The choice of experimental design depends on the objectives of the study and the complexity of the system. Common designs include:
Full Factorial Design: All possible combinations of factors and levels are tested. This is ideal for understanding interactions but can be resource-intensive. Fractional Factorial Design: Only a subset of the possible combinations is tested. This reduces the number of experiments while still providing valuable information. Response Surface Methodology (RSM): Used for optimizing conditions by fitting a polynomial equation to the experimental data.
