Helping businesses dramatically improve their product and manufacturing performance!!!

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Design of Experiments Training (3-days, 2.4 CEUs), software based training

Experts consider Design of Experiments (DOE) the most powerful statistical tool available to help scientists and engineers invent the best products and processes possible.

The instructor has taught this course for both UCI and UCSD for 6+ years through their Extension and Corporate Training Programs.

Many traditional DOE training programs require 3 days of training to cover the DOE basics and another 2 days of training for the advanced DOE material, which this course covers. Thus this 3-day course is more comprehensive and cost effective.

Learning Outcomes:
Students will get hands-on experience working several DOE exercises.

  • Learn DOE basics (2-level DOEs):
      • Understand important considerations when selecting responses (outputs), factors (inputs), and factor levels to study.
      • Know which standard experiment is appropriate.
      • Know how to block effects from lurking variables.
      • Understand how to interpret experimental charts, graphs, plots, and ANOVA Table.
      • Be able to identify statistically significant factors and interactions.
      • Be able to build a 1st order experimental Y-model for the response and verify that it is adequate.
      • Understand how to use the model to optimize the response.
  • Learn advanced DOE techniques (Robust Designs and More):

Dual Responses

    • Know how to create an S-model for the standard deviation and use it to reduce variation in the response (output).
    • Understand how to use the S-model to estimate product or process capability (Cp, Cpk).
    • Know how to use both the Y-model and the S-model to locate the response on target while minimizing variation. This technique will be performed using both overlaid contour plots and a numeric search routine to find the optimum.

Response Surface Methodology (RSM)

    • Know how to use multilevel DOEs such as Central Composite Designs and Box-Behnken Designs. These experimental designs are needed when there is a curvilinear relationship between one or more of the factors and the response. These efficient experimental designs are used to build a 2nd order experimental model.
    • Be able to use contour plots to find the best targets for the factors in order to optimize the response, referred to as Parameter Design.
    • Understand how to use contour plots to perform Sensitivity Analysis and Tolerance Design.
    • Understand how to move toward a new optimal experimental region when the current results are not satisfactory. A technique called the Path-of-Steepest-Ascent will be demonstrated in class.

Multiple Response Optimization

    • Be able to simultaneously optimize multiple responses using numeric search routines.

Robust Designs

    • Learn how to significantly reduce product and process performance variation by making key CTQ outputs robust to uncontrollable noise factors.

Course Description:
Learn to use Design of Experiments (DOE) to dramatically improve product and process innovation, effectiveness, and efficiency. DOE is the scientific approach used by researchers to build empirical mathematical models of product and process performance. These models are formulas that are used to optimize product and process performance while significantly reducing costs. This software-based course provides practical hands-on training covering basic and advanced DOE methodology. Students will learn how to create 1st and 2nd order empirical product and process models used to identify the optimum levels of product and process performance while reducing variation by using Residual Analysis, Response Surface Methodology and Dual Response Analysis. DOE is the most powerful Six Sigma optimization tool and the Global Harmonization Task Force (GHTF) strongly encourages its use during medical device development. Prerequisite: Prior statistical training would be helpful but it is not necessary to take this course.

Who Should Attend:
This course is intended for Quality Managers, Quality Engineers, R&D personnel, Product Engineers, Process & MFG Engineers, Designers, and Six Sigma Green & Black Belts.

Location:

        • In-house training at your facility is the most cost effective approach for training. Additionally, some time can be used to discuss DOE project opportunities at your business.
        • Public training is scheduled based on interest.

DOE Consulting:

        • Three free consulting hours included with on-site corporate training, good for 60 days after training is completed.
        • Additional consulting is available upon request

Course Materials:
Participants will receive a course manual and a Demo CD of the software used during training, which is active for 30 days after it is loaded.