| Summary: | Modern industries, particularly oil and gas, necessitate robust maintenance management and optimization for increased profits, plant availability, and maintenance cost reduction. The maintenance strategy is therefore crucial, especially under global economic pressures on equipment reliability. This study examines the present maintenance management practices for refinery valves, critical equipment whose failure can have severe consequences. Many existing models for selecting critical equipment in maintenance management face limitations due to inadequate decision analysis and exclusion of key criteria. This research proposes a strategy model, combining artificial intelligence and multi-criteria decision-making techniques like Fuzzy Logic and Analytical Hierarchy Process, to fill this gap and manage refinery valves' maintenance. Proven by case studies and interviews, the model improves safety, reliability, operational availability and enables operators to monitor their decision consequences. The model can convince asset managers to invest in maintenance initiatives.
|
|---|