Predictive Maintenance Strategies for Heat Exchangers Applied in a Hybrid Project Management Framework for Oil and Gas Industries

This study presents the development of a predictive maintenance model for heat exchangers in oil refineries, integrating agile methodologies within a structured project management framework. Conducted as a case study in an oil and gas company refinery, the research addresses challenges related to data accuracy, model reliability, and implementation. The hybrid methodology encompasses project scope definition, data collection from laboratory-scale and operational heat exchangers, and model development over 18 months. The model was validated and refined through rigorous testing, enabling the prediction of optimal cleaning schedules. Risk management strategies included applying a Risk Breakdown Structure (RBS) and SWOT analysis, resulting in optimized maintenance scheduling, cost reduction, and enhanced operational efficiency and safety. This approach provides a benchmark for improving oil and gas industry maintenance practices.