This module designs a two-level multifactorial orthogonal plan 2^(n–k) and perform its analysis. The DOE module has two parts, Design for the experimental design before carying out experiments which will find optimal combinations of factor levels to gain maximum information at a reasonable number of experiments and part Analysis which will analyse results of the planned experiment. The main goal of DOE is to find which of the factors included in the model have considerable influence on one outcome of the experiment. The outcome is called response and it can typically be yield, energy consumption, costs, rate of non-conforming product units, blood pressure etc.

Design and analysis of experiment (DOE) - Pdf manual

Text/numerical output:

Graphical output:

Design type Design definition Design charcteristics Number of factors and replication No of experiments needed Alias structure analysis Main effects and interactions Computed effects and regression coefficients Effects standard deviations Analysis of variance (ANOVA) Total variability Explained variability Residual variability Influence of factors to variance Detailed analysis - Taguchi approach Means(-/+), Variances(-/+) Influence ratios(+/-) Residual analysis Response prediction

Plot of absolute effects  Sorted effects Squared effects Diagnostic Effects QQ-plot Deviations in QQplot Effects plot Interaction plot

Design of Experiments input dialog box

Analysis of Designed experiments input dialog box

Example output from DOE Analysis. 2^(6-1) design, 6 efects, 16x2 experiments

Graphical outputs of the module is essential and highly informative part of the analysis, revealing most influential factors and interactions for the first sight. Some of the plots are shown below.

Effects and interaction, assessment of influence

Detailed visualization of all pairs if second order interactions

Overall interaction plot