An Open Source First Principles-Based Approach for Energy Forecasting in Discrete Manufacturing Processes Using LLMs/Generative AI

The Defense Logistics Agency (DLA) manages a significant annual procurement budget exceeding $40 billion, involving both discrete and continuous manufacturing processes crucial for national security. Optimizing energy usage in these processes is essential for enhancing operational efficiency and cost-effectiveness. To address this, Green Squirrel Research proposes a novel approach using generative artificial intelligence (AI) and large language models (LLMs) to develop a first principles-based energy calculator. By accurately identifying energy consumption within discrete manufacturing (DM) processes, this tool offers multifaceted benefits for the DLA, including substantial cost reduction, enhanced operational efficiency, and improved sustainability practices. Leveraging the Life Cycle Assessment (LCA) framework, the tool quantifies energy usage and greenhouse gas emissions across the entire manufacturing life cycle, providing a comprehensive understanding of environmental impact. Unlike existing methods reliant on static lookup tables, the proposed approach utilizes fundamental scientific principles to calculate energy consumption, offering tailored insights and reducing uncertainties. Furthermore, the tool's transparency and adaptability enable informed decision-making and facilitate the adoption of energy-efficient manufacturing practices. Through the development and implementation of this innovative tool, the DLA stands to significantly improve its manufacturing operations while contributing to broader global sustainability efforts.