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This paper presents a systematic approach for designing an experiment in situations where expensive and time consuming computer simulations are used to evaluate product characteristics. In the presence of many design parameters, the critical step is to find the best possible experimental set up with minimum number of simulations. Usually in such situations, designers use their intuition and experience to carry out a number of simulation runs and choose the design that gives better performance. This intuitive approach can be considerably improved by using statistical methods. “Classical experimental designs” were compared with “space filling designs” in terms of their results and requirements. A typical clutch booster bracket is used as an example to demonstrate the methodology.