Digital twins and AI for process optimization

This company seeks AI and digital twin technologies to simulate manufacturing processes and predict how changes in ingredients, equipment, or parameters affect final product quality in food and consumer products, enabling smarter process optimization and reducing costly trial-and-error approaches.

Overview

• Partnership opportunity to develop simulation tools for manufacturing optimization
• Focus on enabling "first-time-right" execution and reducing waste
• Solutions to accelerate scale-up from lab to production environments
• Technologies to improve adaptability to ingredient variability and shifting market needs
• Platforms to enable consistent product specifications across multiple facilities

Priority Areas

• Digital Twin Platforms: Solutions simulating manufacturing workflows for food and consumer products
• Machine Learning Models: Systems for soft sensing and real-time process adjustment
• Simulation Tools: Technologies for what-if scenario testing in production environments
• Analytics Platforms: Solutions enabling cross-site performance benchmarking and best practice sharing

Eligibility & Requirements

Must Have:

• Must simulate key manufacturing steps (mixing, heating, extrusion, drying)
• Must predict how process parameters affect final product quality
• Must simulate how changes in ingredients, equipment, or environmental conditions affect product quality
• High-cost technologies that don't demonstrate ROI may be out of scope

Nice to Have:

• Integration with real-time sensors for dynamic parameter adjustment (moisture, temperature, dosage)
• Cross-site performance comparison capabilities to capture and share best practices
• Integration of energy, water, or resource efficiency metrics into process simulations
• End-to-end digital twin models simulating entire production lines under different scenarios

Please note: Full RFP is attached in the "More Information" section of this page. Faculty and researchers interested in applying for these opportunities based on technologies developed or disclosed at Vanderbilt must submit their proposals through the CTTC.