Developing high-quality ice cream requires a delicate balance between processing parameters, ingredient formulation, and sensory experience. General Mills is looking to leverage AI and ML-driven modeling approaches to optimize ice cream processing and formulation while ensuring that the final product maintains its expected sensory properties. 

Achieving an optimal balance between texture, mouthfeel, and stability while maintaining production efficiency is challenging due to the inherent variability in ingredients and processing conditions. Current methods rely on time-intensive physical experimentation, making it difficult to predict how formulation and process adjustments will impact the final product. 

To address this challenge, we seek hybrid simulation models (combining multiphysics and ML-based predictions), AI-powered ingredient interaction modeling, and consumer sensory experience prediction to develop a digital framework that links process parameters, ingredient composition, and end-product perception. 

A robust AI-driven system will enable rapid scenario testing, significantly reducing the time and cost associated with traditional R&D. By predicting the effects of changes in freezing conditions, mixing speeds, stabilizer concentrations, or ingredient substitutions, this approach will enhance production agility, improve product quality, and accelerate innovation. Ultimately, this will ensure that any changes in formulation or processing result in a final product that meets both manufacturing efficiency goals and consumer expectations.