D.H. Stamatis, ASQ Quality Press, 2019, 118 pp., $42 member, $60 list (book).
Failure mode and effects analysis (FMEA) is a risk prediction and mitigation tool created to help Six Sigma teams identify and ultimately take care of problems in a process. I’ve found this tool to be indispensable to project success throughout my career, and the author brings a wealth of knowledge on this particular tool to the field in this text. This book is a great reference for project and program management specialists who want to transform the way they minimize uncertainty and mitigate risk.
The book’s introduction explains the simple reasons why problem analysis and the ability to predict those problems, and, ultimately, how to remove those problems from any system are critical to moving the needle on a global scale. The fact is the world will become increasingly competitive, and for organizations and countries to maintain a competitive status, they must always improve. Processes may never be perfect, but FMEA is a tool that will help teams get closer.
As a team designs a process, one question eventually comes up: What could go wrong? FMEA helps the team determine the best ways to predict and neutralize risks and issues. There’s a standardized process for setting up FMEA that starts with defining the scope. If the team can determine what the process must do, or even what the customer’s specifications are, it can use that information to create a roadmap to the goal. The author provides enough examples of this process to allow comprehension of its function. He offers specific definitions of each step and each tool to use when completing the plan.
The author goes further to provide solutions that apply not just to manufacturing or engineering processes, but also to industries such as healthcare and aerospace. Interestingly, governing and consulting bodies across the spectrum demonstrate that they embrace the use of FMEA as a helpful and effective method of dealing with risk. There are instructions on how to use each of the tools mentioned, and their intended uses and results. In effect, this manual serves as a complete and helpful toolkit for identifying and managing risk to a successful result.
Trevor Jordan, Orlando, FL
Matthew A. Barsalou and Joel Smith, ASQ Quality Press, 2018, 444 pp., $69.30 member, $99 list (book).
This book uses real-life scenarios to explain the practical utility of various statistical tools. For each statistical technique and test, an application-based example is given and guidance is provided on how to carry out the same using Minitab.
The hallmark of the book is its focus on statistical applications rather than harping on the math behind the techniques. The statistical methods can be understood easily by readers not ingrained in statistics. The structure and flow proceed like any textbook, and the coverage is reasonably good, addressing many important topics in statistics such as descriptive statistics, exploratory data analysis and hypothesis testing.
The examples and formulas help readers understand the efficacy of statistics from an application standpoint, but more conceptual depth on the techniques would help readers better understand the fundamental theory behind the tools. Not enough contextual background or conceptual underpinning are provided before the practical examples.
A striking feature is the Q&A at the end of each chapter. The Q&As, however, could be more exhaustive to do better justice to the coverage of the chapters.
Though the book covers the aforementioned statistical topics, there are some notable exclusions. Nonlinear regression, time series analysis and multivariate analysis of variance, for example, are conspicuous by their absence. Another glaring oversight is the lack of practice exercises for each chapter, which would help readers test their proficiency on the subject.
In view of the omissions and lacunae noted earlier, this is more of a primer on applied statistics than a full-fledged manual.
This is a good book for beginners in statistics because it gives novice readers a comprehension of the usefulness of the complex subject of statistics from an application perspective.
Sureshchandar GS, Chennai, India