Semantic Ontology AI Assessments at the US Navy COMFRC
Scope Overview
The Commander, Fleet Readiness Centers (COMFRC) sustains Naval Aviation readiness through depot-level maintenance, repair, and overhaul. These operations rely on recurring maintenance processes governed by Technical Orders, logistics data, quality requirements, and constraints. COMFRC leadership remains accountable for safe, repeatable, auditable processes aligned with engineering intent and surge requirements.
The Process Effectiveness Management System (PEMS) assesses whether maintenance processes execute as intended, identifies execution gaps, and evaluates risk across required inputs. Over time, processes drift as Technical Orders, Logistics Product Data (LPD), routes, inspection plans, and shop-floor execution change on different cycles. Process Owners must reconcile intended and actual execution, an effort that scales poorly. Performance metrics show outcomes but rarely pinpoint where risk enters the process or which execution inputs—Manning, Method, Machinery, Material, Measurement, Medium, or Management—are incomplete. To address these challenges, Shipcom developed the AI-Enabled PEMS-AI Assessment Tool (Figure 1).
Figure 1. AI-Enabled PEMS-AI Assessment Tool | Shipcom’s AI-Enabled PEMS-AI Assessment Tool evaluates maintenance execution, identifies process gaps, and highlights risk drivers across all seven inputs for auditability.
Shipcom’s PEMS-AI capability uses a semantic ontology and AI to normalize maintenance data across Technical Orders, logistics and quality records, routes, and defect history. It assembles step-level evidence and generates 7M-structured process artifacts with full traceability to authoritative sources.
Shipcom AI flags gaps and conflicts early—such as missing measurements, unclear tooling, or inconsistent instructions—reducing manual reconciliation and improving auditability. This enables Process Owners to focus on governing, standardizing, and improving maintenance processes rather than reconstructing them.