Douglas C. Montgomery

Douglas C. Montgomery is Regent's Professor of Industrial Engineering, and ASU Foundation Professor of Engineering at Arizona State University. He was the John M. Fluke Distinguished Professor of Engineering, Director of Industrial Engineering and Professor of Mechanical Engineering at the University of Washington in Seattle. He was a Professor of Industrial and Systems Engineering at the Georgia Institute of Technology. He holds BSIE, MS and Ph.D. degrees from Virginia Tech. He has industrial experience with Union Carbide Corporation and Eli Lilly and Company and extensive consulting experience. Dr. Montgomery's professional interests focus on industrial statistics, including design of experiments, quality and reliability engineering, applications of linear models, and time series analysis and forecasting. The Office of Naval Research, the National Science Foundation, NASA, the Department of Defense, and private industry have sponsored his research. He has supervised 69 doctoral dissertations and over 40 MS theses and MS Statistics Projects. Dr. Montgomery is an author of thirteen books that have been published in over 50 English language editions, including Design and Analysis of Experiments, 10th edition (2020), and Response Surface Methodology, 4th edition (2016, with R. H. Myers and C.M. Anderson-Cook). He is an author of over 275 archival journal papers. He is currently one of the Chief Editors of Quality and Reliability Engineering International and is a former Editor of the Journal of Quality Technology. He is an Honorary Member of the American Society for Quality, a Fellow of the American Statistical Association, a Fellow of the Royal Statistical Society, a Fellow of the Institute of Industrial Engineers, an Elected Member of the International Statistical Institute and an Academician of the International Association for Quality. His recognition awards include the Shewhart Medal, the Distinguished Service Medal, the William G. Hunter Award, the Brumbaugh Award, the Lloyd S. Nelson Award, and the Shewell Award (twice) from the American Society for Quality, the Deming Lecture Award from the American Statistical Association, the George Box Medal from ENBIS (European Network for Business and Industrial Statistics), the Greenfield Medal from the Royal Statistical Society and the Ellis R. Ott Award. He was named an ASU Outstanding Doctoral Mentor in 2004 and a member of the team that received the ASU President’s Award for Innovation in 2015.

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Random Models, Nested and Split-plot Designs (Coursera)

Many experiments involve factors whose levels are chosen at random. A well-know situation is the study of measurement systems to determine their capability. This course presents the design and analysis of these types of experiments, including modern methods for estimating the components of variability in these systems. The [...]

Factorial and Fractional Factorial Designs (Coursera)

Many experiments in engineering, science and business involve several factors. This course is an introduction to these types of multifactor experiments. The appropriate experimental strategy for these situations is based on the factorial design, a type of experiment where factors are varied together. This course focuses [...]

Experimental Design Basics (Coursera)

This is a basic course in designing experiments and analyzing the resulting data. The course objective is to learn how to plan, design and conduct experiments efficiently and effectively, and analyze the resulting data to obtain objective conclusions. Both design and statistical analysis issues are discussed. Opportunities to use [...]

Response Surfaces, Mixtures, and Model Building (Coursera)

Factorial experiments are often used in factor screening.; that is, identify the subset of factors in a process or system that are of primary important to the response. Once the set of important factors are identified interest then usually turns to optimization; that is, what levels of the important [...]