Programs

Statistics Design of Experiment

Overview

Design of Experiments (DOE) is a powerful tool that enables you to investigate and manipulate multiple key process input variables concurrently to optimize a specific output or response variable. This course will expose learners to key knowledge required to design and analyse statistical experiments using Minitab. Pre-requisite Basic Statistics with Minitab will be a distinct advantage. However, the first day of the course will be a review of basic statistical concepts relevant to DOE.

 Course Outline

DOE Statistics

1. Understand key statistical concepts and definitions
   1. Population, sample, types of data , etc
   2. Measures of process variation and central tendency
   3.  Descriptive and inferential statistics.
2. Understand the distribution of your data
   1. ✓ Distribution parameters
   2. ✓ Difference between PDF and CDF
   3. ✓ Probability Distributions – normal, t, binomial, Poisson, F, Chi-square. 9
3. Review of Statistical Inferences with Minitab
   1. ✓ Confidence Intervals.
   2. ✓ Hypothesis testing.
   3. ✓ Analysis of Variance.
   4. ✓ Goodness-of-fit test.
   5. ✓ Individual Distribution Identification.
4. Review of Regression Analysis with Minitab.

 DOE Fundamentals

1. Understanding DOE terms and concepts
   1. ✓ independent and dependent variables,
   2. ✓ factors and levels,
   3. ✓ treatment, error, replication,
   4. ✓ full and fractional designs,
   5. ✓ screening experiments,
   6. ✓ confounding, etc
   7. ✓ covariates and analysis of covariates (ANCOVA).
2. Experimental Planning
   1. ✓ Measurement systems analysis,
   2. ✓ Identifying your objectives,
   3. ✓ Identifying factors and responses of interest,
   4. ✓ Design type selection,
3. Creating a Design In Minitab
   1. ✓ Create a Full Factorial Design,
   2. ✓ Understand Design Table,
   3. ✓ Modify your design to Fractional Factorial,
   4. ✓ Understand Aliasing and Alias Structure.
4. 11 Manually Analyse A Full Factorial Design
   1. ✓ Understand Main Effects,
   2. ✓ Understand Interaction Effects,

 Design and Analysis of Experiments

1. Create and Analyse A Screening Experiment
   1. ✓ Definitive Screening Design.
   2. ✓ Plackett-Burman Design
      1. ▪ Analyse Design Summary,
      2. ▪ AnalysePareto Effects, 

AnalyseEffects Plot,

1. ▪ AnalyseMain Effects,

2. Create and Analyse A Two-level Full Factorial Design
   1. ✓ Create and store your design.
   2. ✓ Analyse your design using available tools in Minitab ▪ Four-in-One plot, probability plot,
      1. ▪ ANOVA, Pareto, main and interaction plots, etc
   3. ✓ Reduce the model by screening out factors that are not statistically significant.
   4. ✓ Optimise your design.
   5. ✓ Identify optimum settings using ▪ Contour plot (Plant Flag) ▪ Surface Plot ▪ Response Optimiser
   6. ✓ Use your model to make predictions.
3. Create A Response Surface Design.
   1. ✓ Central Composite Design.
   2. ✓ Box-Behnken Design.
   3. ✓ Response Surface with Categorical factor.