Chapter

Six Sigma with R

Volume 36 of the series Use R! pp 197-215

Date:

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

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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 two-level 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.