design of experiments with minitab

Design of Experiments (DOE) with Minitab – 3 day

Design of Experiments with Minitab Course Description
Design of Experiments (DOE) is an off-line quality improvement technique that can be employed to dramatically improve industrial products and processes. Through its use, it is possible to isolate the cause and effect linkages between product/process variables and the resulting output measures of function, quality, cost and performance.

This course provides participants with in-depth understanding of the basic principles of experimental designs. Actual examples are emphasized throughout the presentation.  Participants are taught how to use screening designs (fractional factorials) to identify important factors, along with characterization designs (general factorials and 2^k factorials) for assessment of main effects and interaction. Use of games such as helicopters and unique simulation exercises accelerates the learning process and makes the learning process fun for the engineer.

Knowledge of DOE and the ability to effectively use DOE are basic requirements of modern engineering.  This course equips the engineer to effectively plan, execute, analyze and interpret DOE’s.

This course goes beyond teaching participants how to simply point and click. The basic concepts underlying each tool are discussed before the use of the software is demonstrated.

Who Should Attend Design of Experiments with Minitab
This course is designed for Managers and Engineers from all engineering disciplines, including Process, Research & Development, Quality, Maintenance, and Reliability.

Learning Objectives
Through training, participants will gain knowledge of Experimental Design Fundamentals and the ability to perform Product/Process Characterization experiments to understand main effects and interactions of factors. Participants will also learn to:

  • Identify Key Product and Process Parameters for Improvement
  • Run experiments for Improved Product/Process Performance Relating to Cost, Quality, and Reliability

Design of Experiments with Minitab Course Outline

How Experimental Design is Useful in Industry

  • Using Experimental Design as part of a Total Quality Solution

Complementary Relationship between DOE and SPC

  • Attributes of a Well-Designed Experiment

Review of Basic Statistics Fundamentals

  • Measures of Location and Spread (Mean, Median, Standard Deviation, Variance)
  • Normal Probability Plot/Normal Distribution
  • Hypothesis Testing
  • Confidence Intervals

Single-Factor Experiments

  • Randomized Experiments
  • Blocking and Nuisance Variables
  • Analysis of Variance
  • Simultaneous Multiple Comparisons
  • Residual Analysis for checking assumptions

Factorial Designs for Characterization

  • General Factorial Design
  • 2^k Factorial Design
  • Main Effects and Interactions: Analysis and Interpretation
  • Blocking in Factorial Designs
  • Unreplicated Full Factorial Designs

2^k-p Fractional Factorials Designs for Screening

  • Hierarchy of Terms and Alias Structure
  • Resolution III, IV and V designs
  • Fold-over Designs
  • Blocking Unreplicated Full/Fractional Factorials
  • Design with Centerpoints for testing curvature
  • Sequential Experimentation

DOE Planning

  • 10 Step Planning Guide

Live Experimentation

Prerequisites
None

Design of Experiments with Minitab Course Format
24 hours
Combination lecture and classroom exercises
Available at QSG’s training facilities, on-site at your organization, and virtually

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