The FMEA and DV&PV process of developing automotive products requires identifying and repeatedly testing critical vehicle attributes and their response to noise factors that may impair vehicle function. Ford Electrified Powertrain Engineering has developed a new process and an automated scripting tool to streamline in-vehicle robustness testing and produce more accurate and repeatable results. Similar noise factors identified during the FMEA process are grouped together, condensed, and scripts are developed to simulate these noise factors using calibration parameters and vehicle controls. The automated testing tool uses the ATI Vision API and a graphical scripting interface to consistently simulate driver inputs with greater precision than a human calibrator and enable more sophisticated controls, which would have previously required experimental software builds. The noise factor scripts are executed with minimal intervention from a human operator, and the collected data is analyzed to determine robustness. The scripts are archived to form a testing library which facilitates repeated tests throughout the DV&PV cycle. Results of repeated tests are compared against metrics to evaluate progress towards complete robustness. Combining the new robustness process and the scripted testing tool allows for a more efficient use of limited testing time in prototype vehicles, creates tests that closely reflect the identified noise factors, and results in tests that are more repeatable than tests performed by a human driver. The scripting tool and robustness testing process were developed for a hybrid powertrain, but they are applicable to all powertrain types.