Digital twins are the foundation for the Factory of the Future providing the data foundation to answer questions like what is happening and what can be done about it. It requires combining data across the business — from R&D, manufacturing, supply chain, and operations — and with partners, that then is used with AI to make decisions.
This session presents a case study of a digital twin implemented for warehouse controllers designed to alleviate internal decisions and recommendations for next trips, that replaces tribal knowledge and gut-decision making. We share how we use a domain knowledge graph to drive a data-driven approach that combines warehouse data, with simulations, AI models, and domain knowledge. Warehouse controllers use a dispatch control board that provides a list of orders by dispatch date and time, destination, carrier, assignments to the trailers and to the order and dock number. We show how this new semantic layer works with large language models to make it easier to answer questions on what trip to activate and trailer to choose; based on assets available, products in inventory, and what’s coming out of manufacturing.
Talk by: Teresa Tung
Here’s more to explore:
A New Approach to Data Sharing: https://dbricks.co/44eUnT1
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