Robust Optimization, Design Space 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.


This Course is required for all scientists, engineers and quality professionals who actively work on any aspect of discovery, product and process development where the goal is to characterize, optimize and improve product and process performance.


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

16 Hours

Contact Information


1 (650) 967-2700

P.O. Box 2103
Sunnyvale, CA 94087-0103

Course Objectives

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

  • Learn and apply the principles of robust product design

  • Design experiments appropriate for the information of interest

  • Use and apply the structures of orthogonal arrays for product and process development and problem solving

  • Ensure the experimental design is efficient

  • Use regression techniques in order to analyze the results and make process and product improvements

  • Optimize the response at this most robust condition

  • Tolerance the factors and responses

  • Use JMP software to design and analyze experiments

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