Subsea Spare Parts Analysis Optimisation

The main objective of this paper is to present a fully quantitative methodology combining reliability, availability and maintainability (RAM) analysis and cost-benefit analysis (CBA) approaches to determine the optimum sparing strategy for subsea components considering reliability data, lead times, availability and cost. This methodology can be utilized at any stage of an asset lifecycle, from design to operation and can be adjusted to reflect modifications throughout the life of field. Using commercially available RAM analysis software, Maros [2], a reliability block diagram (RBD) is constructed to represent the reliability structure and logic of the system being analyzed. Retrievable components, for which spares would be suitable, are then identified within the model to review and update the failure modes and reliability information for each component. Reliability information can be based on project specific data or from industry-wide sources such as OREDA. The RAM analysis software uses the Monte-Carlo simulation technique to determine availability. A sensitivity analysis is then performed to determine maximum availability while holding the minimum required stock level of spare components. A sparing priority factor (SPF) analysis is then performed in addition to the RAM sensitivity analysis to support those results and consider spare purchase, storage and preservation costs. The SPF gives a weighting to the storage cost against the potential impact on production. The SPF is a number used to determine a component’s need to have a spare. A high SPF indicates an increased requirement to hold a spare.