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Expert insights from Professor William Q. Meeker, part 4

In the final post of this series, we see the last bits of JMP Chief Data Scientist Chris Gotwalt’s interview with world-renowned reliability expert, William Q. Meeker, Professor of Statistics and Distinguished Professor of Liberal Arts at Iowa State University. The first post touched on “proactive reliability” and how machine learning, IoT, and Industry 4.0 have implications for maintenance and improved reliability. The second post explored overlapping disciplines and foundational contributions of statistics, as well as the evolution of statistics education. The third post examined the growing importance of Bayesian methods.

The interview complemented the plenary talk Bill recorded for the 2021 Discovery Summit Japan. This blog series features sections of Chris’ interview to shine light on Bill’s many contributions to statistics, as well as two recent books he has co-authored: Achieving Product Reliability: A Key to Business Success, with Necip Doganaksoy and Gerald J. Hahn; and the second edition of Statistical Methods for Reliability Data, which Bill co-authored with Luis A. Escobar and Francis G. Pascual. We are pleased to offer the first chapter of Achieving Product Reliability.  

We have had a long and fruitful collaboration with Bill, adding new methods for reliability analysis into JMP software. We are grateful for his many contributions to statistics and working with us to incorporate new and better methods to enable better product reliability.

In the first clip, Bill reveals his motivation for writing the book on statistical intervals.

Here, Bill shares an interesting exchange he had with W. Edwards Deming.   

You can see the entire interview, as well as Bill’s plenary talk at Discovery Summit Japan from November 2021, here in the JMP Community.

Last Modified: Jun 27, 2022 5:33 PM
Comments
gail_massari
Community Manager

Bill describes advantage of Bayesian statistics, Bayes methods, including when using non-informative priors with small amount of info., as one often does when evaluating reliability.  His interesting example was and included in the first edition of his Reliability book.  His recent 2021 Edition 2 of Statistical Methods for Reliability Dataincludes more Bayesian examples.

DeepakRam
Staff

I recall the SAS Warranty Solution leveraged a lot of the findings from the Wu-Meeker paper. Early Detection of Reliability Problems Using Information From Warranty Databases

anne_milley
Staff

Thanks, Deepak and Gail, for sharing these links. Bill's contributions have indeed been leveraged far and wide for the benefit of many.