer models can be time consuming and, therefore, directly doing the optimization on the computer simulator can be infeasible. Experimental design and statistical modeling techniques can be used to overcome this problem. This article reviews experimental designs known as space-filling designs that are suitable for computer simulations. In the article, a special emphasis is given for a recently developed space-filling design called maximum projection design. Its advantages are illustrated using a simulation conducted for optimizing a milling process.

KEYWORDS:

• design of experiments
• kriging
• optimization
• simulation

About the author

V. Roshan Joseph is a professor in the Stewart School of Industrial and Systems Engineering at Georgia Tech. He holds a Ph.D. degree in statistics from the University of Michigan, Ann Arbor. His research focuses on engineering statistics. He is the author of more than 50 papers and has won two best paper awards. He is a fellow of the American Statistical Association and a recipient of National Science Foundation’s CAREER Award. He is an Associate Editor of the Journal of the American Statistical Association and Technometrics and past Associate Editor or editorial board member of Operations Research, Naval Research Logistics, and Journal of Quality Technology.

Acknowledgments

I would like to thank Evren Gul for running the simulations on the Production Module software.

Funding

This research is supported by the U.S. Department of Energy Advanced Scientific Computing Research Award ERKJ259, Innovative Manufacturing Initiative Award DE-EE0005762/000, and a U.S. National Science Foundation grant CMMI-1266025.