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ATI's Practical Design of Experiments course
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Summary:
This two-day course will enable the participant to plan
the most efficient experiment or test which will result in a
statistically defensible conclusion of the test objectives. It
will show how properly designed tests are easily analyzed
and prepared for presentation in a report or paper. Examples
and exercises related to various NASA satellite programs
will be included.
Many companies are reporting significant savings and
increased productivity from their engineering, process
control and R&D professionals. These companies apply
statistical methods and statistically-designed experiments to
their critical manufacturing processes, product designs, and
laboratory experiments. Multifactor experimentation will be
shown as increasing efficiencies, improving product quality,
and decreasing costs. This first course in experimental
design will start you into statistical planning before you
actually start taking data and will guide you to perform
hands-on analysis of your results immediately after
completing the last experimental run. You will learn how to
design practical full factorial and fractional factorial
experiments. You will learn how to systematically
manipulate many variables simultaneously to discover the
few major factors affecting performance and to develop a
mathematical model of the actual instruments. You will
perform statistical analysis using the modern statistical
software called JMP from SAS Institute. At the end of this
course, participants will be able to design experiments and
analyze them on their own desktop computers.
Factorial Design for Choosing Input Values in Experimentation: Generating Informative Data for System Identification
Instructor:
What you will learn:
- How to design full and fractional factorial
experiments.
- Gather data from hands-on experiments while
simultaneously manipulating many variables.
- Analyze statistical significant testing from
hands-on exercises.
- Acquire a working knowledge of the statistical
software JMP.
Course Outline:
- Survey of Statistical Concepts.
- Introduction to Design of Experiments.
- Designing Full and Fractional Factorials.
- Hands-on Exercise: Statapult Distance Experiment using
full factorial.
- Data preparation and analysis of Experimental Data.
- Verification of Model: Collect data, analyze mean and
standard deviation.
- Hands-on Experiment: One-Half Fractional Factorial,
verify prediction.
- Hands-on Experiment: One-Fourth Fractional Factorial,
verify prediction.
- Screening Experiments (Trebuchet).
- Advanced designs, Methods of Steepest Ascent, Central
Composite Design.
- Some recent uses of DOE.
- Summary.
Tuition:
Tuition for this two-day course is $1150 per person at one of our scheduled public courses. Onsite pricing is available. Please call us at 410-956-8805 or send an email to ati@aticourses.com.
Register Now Without Obligation
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Dr. Manny Uy is a member of the Principal
Professional Staff at The Johns Hopkins
University Applied Physics Laboratory
(JHU/APL). Previously, he was with
General Electric Company, where he
practiced Design of Experiments on many
manufacturing processes and product
development projects. He is currently
working on space environmental
monitors, reliability and failure
analysis, and testing of modern instruments for
Homeland Security. He earned a Ph.D. in physical
chemistry from Case-Western Reserve University and
was a postdoctoral fellow at Rice University and the Free
University of Brussels. He has published over 150
papers and holds over 10 patents. At the JHU/APL, he
has continued to teach courses in the Design and
Analysis of Experiments and in Data Mining and
Experimental Analysis using SAS/JMP.
