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Submission: On August 07 via manual from US — Scanned from DE
Submission: On August 07 via manual from US — Scanned from DE
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LIVE WEBINAR SERIES
SMARTER INNOVATION WITH DESIGN OF EXPERIMENTS
Tuesday, August 22 | 2:00-3:00pm ET
Thursday, August 24 | 2:00-3:00pm ET
Wednesday, August 30 | 2:00-3:00pm ET
Experimental design is a technique that enables scientists and engineers to
efficiently assess the effect of multiple inputs (factors), on measures of
performance (responses). Compared to one-factor-at-a-time, trial-and-error
approaches, a well-designed experiment can provide clear results while
dramatically reducing the required amount of testing.
In this series we’ll learn how to effectively implement (or expand) the use of
design of experiments at your organization. We’ll learn a little more about the
history of design of experiments (DOE), its benefits and the numerous ways it
can help expand your understanding and positively impact your organization.
During the series, we’ll learn:
* The origins of DOE, how it has evolved, and new innovations on the horizon.
* The benefits of using statistically designed experiments.
* How to design efficient experiments despite real-world constraints like
process or budget limitations.
* How to implement “Easy DOE” and how it can help you understand cause and
effect better (and faster).
* Tips, tricks, and best practices for effectively using designed experiments
in your organization.
Each session lasts 30 minutes, followed by 15 minutes of live Q&A with our
experts.
SESSION 1: DOE: PAST, PRESENT, AND FUTURE
Date: Tuesday, August 22
Time: 2:00 - 3:00 p.m. ET
Presenter: Bradley Jones
Location: Online (Zoom)
Registration: Free
Design of experiments is one of the most strategic contributions to enable us to
learn faster from data and understand cause and effect.
In this session, JMP’s Distinguished Research Fellow, Dr. Bradley Jones will
discuss the origins of design of experiments, how it evolved and its
immeasurable contributions to statistics and data discovery.
During this session we will learn:
* About the pioneers of the design of experiments methodology(past, present,
and future).
* The evolution of experimental design, including inflection points and
advancements that have helped shape the methodology.
* How fast (or slow) DOE has been adopted across various industries and
application areas.
* Tools that make DOE easier to implement.
* How DOE has changed the world and how exciting new innovations can make it
even better.
--------------------------------------------------------------------------------
SESSION 2: DESIGN OF EXPERIMENTS MADE EASY
Date: Thusday, August 24
Time: 2:00 - 3:00 p.m. ET
Presenter: Peter Polito
Location: Online (Zoom)
Registration: Free
Sometimes the hardest part of conducting a designed experiment is getting
started. Few of us – particularly when we’re under a deadline – have the time or
energy to learn the new concepts and jargon needed to be effective with DOE.
What we really need is an “easy button” for shortening the learning curve.
Good news! Whether you’re brand new to DOE or been using it for years, JMP now
has a guided platform that makes designing, running and analyzing experiments
consistently… yes, essentially an “Easy Button” for DOE.
During this session we’ll learn:
* The basics of DOE.
* The importance of conducting consistent experiments.
* How the new Easy DOE platform in JMP 17 provides a guided workflow that
allows you to conceptualize, design, run, analyze, and report out the results
in no time flat.
--------------------------------------------------------------------------------
SESSION 3: UNLOCKING THE POWER OF DESIGNED EXPERIMENTS
Date: Wednesday, August 30
Time: 2:00 - 3:00 p.m. ET
Presenter: Mike Anderson
Location: Online (Zoom)
Registration: Free
When it comes to efficiently collecting experimental information, there is no
better method than designed experiments. Still, they have limitations. Due to
their incredible efficiency, and relatively small data sets, it can be difficult
to create a robust predictive model from a designed experiment without
compromising the data set.
A recent development has identified a novel way to create robust models from
these data sets by stringing together cutting-edge modeling techniques and best
practices to create an enhanced solution.
In this session we’ll learn:
* The importance of cross validation and why it’s hard to do with designed
experiments.
* An exciting new capability you can apply to your designed experiments… and
even your historical data.
* How to leverage historical data along with new techniques to create a
holistic experimental design process.
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Session 1: August 22 | 2:00 - 3:00 pm ET
Session 1: August 22 | 2:00 - 3:00 pm ET
Session 2: August 24 | 2:00 - 3:00 pm ET
Session 2: August 24 | 2:00 - 3:00 pm ET
Session 3: August 30 | 2:00 - 3:00 pm ET
Session 3: August 30 | 2:00 - 3:00 pm ET
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×
BRADLEY JONES
JMP DISTINGUISHED RESEARCH FELLOW
Bradley Jones, PhD, is the Distinguished Research Fellow in JMP, where he is
responsible for the development of new methods in design of experiments (DOE).
He built the JMP Custom Designer, a general and powerful tool for generating
optimal experimental designs. He holds a patent on the use of DOE for minimizing
registration errors in the manufacture of laminated circuit boards and is the
inventor of the prediction profile plot for interactive exploration of multiple
input and output response surfaces.
Before joining SAS in 1997, he was the principal statistician at The MathWorks
Inc., where he designed and implemented the MATLAB Statistics Toolbox. He was
Chief Scientist and a founding partner of Catalyst Inc., a company created to
support the use of computer-aided DOE in industry.
Jones is the 2012 recipient of the Statistics in Chemistry award from the
American Statistical Association (ASA). In both 2009 and 2011, he received the
American Society for Quality’s Brumbaugh Award for the paper making the largest
contribution to industrial quality control. He also won the 2010 Lloyd S. Nelson
Award for the article having the greatest immediate impact to practitioners.
Jones is the former Editor-in-Chief of the Journal of Quality Technology and a
Fellow of the ASA. He holds a master’s degree in statistics from Florida State
University and a PhD in applied economic sciences from the University of
Antwerp, Belgium.
×
PETER POLITO
SENIOR SYSTEMS ENGINEER
Peter Polito is a geologist with experience in mechanical and electrical
engineering. Polito helps customers solve complex problems using data analysis
and visualization. Prior to joining JMP, he spent more than 10 years as an
Engineering Research Scientist and Lab Director at the Flemings Research Lab at
The University of Texas at Austin, where he and his staff worked with scientists
worldwide to answer scientific questions through experimental design and
discovery. His research has been published in numerous professional journals and
featured in popular media, including The Science Show on Australian Broadcasting
Corporation National Radio and the UT Jackson School’s Fueling the Future.
Before joining SAS, Polito founded the men’s grooming company The Bearded
Savant, where he used JMP design of experiments capabilities to help formulate
grooming products.
×
MICHAEL ANDERSON
SYSTEMS ENGINEER, JMP STATISTICAL DISCOVERY
Michael Anderson is a Systems Engineer at JMP Statistical Discovery LLC, a
wholly owned subsidiary of SAS, which creates interactive and highly visual
statistical software designed for scientists and engineers. In his current role,
Anderson enjoys helping customers find hidden insights in data that result in
quantifiable improvement. Before joining SAS, he worked in a variety of roles in
high-tech manufacturing, encompassing measurement statistics, Lean Six Sigma,
and cost and defect reduction. Anderson holds a PhD in Materials Chemistry from
the University of Oregon and has achieved certification as a Lean Six Sigma
Black Belt.
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