Using genetic algorithms to generate mixture-process experimental designs involving control and noise variables

Journal of Quality Technology

Volumn 37, Issue 1, 2005, Pages 60-74

  Goldfarb, Heidi B ^a,e   Borror, Connie M ^b,f   Montgomery, Douglas C ^c,f   Anderson Cook, Christine M ^d,g  

^a Dial Corporation   (United States)

^b UNIVERSITY OF ILLINOIS AT URBANA CHAMPAIGN   (United States)

^c ARIZONA STATE UNIVERSITY   (United States)

^d LOS ALAMOS NATIONAL LABORATORY   (United States)

^e Research and Development   (United States)

^f Department of General Engineering ^*  (United States)

^g Statistical Sciences Group   (United States)

Author keywords

Genetic Algorithm; Mixture Process Experiments; Noise Variables; Optimal Designs; Response Surface Methodology; Robust Parameter Design

Indexed keywords

EVALUATION; PARAMETER ESTIMATION; PREDICTIVE CONTROL SYSTEMS; PROCESS CONTROL; PRODUCT DESIGN; ROBUSTNESS (CONTROL SYSTEMS); STATISTICAL METHODS;

MIXTURE-PROCESS EXPERIMENTS; NOISE VARIABLES; OPTIMAL DESIGNS; RESPONSE SURFACE METHODOLOGY; ROBUST PARAMETER DESIGN;

GENETIC ALGORITHMS;

EID: 18144412011     PISSN: 00224065     EISSN: None     Source Type: Journal    
DOI: 10.1080/00224065.2005.11980301     Document Type: Article

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