Optimizing Maintenance Inventory Management to Improve Operational Efficiency, Asset Reliability and Financial Performance

Abstract

This study investigates the optimisation of maintenance inventory management in capital-intensive refinery operations to enhance operational efficiency, asset reliability, and financial performance. The background of this research is driven by persistent inefficiencies in Maintenance, Repair, and Operations (MRO) inventory, which often result in excessive capital tied up in slow-moving stock and an increased risk of obsolescence. The objective of this study is to identify the root causes of inventory inefficiency and develop an integrated optimisation framework for improving inventory turnover and reducing provisioning exposure. The research employs a mixed-method case study approach combining qualitative thematic analysis and quantitative inventory classification. Data were collected through interviews with key operational stakeholders and supplemented by secondary data from inventory management systems. Analytical methods include Inventory Turnover Ratio (TOR) assessment and multidimensional ABC-VED-FSN classification. The results reveal significant inefficiencies, including a low TOR of 0.67, a high proportion of non-moving inventory, and provisioning exposure exceeding USD 50 million. The analysis identifies five principal root causes: the absence of criticality-based segmentation, inaccurate master data, the lack of periodic review processes, disposal constraints, and conservative procurement practices. In conclusion, the proposed integrated optimisation framework is expected to improve TOR to 0.95 by 2030 and achieve a significant reduction in provisioning exposure. The study highlights the importance of data governance and structured inventory classification in achieving sustainable operational and financial efficiency in refinery maintenance systems.