Asset Hierarchy
Assembly Line
In the age of Industrial AI and knowledge graphs, don’t overlook the asset hierarchy
70% of industrial organizations struggle to use operational data for analysis1. While existing point solutions deliver targeted analysis and impact, the unstructured OT data landscape has prevented this impact from scaling across additional sites or use cases. The purpose of an asset hierarchy is to normalize and structure operational data, removing the need to understand the unique naming conventions of siloed systems and simplifying the use of OT data for analysis at scale.
An asset hierarchy provides a logical, tree-like structure representing an industrial organization’s physical assets. It contains parent-child relationships between units and systems, systems and equipment, and components and their parts. These relationships can represent a single unit or production line and span from the enterprise to individual parts.
Generative AI data exploration – As an industrial knowledge graph continues to grow, standard searching and filtering are helpful but limited in the data they can surface. Searching by a specific asset or description may not yield all the results a user is seeking. To enhance knowledge graph exploration, SymphonyAI combines role-based views with a built in a generative AI copilot so users can perform searches in natural language. Instead of search by a specific asst name, search for “list all of the alerts for pumps in my area” and quickly find actionable information within the continuously evolving industrial knowledge graph.