Design of Experiments (DOE) with Minitab – Advanced

Course Description
This course explores how experimental design can be applied to the product and process optimization phase of development. Using Response Surface Methods, models that relate the process outputs to the process inputs are generated. These models allow one to determine optimal settings for the process and identify “sweet spots” that enable the process to be robust to uncontrollable variables.

Participants will apply their newly acquired knowledge by designing, running, and analyzing a series of experiments via Minitab computer simulations.

Who Should Attend
This course is designed for managers and engineers involved in product and process design (R&D) and improvement. Basic DOE knowledge and Minitab Essentials or equivalent are required prerequisites for this course.

Learning Objectives
Upon completion of the course, participants will:

  • Understand Response Surface Strategy for Process Optimization
  • Understand Taguchi Philosophy and Contribution to Process Optimization
  • Have the ability to use Minitab to design and analyze experiments

Course Outline
Experimental Design and Regression Analysis Fundamentals Review

  • Factorial Design Concepts
  • Fractional Factorial Designs
  • Blocked Designs
  • Regression Analysis (One Factor Process Optimization)

Introduction to Response Surface Methods

  • Experimentation as an Iterative Process
  • Goals and Strategy of RSM
  • Case Study

First Order Models

  • Experimental Designs for Fitting First Order Models
  • Use of Center Points to Test Curvature
  • Path of Steepest Ascent (POA)

Second Order Models

  • Experimental Designs for Fitting Second Order Models: 3^k, Central Composite
  • Designs, Box-Behnken Designs
  • Rotatability and Orthogonality

Blocking in RSM Designs

  • Experimental Designs for Fitting Second Order Models: 3^k, Central Composite
  • Designs, Box-Behnken Designs
  • Rotatability and Orthogonality
  • Blocking in RSM Designs

Multiple Response Optimization

  • Desirability Function

Taguchi Methods

  • Basic Taguchi Philosophy for Robustness and Ruggedness
  • Quality Loss Function
  • Strategy for Robustness and Ruggedness Testing

Live Experimentation

Course Format
16 hours
Combination lecture and classroom exercises
Available at QSG’s training facilities and on-site at your organization

 

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