Design of Experiments (DOE)

Turbocharge the efficacy of your product and process designs

What you will learn
How you will learn

What you will learn

Overview

Organizational experiments are often conducted using best-guess or one-factor-at-a-time approaches to determine which particular changes or solutions work best. These methods of testing can be time- and resource-intensive, may lead you on a random walk of experimentation and may or may not produce the optimal solution in the end.

This Design of Experiments (DOE) course, on the other hand, guides experimenters through making several simultaneous changes or testing more than one factor at a time—enabling them to spend far less time and resources doing fewer experiments, while creating better and more reproducible solutions.

Early in my career as an R&D and Manufacturing Engineer, I quickly learned how invaluable DOE could be. As my responsibilities with various organizations grew to ultimately become President and CEO, I insisted we use this amazing tool to define our new product design and process development—and to identify the root causes of unforeseen design and process problems with existing products.

Rodger Stewart - President of North America (retired), Sorin Group

Specifically, course participants will learn what type of design works best for the particular outcomes they want to investigate, and they’ll also learn how to analyze DOE results. They’ll learn about the advantages of fractional and screening designs versus full factorial and Taguchi designs. And they’ll be introduced to such advanced approaches as response surface designs and mixture designs.

Unlike most other courses offered at universities, this course has a strong applied (not theoretical) focus, making the task of learning much simpler and much more connected to business and operational practicalities.

Learning Objectives

Upon completion of this course, participants will be able to:

Enhance product and process development through improved experimentation.
Plan, design and conduct more effective experiments with minimal resources and time.
Accurately track experiment results during multiple trials.
Reduce development time for new products/processes.
Improve process control for higher quality outcomes.

How you will learn

Classroom

Relative to university-based alternatives, this course has a definite applied focus, making it much more valuable to those with an imperative to improve existing and new products and processes.

BMGI instructors for this course have extensive experience in applying DOE across dozens of manufacturing, service, transactional and research organizations. They bring this experience to bear through lecture, hands-on exercises, simulations and individualized mentoring on real problems and challenges participants bring to class from their organizations.

BMGI expert instructors are interesting and engaging, transferring knowledge from a thorough and deep set of course content—always challenging participants to extract the most value from the learning experience and their respective data sets.

Course Length:

5 consecutive days (or 4 days for those who can skip day 1 because they already have a good understanding of basic statistics)

36 hours of instruction

Classroom Cost:

$ 3,950

Classroom Agenda:

Day 1 Basic Statistics for Engineers (Optional)

Data Types, Statistical Measures
Cause & Effect Diagrams
Capability
Statistical Process Control
Simple Linear Regression and Correlation

Day 2 Introduction to Design of Experiments

On-line vs. Off-line Improvement
System, Parameter and Tolerance Design
Loss Function Analysis
Computer Simulations
Design of Experiments Concepts
2k Factorial Designs
Randomizing and Blocking Methods
Main Effects & Interaction Analysis
Multiple Response Optimization

Day 3 Fractional and Screening Designs

2k Fractional Designs
Aliasing and Confounding of Interactions
Screening Designs (Plackett Burman)
Classroom Simulations

Day 4 Full Factorial and Taguchi Designs

Multiple Level Designs
Interactions, Covariates, Random Factors
Transactional DOE’s
Taguchi Concepts
L18 Design

Day 5 Introduction to Advanced Designs

Response Surface Designs
Mixture Designs

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Design of Experiments (DOE)

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Free problem solving resources

Introduction to Design of Experiments

Basic Factorial Experiments

Appropriate for

Engineers, scientists, researchers and developers interested in reducing experiment timing and costs, and improving results.

Those who need to experimentally discover how to solve difficult problems with products or processes.

Those who need to economically validate new product or process designs.

Six Sigma green belts and black belts, as well as those with no prior Six Sigma experience with good statistical acumen .

Course at a Glance

Prerequisites

Classroom:

Laptop computer running Microsoft Excel

No prior knowledge of Six Sigma required

Course Length

Classroom:

5 consecutive days (or 4 days for those who can skip day 1 because they already have a good understanding of basic statistics)

36 hours of instruction

Cost

Classroom:

$ 3,950

Credits

Classroom: 3.6 CEUs