Optimal Maintenance Strategy Selection for Oil and Gas Industry Equipment Using a Combined Analytical Hierarchy Process–Technique for Order of Preference by Similarity to an Ideal Solution: A Case Study in the Oil and Gas Industry

Maintenance plays a key role in oil and gas enterprises, especially in the process of increasing pressure to improve equipment efficiency, reduce costs, and comply with environmental protection requirements towards sustainable production. This study proposes an optimal maintenance strategy based on the overall equipment effectiveness (OEE) index, using a multi-criteria decision-making method (MCDM) integrating an Analytical Hierarchy Process (AHP) and a Technique for Order of Preference by Similarity to an Ideal Solution (TOPSIS). The study evaluates five maintenance strategies—preventive maintenance (PM), risk-based maintenance (RBM), condition-based maintenance (CBM), reliability-centered maintenance (RCM), and predictive maintenance (PdM)—based on four key criteria: maintenance cost, safety, efficiency, and flexibility. The comparison of each pair of criteria and the maintenance strategy choices was carried out systematically to ensure consistency in the decision-making process. The Evaluation Distance to the Mean Solution (EDAS) method was used as a cross-validation tool to strengthen the reliability of the results. The results showed that RCM is the optimal maintenance strategy, providing superior equipment performance and reliability. The study expands the theoretical basis in industrial maintenance, providing a structured and data-driven decision support tool. The method can be flexibly applied in many industries to optimize maintenance strategies and promote sustainable production.