The Oil and gas industry has embraced the idea of reliability analyses for driving design improvements as the potential high costs associated with equipment failures lead to the desire of a highly reliable system and/or a reduction in system uncertainty. Reliability engineering is about controlling risk as it deals with the longevity and dependability of assets. There are a number of different types of reliability engineering techniques such as Reliability, Availability and Maintainability (RAM), Reliability-Centered Maintenance (RCM), Failure Modes and Effects (and Criticality) Analysis (FMEA, FMECA) and Fault Tree Analysis (FTA). The following will present in particular how RAM analysis can be employed to identify potential bottlenecks in the process, to outline the planned and unplanned maintenance requirements, to estimate the current availability of the asset and add value to projects through the use of sensitivity analyses in a move away from a reactive approach towards a proactive one.


Reliability, Availability and Maintainability (RAM) analyses are carried out to optimise plant availability to maximise client return on investment. By using the approach a clear auditable trail is created to justify investment in facility improvements which can be made with confidence. This paper describes what RAM is through some key definitions, how it can be used to provide a quantifiable assessment of the effectiveness of an operating asset and a case study to illustrate RAM application. RAM analysis is a modeling technique that has its origin in the military sector involving the V-1 missile team during World War II. It was here that it became first understood that an improvement in the reliability of individual components and reconfiguring the system to improve reliability resulted in an increased likelihood of success. Globally, the Oil and Gas Industry has embraced the idea of reliability analysis for driving design improvements.

This content is only available via PDF.
You can access this article if you purchase or spend a download.