Planning and executing a design of experiments (DOE) can be a complex task involving multiple specialists. Post-experiment, the challenges of analyzing, interpreting, and communicating results persist, particularly when stakeholders have varying levels of technical expertise. To streamline this process and standardize our workflow, we developed a script that automatically visualizes DOE results. The script generates two intuitive graphs that effectively convey the findings.

The first graph illustrates the total variability of each variable of interest, indicating the extent to which each variable can be influenced according to the DOE. The second graph summarizes the sensitivity of the variable of interest to changes in input variables.

Our script is designed for flexibility, allowing for the addition of new calculations and normalization of graphs as needed. This tool has significantly improved our efficiency, saving approximately two hours per graph compared to manual methods. Moreover, the standardized visualization format enhances communication with non-technical stakeholders, making the DOE results more accessible and easier to understand.