Recent Advances in Design of Experiments by Dr. Douglas Montgomery Cost $300 per person 3 hours
The last 20 years have seen many important and fundamental changes in how experiments can be designed. These changes have come about because of increases in computing power and the development of efficient algorithms for implementing optimal design methodology. This enables engineers, scientists and other that use designed experiments to create designs that are customized to the specific characteristics of their problem and not have to rely on tables of libraries of standard design from textbooks or software. This 3-hr webinar gives a basic overview of optimal design methodology and demonstrates how it is implemented in modern computer software. Examples of how this approach can be used to create custom designs are shown for a variety of situations, including cases where there are constraints on the region of experimentation, restrictions on the number of runs that can be made, or non-standard models that need to be fit to the results. Some specific new developments in DOX that have origins in optimal design methodology that will be discuss include no-confounding fractional factorial designs, designs that include one-step screening and response surface modeling, and designs for computer experiments.
Dr Montgomery is Regents’ Professor of Industrial Engineering and Statistics at ASU. He holds a BSIE, MS and Ph.D. degrees from Virginia Polytechnic Institute. Professor Montgomery’s professional interests are in industrial statistics, including design of experiments, quality control, applications of linear models, and time series analysis and forecasting. He also has interests in operations research and statistical methods applied to modeling and analyzing manufacturing systems. He has lectured extensively throughout the Americas, Europe and the Far East. He has authored 13 textbooks and edited or co-authored 7 other research books or edited volumes. His research papers have appeared in many journals.
To purchase this webinar contact with link above or call 303 655 3051.