Six Sigma with R Statistical Engineering for Process Improvement /

• Main Authors: Cano, Emilio L. (Author), Moguerza, Javier M. (Author), Redchuk, Andrés (Author)
• Corporate Author: SpringerLink (Online service)
• Format: Electronic eBook
• Language: English
• Published: New York, NY : Springer New York : Imprint: Springer, 2012.
• Series: Use R! ; 36
• Subjects: Statistics.; 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/Economics/Mathematical Finance/Insurance.

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...

Table of Contents:

• Part I Basics
• Six Sigma in a Nutshell
• R from the Beginning
• Part II R Tools for the Define phase
• Process Mapping with R
• Loss Function Analysis with R
• Part III R Tools for the Measure phase
• Measurement System Analysis with R
• Pareto Analysis with R
• Process Capability Analysis with R
• Part IV R Tools for the Analyze phase
• Charts with R
• Statistics and Probability with R
• Statistical Inference with R
• Part V R Tools for the Improve phase
• Design of Experiments with R
• Part VI R Tools for the Control phase
• Process Control with R
• Part VII Further and Beyond
• Other Tools and Methodologies.