Prototipo de asistente operativo inteligente (DABU) integrado con herramientas SCADA (Rockwell) para apoyo en la operación de estaciones de producción de crudo

Abstract

The fragmentation of operational data in oil production facilities represents a critical bottleneck for timely decision-making within Centralized Control Rooms (CCR). This research presents the design, development, and implementation of DABU (Intelligent Operational Assistant), a hybrid neuro-symbolic platform integrated with industrial SCADA systems under Rockwell Automation's PlantPAx distributed architecture. The system is deployed across a six-layer virtualized environment (ISA-95) using independent virtual machines, enforcing a zero-trust network topology. DABU's cognitive engine combines the precision of a deterministic Python execution unit, which evaluates telemetry thresholds and alarms in real time, with a Retrieval-Augmented Generation (RAG) pipeline for unstructured technical manuals (PDFs) and historical logs (Excel sheets) indexed in ChromaDB. Conversation orchestration is governed by state graphs in LangGraph, routing language synthesis to a quantized local Large Language Model (phi3:mini) operating on-premise without reliance on external cloud APIs. Experimental validation in an emulated industrial environment confirmed DABU's ability to streamline operational triage and deliver context-grounded technical diagnostics. No hallucinations were observed in deterministic calculations during the evaluated trials, supporting the robustness of the proposed hybrid architecture and demonstrating its suitability as a resilient and model-agnostic solution for critical OT infrastructure.