Introduction to Engineering Statistics and Six Sigma: Statistical Quality Control and Design of Experiments and Systems

Part I: Statistical Quality Control

Chapter List

Chapter 2: Quality Control and Six Sigma
Chapter 3: Define Phase and Strategy
Chapter 4: Measure Phase and Statistical Charting
Chapter 5: Analyze Phase
Chapter 6: Improve or Design Phase
Chapter 7: Control or Verify Phase
Chapter 8: Advanced SQC Methods
Chapter 9: SQC Case Studies
Chapter 10: SQC Theory

1.1 Purpose of this Book

In this chapter, six sigma is defined as a method for problem solving. It is perhaps true that the main benefits of six sigma are: (1) the method slows people down when they solve problems, preventing them from prematurely jumping to poor recommendations that lose money; and (2) six sigma forces people to evaluate quantitatively and carefully their proposed recommendations. These evaluations can aid by encouraging adoption of project results and in the assignment of credit to participants. The main goal of this book is to encourage readers to increase their use of six sigma and its associated "sub-methods." Many of these sub-methods fall under the headings "statistical quality control" (SQC) and "design of experiments" (DOE), which, in turn, are associated with systems engineering and statistics.

"Experts" often complain that opportunities to use these methods are being missed. Former General Electric CEO Jack Welch, e.g., wrote that six sigma is relevant in any type of organization from finance to manufacturing to healthcare. When there are "routine, relatively simple, repetitive tasks," six sigma can help improve performance, or if there are "large, complex projects," six sigma can help them go right the first...

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