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Design for Six Sigma Statistics: 59 Tools for Diagnosing and Solving Problems in DFFS Initiatives, by Andrew Sleeper
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In today’s competitive environment, companies can no longer produce goods and services that are merely good with low defect levels, they have to be near-perfect. Design for Six Sigma Statistics is a rigorous mathematical roadmap to help companies reach this goal. As the sixth book in the Six Sigma operations series, this comprehensive book goes beyond an introduction to the statistical tools and methods found in most books but contains expert case studies, equations and step by step MINTAB instruction for performing: DFSS Design of Experiments, Measuring Process Capability, Statistical Tolerancing in DFSS and DFSS Techniques within the Supply Chain for Improved Results. The aim is to help you better diagnosis and root out potential problems before your product or service is even launched.
- Sales Rank: #461518 in Books
- Published on: 2005-12-26
- Ingredients: Example Ingredients
- Original language: English
- Number of items: 1
- Dimensions: 9.10" h x 2.60" w x 6.50" l, 3.07 pounds
- Binding: Hardcover
- 854 pages
From the Back Cover
THE STATISTICAL TOOL NECESSARY TO IDENTIFY AND SOLVE ANY DFSS PROBLEM
Design for Six Sigma Statistics meticulously details 59 mathematical procedures for executing DFSS programs, isolating and identifying problems, and solving them before the actual product launch. More than an introduction to statistical concepts and methods, this comprehensive resource offers real-world case studies and step-by-step MINTAB instruction for performing:
- DFSS Design of Experiments
- Measuring Process Capability
- Statistical Tolerancing in DFSS
- DFSS Techniques within the supply chain
THE STATISTICAL TOOLS YOU NEED TO MAXIMIZE DFSS:
The Design for Six Sigma Process * Defining Product Requirements * Making Decisions with Data * Conducting Efficient Experiments * Predicting New Product Quality * Controlling New Product Quality
Survival in today's competitive environment demands goods and services that truly approximate perfection -- which means pinpointing and solving problems before a product launches. Written by a Six Sigma practitioner with more than two decades of DFSS experience, Design for Six Sigma Statistics provides a detailed, goal-focused roadmap.
Design for Six Sigma Statistics shows quality professionals how to execute advanced mathematical procedures specifically aimed at implementing, fine-tuning, or maximizing DFSS projects to yield optimal results.
For virtually every instance and situation, readers are shown how to select and use appropriate mathematical methods to meet the challenges of today's engineering design for quality. The author covers mathematical tools for planning, interpreting, measuring, correcting, and anticipating product performance and manufacturing parameters. Examples, equations, and MINTAB screen shots facilitate progress through every step toward efficient, effective, and measurable results. In one comprehensive resource, readers will have the formulas they need to fully understand:
- Robust Engineering Concepts
- Failure Mode and Effects Analysis
- Gap Analysis: Audits and Metrics
- Design of Experiments
With Andrew Sleeper's Design for Six Sigma Statistics, quality professionals will have the highly specialized, problem-solving mathematical procedures necessary to create products and services that can compete and succeed in today's marketplace.
About the Author
Andrew Sleeper is a DFSS expert and General Manager of Successful Statistics, LLC. He has worked with product development teams for 22 years as an engineer, statistician, project manager, Six Sigma Black Belt, and consultant. Mr. Sleeper holds degrees in electrical engineering and statistics, and is a licensed Professional Engineer. A senior member of the American Society for Quality, he is certified by ASQ as a Quality Manager, Reliability Engineer, and Quality Engineer, and has provided over 1,000 hours of instruction in countries around the world. His client list includes Anheuser-Busch, Intier Automotive Seating, New Belgium Brewing Company, and Ingersoll-Rand.
Most helpful customer reviews
8 of 8 people found the following review helpful.
The New "king of the hill in reference books"
By Bad Seed Bob
Well folks, clear off some space on your desk and make sure that space is right next to your PC as this is the new "king".
As a Sr Engineer that has worked with suppliers for a number of years, this book is the new "one stop shop". Andy proactively admits that this is an engineer's guide first and math guide second, but his due diligence to the math is better than some "math" books on the topic. This is now the only book I keep at work. If more depth is needed, I bust out Montgomery's DOE book or his SQC book. If more depth is needed in DFSS, I open Yang and El-Haik's book. What most people miss is the overlap with tolerance analysis and to support this one, I turn to Creveling's tolerance design book and for the Dim and Tol stuff I turn to Drakes book titled, Dim and Tol Handbook written by the best in class for each chapter.
Now, back to Mr. Sleeper's work of magic. First, his examples are world class, well written, they flow, and when you read them, you can imagine yourself in that persons shoes. His humor is sprinkled just enough to peak a smile and the gem is left for last. If you have any of the other texts mentioned above, skip right to chapter 11 and watch the mystery unfold. Here Andy takes us down the path of true Design Simulation. Here we talk stackups, tolerances, cpks, six sigma expectations, DOEs, and Monte carlo. All design engineers out there need to buy this book and skip right to chapter 11 and for all those folks doing pure RSS stackups, you are being too optimistic on normality occurrences my friends. Read chapter 11 and see a safer time zero assumption. Normality is nice, but don't assume it at time zero.
So, what should Mr. Sleeper write next: skip the quality tools Andy, all the old folks already write about them. Take us down the path of truly integrated design simulation. Tell the publisher you want a best in class bible on Design Simulation. To do this, follow Mr. Drake's idea and let the content experts write a chapter. You have the vision, guide them.....Take chapter 11 and make it a separate textbook. Lets talk more about Monte carlo and the cross correlation pitfalls or not. Lets talk summarized research on best known dist for types of data, uniform, lognormal, etc. Then lets discuss the tweakable dist you stats geeks out there love to talk about and their pitfalls. I want to know more on truncated normals in @Risk and Crystalball, are they still normal then? We can also add the discussion on the hidden math that people never do....yeah the time zero partial diff to tell us what range to set the DOE +1 and -1 limits at.
So, to all you dorks like me that cant wait for books like this, here is the deal.
Content of this book. A- as depth can't possibly be there on all topics. Flow of book and depth needed to get your job done A+. Style points and readability points, A+ Humor B+, the fact that the publisher was too na?ve to realize that a book this thick will never stay open when reading it, absolute F. Do your benchmarking you idiots. Oh that's right they did, as they are the same ones that biffed up Yang and El-Haik's book as well. It's bad enough that they should reprint and make book larger. Book needs at least the size of Montgomery's SQC book or Drakes Dim and Tol handbook.
So, content A, book size lending itself as a true handbook, F. No-one can give this thing a 5 star rating just on that fact alone. Andy, declare a "mis-print" and demand justice
3 of 3 people found the following review helpful.
Well written, highly recommended
By Perry M. Gill
I just got this on loan from my company library. I think I may have to pony up the cash up to put it in my personal library.
Right from the first few chapters, I knew I was going to love this book. Mr. Sleeper has an oustanding attention to detail. He even includes a chapter on how you should chart your data to better analyze it.
Even with the attention to detail, he writes in a precise manner. It just made sense more than any Six Sigma book I've read yet, and that is what matters. I just wish he published this book a long time ago.
2 of 2 people found the following review helpful.
Reactive -vs- Proactive
By Mr. Barry T. Walker
I admittedly have not completed the full book, as it is thick. However I do find that the narrative focuses on the reactive rather than the proactive tools needed for DFSS. For example almost all the examples given in section 2 talk about an existing system or process and there doesn't seem to be any design examples and how the stats are used to solve the design problems. I therefore think the book is more about Six Sigma than DFSS.
Barry
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