Increasing Plant Reliability of Offshore Gas Installations

The maintenance improvement factor (IF), which provides a mathematical description of maintenance efficiency, can be used to determine the probability of component failure, the foundational block for calculating the optimal preventive maintenance interval. The IF can be estimated via probabilistic analysis of failure data. However, this body of data does not usually incorporate subjective information such as procedure compliance, the quality of spare parts, or the time available for completing an activity. Subjective information provides vital insight into the quality of maintenance. Since poor quality maintenance is assumed to promote component failure in the short term, an IF incorporating subjective information can improve estimates of the probability of component failure. The required information can be provided by maintenance experts. Unfortunately, the literature has shown that their judgment is inherently biased, and this diminishes the accuracy of the IF estimate. This thesis provides a framework within which to estimate a bias-free IF, referred to here as the expert improvement factor (EIF). The EIF is obtained from a combination of an expert interview and a survey administered to maintenance personnel; the survey incorporates questions regarding factors that promote human error in maintenance. The optimal maintenance interval, of a system consisting of two components, based on the EIF was estimated using a simulation model. The model suggests that considerable savings in the total maintenance cost can be realized by estimating the optimal preventive maintenance interval based on the EIF. The current thesis also proposes a second framework that can be applied to determine the effect of reducing the factors considered in the survey, providing a managerial tool for reducing the total maintenance cost over the long term. As an application of the first framework, a specific framework was developed for estimating the optimal maintenance interval for multiple components in a real-world offshore oil and gas installation.Ph.D.2020-11-19 00:00:0