New Frontiers in the Design of Experiments


Kenett, Ron S.; Steinberg, David M.   (2006, ASQ)   KPA Ltd., Raanana, Israel; Tel Aviv University, Tel Aviv, Israel

Quality Progress    Vol. 39    No. 8
QICID: 20658    August 2006    pp. 61-65
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Article Abstract

Statistically designed experiments enable businesses to reduce time to market while achieving quality product performance that is critical to survival and success. R.A. Fisher first introduced them in the early 20th century to evaluate the results of small sample agricultural experiments. Others soon applied his methods to the industrial environment, presenting new opportunities and challenges. Today, computer simulators have become a popular way to run these experiments. New issues with computer-simulated experiments have led to the development of new statistical methods known as the design and analysis of computer experiments (DACE). Computer simulator experiments are faster and cheaper than physical experiments, but since conclusions and recommendations refer to the actual physical system, the simulator data is usually augmented with laboratory or field data and expert opinion. A number of integrative methods have been recently proposed, most of which use Bayesian statistical models and correlation function structures to explicitly combine data from various sources.


Computer models,Design of experiments (DOE),Simulations,Statistical experimental design (SED)

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