Robust Optimization and Tolerance Design

Course Description:
ROTD is specifically designed to meet the analytical needs of those individuals
working within FDA regulated industries. Robust Optimization and Tolerance
Design presents the methods and practices associated with designing and
optimizing products and processes and to discuss tolerance design methods
to protect product quality and clinical benefits. Presentation of the course material
is designed for 16 hours of instruction.

Attendees:
Robust Optimization and Tolerance Design is required for all scientists, engineers
and quality professionals who actively work on all aspects of discovery, product and
process development where the goal is to characterize, optimize and improve product
and process performance.

  

Course Objectives:
Upon completion of the course the participants will be able to:

  1. Learn and apply the principles of robust product design.
  2. Design experiments appropriate for the information of interest.
  3. Use and apply the structures of orthogonal arrays for product and process
    development and problem solving.
  4. Ensure the experimental design is efficient.
  5. Use regression techniques in order to analyze the results and make
    process/product improvements.
  6. Optimize the response at its most robust condition.
  7. Tolerance the factors and responses.
  8. Use JMP software to design and analyze experiments.

Prerequisites:  Engineering Statistics and Data Analysis and Design of Experiments
are recommended prerequisites for this course.

Detailed Course Outline:

Distribution and Tolerance Design Foundations
System, parameter and tolerance design
Tolerance design methods
                                                
DOE Review and Robust Design Principles
Eight robust design principles
                         
DOE Using Custom Designs
Custom designs
Strategies to minimize experimental size
Adding covariate and uncontrolled factors
Special topics for custom designs (optional)
Blocking designs
Setting constraints in the design  
                                                     
Robust Optimization Methods
Tighten the tolerance of X
Design to the flats
Use interactions to tune out sensitivities
Use parameter combinations
                                                           
Tolerance Design and Margin Analysis
Tolerance design procedure
Tolerance stack up analysis