| dc.description.abstract | The unstable geopolitical situation in Europe has caused a high demand for energy resources and significant fluctuations in the price of these. This has affected the backbone of the Norwegian economy, its oil and gas industry, to strive for greater production efficiency and more profitable operations from when an asset enters production until it is decommissioned. Maintenance is one of the most significant cost drivers for an offshore oil and gas installation. Hence, minimising the maintenance personnel and workload while keeping all systems in a productive and safe state, is in the best economic interest of all operator companies.
Inherent workload analysis is used as an input for the manning situation, sizing of hotel area on an installation and as a basis for the maintenance program. The analysis has traditionally been a manual, labour-intensive process, leaving the results highly personalised and unrepeatable. Furthermore, several assumptions are taken for granted without specific verification. Therefore, this thesis explores the effect of advancing the condition-based maintenance regime on the manning requirements. Moreover, defining how the inherent workload analysis process can be digitally transformed.
Case equipment selected for this study is critical equipment with monitoring. However, findings discovered in this thesis suggest further and more advanced monitoring equipment. The advanced monitoring systems were proposed based on a detailed analysis of the failure modes, mechanisms, corrective and preventive maintenance history, and manning requirements were also estimated accordingly. Moreover, the case study was taken further as an example to generalise a work process to digitalising inherent workload analysis.
Further implementation of condition based maintenance reduced the preventive workload by 58% and 70% by using already existing technology. The improved process is also estimated to be 50-60% faster while achieving the same or better results, in a more standardised way of working.
This study can be used as the foundation for further research on the effects of condition based maintenance on maintenance hours and the effect this has on operational expenditure. | |