The format includes discussions of actual experiments that have involved the course methods and workshops where participants practice the methods using  PC-based DOE software.

Course Outline:
Day 1

• Review of Design of Experiments I 
  • Generic Strategy of Experimentation
  • Methods for Reducing Uncertainty in Experimental Results
  • Common Multi-factor Designs
• Data Issues in the Analysis of Designed Experiments
  • Assumptions of the Model:  Common Violations
  • Benefits of Data Transformation
  • Box-Cox Method for Selecting the Transformation
  • Analysis of Binary Responses
• Response Surface Designs
  • Choice of Designs for Assessing Response Curvature
  • Box-Behnken & Central Composite Designs
  • Building 2nd-Order Models
  • Contour, Wireframe, and Overlaid Contour Plots
  • Multi-response Optimization
  • Framing the MRO problem, Common MRO Challenges
  • Desirability Functions
  • Use of DOE software for MRO

Day 2

• DOE for "Robust Design"
  • The Robust Design Problem
  • Noise & Control Factors
  • Designs to Address "Robustness"
  • Signal-to-Noise Ratios & Alternative Methods of Analysis
• Final DOE Workshop:  Optimizing a Multi-response, Multi-factor Process
  • A team-based competition with limited budget and time

Who Should Attend:
Engineers, scientists, continuous improvement specialists, quality assurance personnel, or other technical professionals who are responsible for product, process, or test development, improvement, or control activities.

Prerequisites:
Course participants should have completed DOE I or the equivalent. 

How They Will Benefit:
By the end of the course, participants will have gained:

• The ability to independently design & analyze a multi-factor experiment;
• Knowledge of experiment designs and analyses for achieving system "robustness:"
• Experience designing and analyzing experiments for optimizing the multiple performance features of a product or process;
• In-class experience applying the course methods to experiments they will design and analyze in order to improve a realistic, multi-variable process;
• Knowledge of how to use the PC-based statistical software systems, JMP 7 or Minitab 15, for the design and analysis of optimization experiments.

Cost:
Two-day course (Day 2 of 2) PLEASE RESISTER FOR THIS CLASS THROUGH DAY 1 OF 2 Posting
Cost: $300 TOTAL per student: includes class, bound presentation, and lunch for both days

Instructor Bio:  Don Lewis Ph.D.
Don Lewis is Principal, Lewis Consulting LLC, whose mission is to enable clients to improve their competitive performance through effective application of proven quantitative decision-making methodologies.  Since establishing his consulting practice in 1986, Don has trained and mentored over five thousand technical professionals to apply quantitative methods, such as Statistical Process Control and Design of Experiments, in their project work.  His consulting experience accrues from 50+ organizations across a diverse group of industries, including biosciences.  Clients have achieved significant performance improvement, including proprietary breakthroughs, as a result of implementing his services. 

Recently, as a Lead Instructor in Motorola University’s Digital Six Sigma Black Belt training program, Don has trained over two hundred and fifty Motorola Black Belts throughout the U.S., Europe, and Asia.  Since 2003 his Northwest Lean Six Sigma clients have saved over $16 million in project work completed in conjunction with his training programs.  He is an Adjunct Professor in both the Department of Management of Science & Technology at the OGI School of Science & Engineering in Portland, Oregon and the Atkinson Graduate School of Management at Willamette University.  Don is also a chapter author of the recently published "Encyclopedia of Statistics in Quality and Reliability."  He received his B.A. in mathematics from Claremont McKenna College and Ph.D. in biostatistics from the University of North Carolina at Chapel Hill.  Don is an ASQ Certified Six Sigma Black Belt. 

PLEASE RESISTER FOR THIS CLASS THROUGH DAY 1 OF 2 Posting