Author:
Warren Brussee

ISBN 13:
9780071433853

ISBN 10:
71433856

Edition:
1

Publisher:
McGraw-Hill

Publication Date:
2004-05-01

Format:
Paperback

Pages:
250

List Price:
$24.95

**The first plain-English guide to solving real-world problems with Six Sigma**

So you're ready to improve your processes and products and satisfy your customers through Six Sigma—but you're not looking forward to navigating complicated statistics in order to get results. Now, Warren Brussee, a veteran Six Sigma manager who helped his teams generate millions of dollars in savings, explains how to use the powerful statistical tools of Six Sigma in easy-to-understand language.

In this step-by-step guide, you get a thorough overview of the Six Sigma methodology and techniques for successful implementation, as well as a clear explanation of DMAIC—the problem solving method used by Six Sigma Greenbelts for projects and process improvements. You'll see how to plot, interpret, and validate data for a Six Sigma project. You will use Excel to make Six Sigma problem-solving calculations in a wide range of areas, from sales and marketing to manufacturing, process work, equipment design, and more. Each chapter also features a brief review of what you've learned. Plus, you get:

- A simplified form of the most common Six Sigma tools
- All the basic Six Sigma formulas and tables
- Dozens of Six Sigma statistical problem-solving case studies
- A matrix for finding the right statistical tool to meet your needs
- Basic Greenbelt training in one concise reference

Best of all, no background in statistics is required—you can start improving quality and initiating cost-saving improvements right away. With all these benefits and authoritative guidance, *Statistics for Six Sigma Made Easy* is the only reference you need to facilitate real-world application of Six Sigma tools.

**Warren Brussee **(Columbia, SC) spent 33 years at General Electric as an engineer, plant manager, and engineering manager. He has taught Six Sigma classes to both engineering and manufacturing teams.