PI Mapping Intelligence System
BKOAI’s multi-agent system maps PI points to physical equipment across SCADA, maintenance, and operational databases
Goals
- Map PI points to physical equipment across multiple disparate databases.
- Resolve inconsistent tag names and operational context gaps.
- Establish a live knowledge graph to enhance system diagnostics.
- Automate the equipment-tag mapping process to eliminate manual workflows.
Challenges
- Equipment appears under different aliases across disparate industrial databases.
- Mapping processes rely heavily on manual efforts and tribal knowledge.
- Fragmented systems lack semantic alignment, restricting analytics and automation.
- Operational systems experience data context gaps due to isolated silos.
Solutions
- Deploy collaborative agent-to-agent reasoning with self-reflection capabilities.
- Utilize natural language processing and domain ontologies to extract tag descriptions.
- Integrate symbolic reasoning to map and resolve physical equipment identities.
- Establish continuous feedback loops for live, automatic mapping updates.
Results
- Automated knowledge graphs of equipment-tag relationships.
- Scalable deployment capable of adapting to multi-system industrial environments.
- Improved diagnostic accuracy and operational visibility across the organization.
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