Risk-Based Spare Part Planning. Uncertainties and Operational Conditions

Abstract

Estimates which indicate a large share of the world’s undiscovered oil and gas resources is to be found in the Arctic areas and the increasing demand for energy are important reasons for the growing interest in the High North region. As the offshore industry expands into the High North, system failures associated with these projects is expected to increase significantly. Hence, the quest for effective maintenance and maintenance support services are increased. However, the demanding physical conditions of the Arctic, the remote location, and the uncertainty from various sources are expected to increase the challenges related to the spare part planning, especially the transportation of spare parts.

The aim of this thesis is to study, review, and propose a model for risk-based spare part planning, especially for spare part transportation, considering the effect of operational conditions. Furthermore, the concept of both static and dynamic transportation networks is used to calculate the mean spare part transportation time and spare part deliverability. The application of the static model is demonstrated by a case study.

In this thesis, the theoretical framework chapter covers a brief survey of spare part planning, risk-based approaches, risk assessment methods, and application of risk analysis to spare parts planning. Then, types and sources of uncertainties, factors affecting spare part planning and spare part forecasting methods are reviewed. Afterward, a static model is developed for spare part transportation by considering the operating conditions of the Arctic region. The model is based on the concept of the transportation block diagram. A case study for the oil & gas (O & G) industry is presented to demonstrate how the proposed model can be applied. Furthermore, a dynamic model for spare part transportation is also developed. In this model, the factors which provide dynamic behavior of a spare part transportation network such as season (months) of the year (i.e. to transport the spare part), and criticality of the spare part are modeled.

The results obtained from data analysis showed that operational conditions of the Arctic region leads to approximately 20% extended delay’s during the winter season, when we transport the spare part from the southwestern Norway to the northern Norway. Hence, any decision about the spare parts planning, especially the transportation of spare parts in the Arctic region must consider the effects of the operational conditions of the region.

Keywords: Spare part, Transportation, Block diagram, Deliverability, Dynamic network, Arctic, Risk-based, Operational environment, Uncertainties