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🔬 DOE Design of Experiments
Full / fractional factorial, Box-Behnken, CCD — with AI design recommendation
Design Type
Factor Names (optional, default A/B/C...)
🤖 AI Recommendation
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Experiment Plan
How to Use
· 2-level Full Factorial: every high/low combination, 2^k runs; estimates all main effects and interactions
· 3-level Full Factorial: 3 levels per factor, 3^k runs; also estimates curvature
· Plackett-Burman: screening design; at most N-1 factors in N runs; main effects only
· Box-Behnken: response surface; 15 runs (3 factors) / 27 (4 factors) / 46 (5 factors); no corner points
· Central Composite (CCD): response surface; 2^k + 2k + center points; axial points suit quadratic models
· After generating the design, enter measured values in the Response column, then click AI Analyze Results
· Sample: the classic "chemical reaction yield" full factorial case — 3 factors (reaction time 20/50, reaction temperature 150/200, catalyst B/A), 2 replicates × 2 blocks = 16 runs, response Y = yield; compare it with the design table generated here to see how factor names and high/low levels are entered
· 3-level Full Factorial: 3 levels per factor, 3^k runs; also estimates curvature
· Plackett-Burman: screening design; at most N-1 factors in N runs; main effects only
· Box-Behnken: response surface; 15 runs (3 factors) / 27 (4 factors) / 46 (5 factors); no corner points
· Central Composite (CCD): response surface; 2^k + 2k + center points; axial points suit quadratic models
· After generating the design, enter measured values in the Response column, then click AI Analyze Results
· Sample: the classic "chemical reaction yield" full factorial case — 3 factors (reaction time 20/50, reaction temperature 150/200, catalyst B/A), 2 replicates × 2 blocks = 16 runs, response Y = yield; compare it with the design table generated here to see how factor names and high/low levels are entered
About DOE Design of Experiments Generator
Free DOE generator: create full factorial, fractional factorial, response surface and Taguchi designs with randomized run order and effect analysis.
Learn more about this tool →
Response Surface Methodology
Taguchi Robust Design
Main Effects & Interaction Plots
Mixture & D-Optimal Design
One-Way ANOVA
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