Holistic hybrid modeling framework for food manufacturing process simulation
A novel hybrid modeling framework that combines physics-based models with machine learning to simulate and optimize food manufacturing processes, enhancing product quality and reducing trial-and-error.
Overview
The holistic hybrid modeling framework is an innovative solution designed to simulate and optimize food manufacturing processes by integrating physics-based models with machine learning corrections. This approach captures the entire food production line, from mixing to drying, enhancing product quality and reducing reliance on trial-and-error experimentation. The framework is practical for implementation in Python, providing a versatile and scalable digital twin that links operating conditions to quality outcomes.
Technical specifications
Key features:
- Mixing: Uses compartment and population balance models to achieve macro- and micro-scale homogeneity.
- Heating: Modeled through transient heat conduction models with temperature-dependent properties.
- Extrusion: Utilizes residence time distribution and reactor-network models linked to screw speed and feed for precise control.
- Drying: Combines Fickian diffusion models with thin-layer kinetics for accurate moisture and shrinkage predictions.
- Integration: AI/ML techniques refine parameters such as diffusivity and viscosity, enhancing model accuracy and adaptability.
- Flexibility: Allows scenario testing and optimization across diverse raw materials and equipment settings.
- User-friendly interface: Designed for process engineers to run simulations without coding expertise.
Technology readiness level
The framework is currently at Technology Readiness Level 5, having been developed and validated against published benchmarks and pilot-scale data. Future validation plans include case studies with varying ingredient compositions and equipment settings to ensure practical applicability and scalability across different food systems.
About The Ohio State University
The Ohio State University is a comprehensive public land‑grant research university in Columbus, serving one of the nation’s largest student populations and a broad research enterprise. Industry partners engage through an integrated academic medical center for clinical translation, a campus‑adjacent innovation district for co‑located projects, and a statewide extension network that pilots solutions across Ohio. Corporate engagement provides a single front door for sponsored research, talent pipelines, and streamlined agreements. Research is supported by competitive federal funding from agencies such as NIH, NSF, DOE, USDA, DoD, and NASA. A dedicated technology transfer office and venture support help protect IP, license technologies, and launch startups.
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