Risk based integrity modeling of offshore process components suffering stochastic degradation

Purpose - The purpose of this paper is to develop a risk-based integrity model for the optimal replacement of offshore process components, based on the likelihood and consequence of failure arising from time-dependent degradation mechanisms.

Design/methodology/approach - Risk is a combination of the probability of failure and its likely consequences. Offshore process component degradation mechanisms are modeled using Bayesian prior-posterior analysis. The failure consequences are developed in terms of the cost incurred as a result of failure, inspection and maintenance. By combining the cumulative posterior probability of failure and the equivalent cost of degradations, the operational life-risk curve is produced. The optimal replacement strategy is obtained as the global minimum of the operational risk curve.

Findings - The offshore process component degradation mechanisms are random processes. The proposed risk-based integrity model can be used to model these processes effectively to obtain an optimal replacement strategy. Bayesian analysis can be used to model the uncertainty in the degradation data. The Bayesian posterior estimation using an M-H algorithm converged to satisfactory results using 10,000 simulations. The computed operational risk curve is observed to be a convex function of the service life. Furthermore, it is observed that the application of this model will reduce the risk of operation close to an ALARP level and consequently will promote the safety of operation.

Research limitations/implications - The developed model is applicable to offshore process components which suffer time-dependent stochastic degradation mechanisms. Furthermore, this model is developed based on an assumption that the component degradation processes are independent. In reality, the degradation processes may not be independent.

Practical implications - The developed methodology and models will assist asset integrity engineers/managers in estimating optimal replacement intervals for offshore process components. This can reduce operating costs and resources required for inspection and maintenance (IM) tasks.

Originality/value - The frequent replacement of offshore process components involves higher cost and risk. Similarly, the late replacement of components may result in failure and costly breakdown maintenance. The developed model estimates an optimal replacement strategy for offshore process components suffering stochastic degradation. Implementation of the developed model improves component integrity, increases safety, reduces potential shutdown and reduces operational cost.