Designing Optimal Chocolate Chip Cookie Experiments

This guide presents a detailed exploration of a kitchen experiment aimed at optimizing chocolate chip cookie recipes through the application of statistical design methodologies. It outlines the use of a split-plot design to manage hard-to-change (HTC) baking factors alongside easy-to-change (ETC) mixture components. The document explains how KCV (Kowalski, Cornell, and Vining) models are utilized to minimize the number of experimental runs while still effectively detecting interactions between mixture and process variables. Additionally, it discusses the incorporation of blocking techniques to facilitate the experiment over two days, ensuring that production and sensory evaluations are manageable. The experiment, guided by an industrial experiments student, involved varying ingredients such as butter and sugars, and adjusting baking temperatures and times to achieve desired cookie textures. The findings emphasize the importance of statistical methods in culinary experimentation, ultimately leading to a recipe that balances taste preferences and baking efficiency.