Maintenance Management Optimization: Evaluating Manual and Automated Methods of Tracking Uptime Hours for Offshore Equipment

Abstract

Offshore oil and gas fields are among the largest contributors to global oil and gas production. The reliable functioning of these facilities relies heavily on the reliability of the process equipment. Managing and operating offshore equipment is inherently complex, requiring careful planning to ensure maximum uptime and minimal downtime. This study addresses a significant gap in knowledge by comparing the effectiveness of manual and automated methods for tracking the uptime hours of offshore equipment. Using a mixed-methods approach that incorporates quantitative and comparative data analysis, the research assesses the impact of each tracking method on equipment reliability, maintenance costs, and production efficiency. The findings indicate that both methods exhibit high level of accuracy and consistency, with minor differences, confirming the reliability of both methods. However, the study reveals that the automated tracking system, which demonstrated more significant data consistency across shifts when compared to the manual approach, offers substantial advantages, including reduced human error, improved data collection efficiency, and enhanced maintenance scheduling. These benefits, result in improved equipment reliability, lower maintenance costs, optimized maintenance management and greater production efficiency. The study recommends the use of automated logging systems, regular calibration, and maintenance of automated systems, and combining data from both approaches for cross-verification. To ensure accuracy and consistency across all equipment and shifts, it is advised that personnel involved in manual logging receive enhanced training and that logging procedures undergo continuous improvement.