Abstract
When investigating many continuous factors under experi-mental cost constraints, an experimenter often selects a screening design from among a variety of published options. This article introduces a novel design selection methodology based on decision trees that identifies which screening design option minimizes the total expected cost of a multistage experiment under model uncertainty. The methodology is illustrated by an example in which a set of traditional and recently published experimental designs are considered for the screening of six potential factors.
Original language | English (US) |
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Pages (from-to) | 139-153 |
Number of pages | 15 |
Journal | Quality Engineering |
Volume | 26 |
Issue number | 2 |
DOIs | |
State | Published - 2014 |
Keywords
- Monte Carlo simulation
- decision trees
- design of experiments
- orthogonal arrays
- response surface methods
ASJC Scopus subject areas
- Safety, Risk, Reliability and Quality
- Industrial and Manufacturing Engineering