4-Hour Virtual Seminar: Modeling and Optimizing Process/Product Behavior Using Design of Experiments
Speaker: Steven Wachs
Speaker Designation: Vice President & Principal Statistician, Integral Concepts, Inc.
Speaker: Steven Wachs
Speaker Designation: Vice President & Principal Statistician, Integral Concepts, Inc.
Experimentation is frequently performed using trial-and-error approaches which are extremely inefficient and rarely lead to optimal solutions. Furthermore, when it’s desired to understand the effect of multiple variables on an outcome (response), “one-factor-at-a-time” trials are often performed. Not only is this approach inefficient, it inhibits the ability to understand and model how multiple variables interact to jointly affect a response. Statistically based Design of Experiments provides a methodology for optimally developing process understanding via experimentation.
Participants gain a solid understanding of important concepts and methods in statistically based experimentation. Successful experiments allow the development of predictive models for the optimization of product designs or manufacturing processes. Several practical examples and case studies are presented to illustrate the application of technical concepts. This webinar will prepare you to begin designing and conducting experiments. You will also learn how to analyze the data from experiments to understand significant effects and develop predictive models utilized to optimize process behavior.
Design of Experiments has numerous applications, including:
The objective is to provide participants with an overview of the analytical tools and methods necessary to:
Steven Wachs has 25 years of wide-ranging industry experience in both technical and management positions. He has worked as a statistician at Ford Motor Company where he has extensive experience in the development of statistical models, reliability analysis, designed experimentation, and statistical process control.
Mr. Wachs is currently a Principal Statistician at Integral Concepts, Inc. where he assists manufacturers in the application of statistical methods to reduce variation and improve quality and productivity. He also possesses expertise in the application of reliability methods to achieve robust and reliable products as well as estimate and reduce warranty. Mr. Wachs regularly speaks at industry conferences and provides workshops in industrial statistical methods worldwide.
He has an M.A. in Applied Statistics from the University of Michigan, an M.B.A, Katz Graduate School of Business from the University of Pittsburgh, 1992, and a B.S., Mechanical Engineering from the University of Michigan.
