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Construction of Efficient Fractional Factorial Mixed-Level Designs

Title: Construction of Efficient Fractional Factorial Mixed-Level Designs.
Name(s): Guo, Yong, author
Simpson, James R., professor directing thesis
Awoniyi, Samuel A., committee member
Pignatiello, Joseph J., Jr., committee member
Department of Industrial and Manufacturing Engineering, degree granting department
Florida State University, degree granting institution
Type of Resource: text
Genre: Text
Issuance: monographic
Date Issued: 2003
Publisher: Florida State University
Place of Publication: Tallahassee, Florida
Physical Form: computer
online resource
Extent: 1 online resource
Language(s): English
Abstract/Description: Mixed-level factorial designs are experimental designs whose factors have different numbers of levels. These designs are very useful in experiments involving both qualitative and quantitative factors. One design approach is to run all possible combinations of the factor levels. However, as the number of factors or factor levels increases, the number of experiments increases dramatically. As a result, research has focused on developing orthogonal or near-orthogonal fractional factorial designs. The property of design balance, that the same number of runs is performed for each factor level, has been maintained in currently proposed designs. In some cases, maintaining balance requires too many experimental runs. The objective of this thesis is to develop fractional mixed-level factorial designs with economical run size that have desirable properties associated with near-balance and near-orthogonality. Two criteria are developed to assess the degree of near-balance for comparing and constructing designs. A modified J2-optimality criterion is used for comparing design near-orthogonality. These criteria are combined to assess different design alternatives. A genetic algorithm is then used to build designs with the most desirable combination of near-balance and near-orthogonality.
Identifier: FSU_migr_etd-3911 (IID)
Submitted Note: A Thesis submitted to the Department of Industrial Engineering in partial fulfillment of the requirements for the degree of Master of Science.
Degree Awarded: Fall Semester, 2003.
Date of Defense: November 21, 2003.
Keywords: Design Of Experiments, Genetic Algorithm, Efficient Mixed-Level Designs, Balance Coefficient
Bibliography Note: Includes bibliographical references.
Advisory Committee: James R. Simpson, Professor Directing Thesis; Samuel A. Awoniyi, Committee Member; Joseph J. Pignatiello, Jr., Committee Member.
Subject(s): Industrial engineering
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Owner Institution: FSU

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Guo, Y. (2003). Construction of Efficient Fractional Factorial Mixed-Level Designs. Retrieved from