Volume 36 of the series Use R! pp 197215
Design of Experiments with R
 Emilio L. CanoAffiliated withDepartment of Statistics and Operations Research, Rey Juan Carlos University
 , Javier M. MoguerzaAffiliated withDepartment of Statistics and Operations Research, Rey Juan Carlos University
 , Andrés RedchukAffiliated withDepartment of Statistics and Operations Research, Rey Juan Carlos University
Abstract
Design of experiments (DoE) is one of the most important tools in the Six Sigma methodology. It is the essence of the Improve phase and the basis for the design of robust processes. An adequate use of DoE will lead to the improvement of a process, but a bad design can result in wrong conclusions and engender the opposite of the desired effect: inefficiencies, higher costs, and less competitiveness. In this chapter, we introduce the foundations of DoE and describe the essential functions in R to perform it and analyze its results. We will describe twolevel factorial designs using a representative example of how DoE should be used to achieve the improvement of a process in a Six Sigma way. The chapter is not intended as a thorough review of DoE. The idea is to introduce a simple model in an intuitive way. For more technical or advance training a number of references are given at the end of the chapter.
 Title
 Design of Experiments with R
 Book Title
 Six Sigma with R
 Book Subtitle
 Statistical Engineering for Process Improvement
 Pages
 pp 197215
 Copyright
 2012
 DOI
 10.1007/9781461436522_11
 Print ISBN
 9781461436515
 Online ISBN
 9781461436522
 Series Title
 Use R!
 Series Volume
 36
 Publisher
 Springer New York
 Copyright Holder
 Springer Science+Business Media New York
 Additional Links
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 Authors

 Emilio L. Cano ^{(1)}
 Javier M. Moguerza ^{(1)}
 Andrés Redchuk ^{(1)}
 Author Affiliations

 1. Department of Statistics and Operations Research, Rey Juan Carlos University, Madrid, Spain
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