Design of Experiments and Statistical Process Control
Design of Experiments
Functions for design of experiments (DOE) enable you to create and test practical plans to gather data for statistical modeling. These plans show how to manipulate data inputs in tandem to generate information about their effect on data outputs. Supported design types include:
- Full factorial
- Fractional factorial
- Response surface (central composite and Box-Behnken)
- Latin hypercube
You can use Statistics Toolbox to define, analyze, and visualize a customized DOE. For example, you can estimate input effects and input interactions using ANOVA, linear regression, and response surface modeling, then visualize results through main effect plots, interaction plots, and multi-vari charts.
Fitting a decision tree to data. The fitting capabilities in Statistics Toolbox enable you to visualize a decision tree by drawing a diagram of the decision rule and group assignments.
Model of a chemical reaction for an experiment using the design-of-experiments (DOE) and surface-fitting capabilities of Statistics Toolbox.
Statistical Process Control
Statistics Toolbox provides a set of functions that support Statistical Process Control (SPC). These functions enable you to monitor and improve products or processes by evaluating process variability. With SPC functions, you can:
- Perform gage repeatability and reproducibility studies.
- Estimate process capability.
- Create control charts.
- Apply Western Electric and Nelson control rules to control chart data.
Control charts showing process data and violations of Western Electric control rules. Statistics Toolbox provides a variety of control charts and control rules for monitoring and evaluating products or processes.