Title : Enhancing refinery operational excellence: An AI-powered approach to digital operations management
Abstract:
The refining industry faces multi-dimensional operational challenges that significantly impact safety performance, production efficiency, and regulatory compliance. Startup and shutdown durations for refinery process units are highly variable, with limited benchmarking mechanisms to establish performance standards. Inefficiencies in shift handovers and fragmented knowledge management practices further amplify operational risks and productivity loss.
To address these challenges, an AI-powered digital operations platform has been developed to systematically digitize refinery workflows and enhance overall operational excellence.
Real-Time Progress Monitoring and Startup Optimization: The platform’s robust time-tracking functionality minimizes startup delays by enabling operators to benchmark performance against defined operational standards. Real-time monitoring ensures adherence to optimized startup procedures and identifies potential bottlenecks before they affect production timelines.
Knowledge Management Hub: A centralized repository of technical guidelines, reference documents, and lessons learned ensures that operational knowledge is captured and shared effectively. This promotes proactive fault diagnosis and reduces the recurrence of process failures.
Improved Shift Handover System: Structured digital workflows streamline communication during operational handovers, ensuring critical information is accurately transferred and operational anomalies are promptly escalated.
AI-Based Digital Assistant: Leveraging machine learning and natural language processing, traditional operation manuals are transformed into smart, interactive, voice-enabled systems that provide real-time procedural guidance and context-driven insights.
Implementation outcomes demonstrate significant improvements in operational performance metrics — reduced procedural execution time, enhanced safety compliance, and optimized shift efficiency. This marks a paradigm shift from reactive to predictive operations management, achieving measurable gains in reliability, safety, and regulatory adherence through technology-driven transformation.
