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.
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
Introduction to Design of Experiments
- Using Experimental Design as part of a Total Quality Solution
- Classifications of Designs
- How DOE is an Improvement over One-Factor-at-a-Time Experimentation
- Attributes of a Well-Designed Experiment
- Hypothesis Testing
- Confidence Intervals
Factorial Designs for Characterization
- General Factorial Design
- Main Effects and Interactions: Analysis and Interpretation
Analysis of Variance
- 2^k Factorial Design
- Residual Analysis for checking validity of test assumptions
Blocking in Factorial Designs
- Unreplicated Full Factorial Designs
2^k-p Fractional Factorials Designs for Screening
- Hierarchy of Terms and Alias Structure
- Resolution IV and V designs
- Blocking Unreplicated Full/Fractional Factorials
- Sequential Experimentation
- 10 Step Planning Guide
Knowledge of Basic Statistics and the statistical software Minitab. Basic Statistics includes Measures of Centering, Spread, and Shape such as Mean, Median, Range, Variance, Standard Deviation, and the Normal Distribution.
Design of Experiments with Minitab Course Format
Combination lecture and classroom exercises
Available at QSG’s training facilities, on-site at your organization, and virtually