Six Sigma Professor

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 

Rating: 4 / 5

I just got this on loan from my company library. I think I’ll have to pony up the cash to put in my personal library.

From the first chapters, I knew I was going to love this book. Mr. Sleeper has a slope are attention to detail. It even includes a chapter on how to map their data to analyze them better.

Despite the attention to detail, who writes in a precise manner. It only makes sense more than any Six Sigma book I’ve read, and that’s what matters. I just wish this book published long ago.
Rating: 5 / 5

I certainly have not finished the whole book, because it is thick. However, I find the story focuses on reactive rather than proactive tools to DFSS. For example almost all the examples cited in Article 2 speaks of an existing system or process and there seems to be examples of design and how to use statistics to solve design problems. Therefore, I think the book is more about Six Sigma DFSS.

Barry
Rating: 1 / 5

This text is fast becoming the best desktop reference guide for troubleshooting. The combination of tools and examples easy to understand in detail all about the calculation method is quickly becoming my # 1 this text goto to issues related to problem solving and statistical strategies.
Rating: 5 / 5

Sad that a reviewer to give a star. He has his points, because the book is not specifically for DFSS and can be used for the SS. For me, the principles are the same and it is a question of implementation.

Very systematic book highlights 59 tools to use.

I am particularly impressed with the DOE section. I have not finished this book yet. What struck me is that Andrew makes it easy to understand. Use examples and stories to be interesting and fun, so I’m left wanting to read more! The stories use real life examples (quite real) and it is easy to relate the tools necessary for effective implementation. I read a couple books DOE and still lost. This book is good! i probably still need other books to be more advanced, but this will be a very good reference and builds a solid foundation.
Rating: 5 / 5