Conference Agenda

Discrete manufacturing industry faces multiple challenges due to data silos arising from the use of multiple Management Information Systems (MIS) in the company leading to poor cross-system traceability and make root-cause analysis of a failure or parts/components manually intensive and prone to data inconsistencies. Traditional relational databases are not capable of mul-ti-hop queries required for complex industrial troubleshooting, such as link-ing a field failure back to specific design tolerances, machine or robot effi-ciency and supplier batches. Large Language Models (LLMs) are able to of-fer intuitive interfaces with reasoning capability but standard Retrieval-Augmented Generation (RAG) often encounters hallucinations due to a lack of context and awareness regarding Product Development, Manufacturing and Supply Chain Management (SCM) schemas. This research proposes a novel GraphRAG (Graph Retrieval Augmented Generation) based orchestra-tion framework designed to bridge these gaps by mapping siloed data into a Unified Knowledge Graph (UKG) of Product Lifecycle Management (PLM), Enterprise Resource Planning (ERP) and Manufacturing Execution Systems (MES). The Systems Architecture (SA) utilizes an LLM orchestrator which acts as a central hub for managing the flow of Data between the User, LLM and UKG.