Design of Experiments

Design of Experiments (DOE)

Design of Experiments (DOE) is a systematic method to improve an operating process by analyzing the relationship

between the inputs and outcome.


A major challenge to industry is to cut design and development times while assuring that designs are effectively and efficiently characterized.  An essential tool in supporting this activity is the practical application of Design of Experiments. 



Design of Experiments is the premier tool in supporting these efforts  in areas of product design and process development.  We offer practical and hands-on training and consulting in these approaches.  We have over 30 years of experience in product and process optimization in a number of industries.  Our team has taught and consulted on the application of these tools for three decades.  We have taught over 5000 engineers and scientists about these terrific tools.  We can have your team doing great applications of these tools in as little as a two or four day session.

  • Why Launsby Consulting?

    We are practical, not theoretical with a unique ability to explain complex engineering and mathematical theories with compelling sketches and diagrams. We can make Design of Experiments easy to understand.

  • We can teach sessions using

    JMP, Minitab, DOE Wisdom software. In addition, we like to customize the training to your specific areas of application.

  • Before your session

    We can integrate your applications or use our library of applications for class exercises.

  • Length of session:

    2 or 4 day sessions

  • In house or public seminars

    Contact us today for more information.

Public Seminars

  • Scientists, engineers, managers, technicians. Anybody who wants to quickly attain an applications-based understanding of Design of Experiments.

  • Public seminars are scheduled throughout the year all across the Continental US.

  • Sample Agenda for a DOE Seminar

    Day 1:

    Introductions, Goals, Expectations

    The Need for Experimental Design in Industry

    Why Engineers, Technicians and Scientists Need to Use These Powerful Approaches

    Examples of Applications from Your Industry

    How to build skill in conducting Designed Experiments

    How long is Pay-back Time with Design of Experiments Training?

    What is Experimental Design?

    What are the Benefits?

    What is a Process Diagram?

    Objectives
    Troubleshooting
    Modeling
    Screening
    Robustness
    Mixtures

    Why Conduct an Orthogonal Array?

    Basic Concepts: Effects, Interactions, Orthogonal arrays

    Graphical Analysis using examples and software
    Pareto Charts
    Main Effects
    Interaction Plots
    Contour Plots
    RSM Plots

    Screening Approaches vs. Modeling Approaches

    Sample Size

    Checklist of Detailed Planning Questions

    Why Confirmation Trials are Important

    How to determine if your experiment confirmed

    Day 2:

    Blending Experimental Design with Knowledge of the Technology

    Common Pitfalls for Those New to Design of Experiments

    Analysis for Variance Reduction

    Full-Factorials, Fractional-Factorials, Taguchi Arrays

    Computer Optimal Designs

    Mixed and Multi-level Orthogonal Arrays

    ANOVA and MLR Using Software

    Numerous Case Studies with Software

    Rules of Thumb regarding Set-up and Analysis

    Multiple Response Co-optimization Using Desirability Functions

    Residual Analysis

    Planning Your Experimental Application, Getting Started with Successful Applications!

    Group Exercise

Enrollment Details

Format: Public Seminars

Submit your interest form (LEFT) with the class date. We will contact you with additional enrollment details.

Cost: $1500.00 per attendant

Includes:

  • Detailed Participants Guide

  • eBook Engineering Today’s Designed Experiments

Available Sessions:

  • June 17 & 18, 2024 Denver, Colorado

    • Deadline to Register: June 3, 2024

  • September 23 & 24, 2024 Denver, Colorado

    • Deadline to Register: September, 2024