Knowledge Tree
Industry-scale knowledge graphs
Also known as: industrial knowledge graphs, Industrial knowledge graphs
Facts (14)
Sources
In the age of Industrial AI and knowledge graphs, don't overlook the ... symphonyai.com Aug 12, 2024 12 facts
claimIndustrial knowledge graphs enable industrial collaboration by unifying asset information, time series data, P&IDs, and predictive models in a live workspace, allowing teams to perform root cause analysis and troubleshooting using rolled-up health scores.
claimIndustrial knowledge graphs enable AI-driven predictive analytics by combining asset hierarchy relationships, equipment failure mode and effects analysis (FMEA), and MLOps studios to identify equipment failures that are undetectable by traditional monitoring techniques.
claimIndustrial knowledge graphs enable industrial copilots by combining industrial LLMs with site-specific or company-specific information, allowing generative AI to simplify the generation of insights.
claimIndustrial organizations need a composable approach to building industrial knowledge graphs, allowing them to start with single units or production lines and add new data sources as business use cases are identified.
claimSymphonyAI provides pre-built connectors to over 100 industrial sources and protocols, including OPC UA and DA, Modbus, MQTT, Azure IoT Hub, InfluxDB, Kafka, OSI PI, IP.21, and an ODBC connector, to facilitate the integration of data for industrial knowledge graphs.
claimStandard searching and filtering methods are limited in their ability to surface data as industrial knowledge graphs grow.
claimSymphonyAI combines role-based views with a generative AI copilot to allow users to perform natural language searches on industrial knowledge graphs.
claimIndustrial knowledge graphs support performance analytics by combining asset hierarchies with time series, IIoT, and CMMS data to generate KPIs such as OEE, process and energy efficiency, mass and energy balance, mean-time-between-failure, and mean-time-to-repair.
claimIndustrial knowledge graphs can be enriched by mapping additional IT and engineering data sources to them.
claimIndustrial knowledge graphs facilitate OT/IT convergence by normalizing industrial data and integrating it with ERP, financial, and supply chain data, which provides business users with a real-time view of operations.
claimIndustrial knowledge graphs facilitate process optimization by allowing AI models to query normalized process variables for systems like rolling mills, furnaces, grinding mills, and distillation processes to maximize throughput or energy efficiency.
perspectiveIndustrial knowledge graphs and asset hierarchies should be composable, allowing organizations to build structures that contain only the fraction of available information necessary to meet specific business objectives, such as increasing throughput for a specific production line.
Construction of Knowledge Graphs: State and Challenges - arXiv arxiv.org 1 fact
claimPublicly available information regarding industrial knowledge graphs is limited.
Knowledge Graphs: Opportunities and Challenges - Springer Nature link.springer.com Apr 3, 2023 1 fact
referenceNoy et al. (2019) published 'Industry-scale knowledge graphs: lessons and challenges: five diverse technology companies show how it’s done' in Queue 17(2), which examines the practical challenges of implementing knowledge graphs at an industry scale across five technology companies.