A major petrochemical plant faced increasing pressure to maintain high uptime while operating complex process units with aging equipment and a shrinking pool of experienced operators. Troubleshooting was slow, inconsistent, and heavily dependent on tribal knowledge, paper-based procedures, and manual investigations across logs, historian trends, and vendor documents. Leadership needed a faster, more reliable way for operators to access accurate guidance during alarms, excursions, and unit deviations.
We implemented a GenAI Operator Assistant significantly improved troubleshooting speed, operational consistency, and workforce readiness:
40% reduction in troubleshooting time, enabling faster stabilization of unit disturbances
Fewer prolonged excursions, reducing equipment stress and operational risk
Consistent troubleshooting across shifts, improving reliability and safety
Faster onboarding of new operators, reducing training time
Clear knowledge traceability, reducing dependence on tribal knowledge
THE SITUATION: The plant’s most experienced operators were retiring, leaving behind gaps in critical operational knowledge. Procedures were stored in multiple systems and formats, creating friction during high-stress events when quick decision-making was essential. Historian data required expert interpretation, and troubleshooting steps varied significantly across shifts. These inconsistencies drove longer disturbances, higher equipment stress, and increased operational risk.
THE PROBLEM: The petrochemical plant faced several knowledge, visibility, and workflow challenges that slowed troubleshooting and increased operational risk, including:
Critical knowledge spread across manuals, SOPs, shift logs, and vendor documents
Inconsistent troubleshooting across shifts and operators
Long investigation cycles during alarms, excursions, or unit deviations
Difficult access to historian trends and the “right” contextual signals
Loss of expertise due to retirements and turnover
High cognitive load on control room personnel
The Frame Solution
Deployed a GenAI-powered Operator Assistant that centralized knowledge, integrated operational signals, and delivered immediate, context-rich guidance to operators. Our solution combined change management, knowledge engineering, RAG frameworks, historian integration, and natural-language interfaces.
Consolidated manuals, SOPs, P&IDs, shift logs, and case histories into a structured knowledge layer
Built a secure RAG (Retrieval-Augmented Generation) pipeline for accurate, context-aware responses
Integrated historian signals and alarm/event data for situational reasoning
Enabled natural-language questions (e.g., “What are likely causes of this temperature spike?”)
Delivered step-by-step troubleshooting guidance aligned with plant SOPs and safety rules
