A comparison of two-level designs to estimate all main effects and two-factor interactions

Bradley Jones, Eric D. Schoen, Douglas Montgomery

Research output: Contribution to journalArticle

5 Scopus citations

Abstract

ABSTRACT: We compare cost-efficient alternatives for the full factorial 24 design, the regular 25-1 fractional factorial design, and the regular 26-1 fractional factorial design that can fit the model consisting of all the main effects as well as all the two-factor interactions. For 4 and 5 factors we examine orthogonal arrays with 12 and 20 runs, respectively. For 6 factors we consider orthogonal arrays with 24 as well as 28 runs. We consult complete catalogs of two-level orthogonal arrays to find the ones that provide the most efficient estimation of all the effects in the model. We compare these arrays with D-optimal designs found using a coordinate exchange algorithm. The D-optimal designs are always preferable to the most efficient orthogonal arrays for fitting the full model in all the factors.

Original languageEnglish (US)
Pages (from-to)369-380
Number of pages12
JournalQuality Engineering
Volume28
Issue number4
DOIs
StatePublished - Oct 1 2016

Keywords

  • A-optimal design
  • D-optimal design
  • column balance
  • orthogonal array
  • strength 2

ASJC Scopus subject areas

  • Safety, Risk, Reliability and Quality
  • Industrial and Manufacturing Engineering

Fingerprint Dive into the research topics of 'A comparison of two-level designs to estimate all main effects and two-factor interactions'. Together they form a unique fingerprint.

  • Cite this