Six Sigma has arisen in the last two decades as a breakthrough Quality Management Methodology. With Six Sigma, we are solving problems and improving processes using as a basis one of the most powerful tools of human development: the scientific method. For the analysis of data, Six Sigma requires the use of statistical software, being R an Open Source option that fulfills this requirement. R is a software system that includes a programming language widely used in academic and research departments. Nowadays, it is becoming a real alternative within corporate environments.
The aim of this book is to show how R can be used as the software tool in the development of Six Sigma projects. The book includes a gentle introduction to Six Sigma and a variety of examples showing how to use R within real situations. It has been conceived as a self contained piece. Therefore, it is addressed not only to Six Sigma practitioners, but also to professionals trying to initiate themselves in this management methodology. The book may be used as a text book as well.
Author(s): Emilio L. Cano, Javier M. Moguerza, Andrés Redchuk (auth.)
Series: Use R! 36
Edition: 1
Publisher: Springer-Verlag New York
Year: 2012
Language: English
Pages: 284
Tags: Statistics, general; Statistics for Life Sciences, Medicine, Health Sciences; Statistics and Computing/Statistics Programs; Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences; Statistics for Business/Econo
Front Matter....Pages i-xxx
Front Matter....Pages 1-1
Six Sigma in a Nutshell....Pages 3-13
R from the Beginning....Pages 15-47
Front Matter....Pages 49-49
Process Mapping with R....Pages 51-61
Loss Function Analysis with R....Pages 63-75
Front Matter....Pages 77-77
Measurement System Analysis with R....Pages 79-90
Pareto Analysis with R....Pages 91-100
Process Capability Analysis with R....Pages 101-112
Front Matter....Pages 113-113
Charts with R....Pages 115-139
Statistics and Probability with R....Pages 141-165
Statistical Inference with R....Pages 167-193
Front Matter....Pages 195-195
Design of Experiments with R....Pages 197-215
Front Matter....Pages 217-217
Process Control with R....Pages 219-238
Front Matter....Pages 239-239
Other Tools and Methodologies....Pages 241-249
Back Matter....Pages 251-284
