Case Study: Ford Motor Company achieves 90% data reconciliation accuracy and reduced production downtime with TigerGraph

Ford Motor Company - Customer Case Study

Ford Motor Company, which manages manufacturing equipment worldwide via IoT, faced data ambiguity across two relational databases that caused production downtimes and prevented reliable asset tracking. To consolidate records and remove duplicates, Ford turned to TigerGraph, deploying a graph database and entity resolution capabilities to resolve asset tags and unify machine data.

TigerGraph implemented entity resolution and similarity-matching algorithms on a graph platform, enabling Ford to reconcile data to the same piece of production machinery with 90% accuracy. Using TigerGraph, Ford can now identify parts about to fail and pre-plan replacements, avoiding unnecessary assembly-line stops and improving overall production efficiency.

Ford Motor Company