Design of Experiments (DOE)

At-a-Glance

How does a problem that has plagued a company for years get solved in 45 days? Effective experimental design and analysis are critical to improving products and process, reducing waste, lowering costs, and improving productivity. This how-to workshop focuses on understanding the fundamental elements of experimental design and on the application of strategies. Numerous exercises are included and a statistical software package, Minitab®, is used for to help create designs, analyze the data, and interpret the results more efficiently and effectively. We will explore the design and collection of new data through designed experiments.

Many companies in both the R&D and manufacturing functions try to solve problems based on theory, opinions or poorly-designed experiments, often with too few factors. We show how to use such theories and opinion to help create and then analyze well-designed experiments with as many factors as needed, where we emphasize experiments from 3 to 15 factors.

Course Topics

• One-factor-at-a-time experiments: what your competitors want you to use
• The importance of a strategy of experimentation
• Summarizing results in experiments: main effects and interactions
• Two-level designs for 3-5 factors: the 2k designs
• Variation when conditions are held constant: a review
• The importance of randomizing and blocking in experiments
• Handling variation naturally in two-level designs
• The value of non-replicated experiments
• How to select the correct number of runs for an experiment
• The role of center points and how to use them correctly
• Fractional factorial (2k–p) designs: studying 5-15 factors, or more efficiently
• The use of fold-over designs to gain more information
• Introduction to response-surface designs
• Case studies, simulations, numerous exercises
• A statistical software package, Minitab®, helps create designs and interpret the results

Who Should Attend

Professionals from Quality, Manufacturing, Engineering, and R&D who plan, conduct, analyze, and interpret tests to evaluate the impact of key parameters on the performance of products and processes. Learn how to select the most effective design to answer important questions about products and processes – maximize results while minimizing time and effort.