Integrating Fuzzy FMEA and RAM Analysis for Evaluating Modernization Strategies in an LNG Plant Pumping and Vaporization Facility

Abstract

In today’s competitive industrial landscape, Reliability Engineering plays a vital role in minimizing costs and expenses in energy projects. The main focus of this paper is to propose the integration of a fuzzy-based FMECA process into a RAM analysis to assess modernization and reconfiguration strategies for LNG facilities. This approach estimates, through a systematic procedure, the system’s failure probabilities and gauges the impact of various maintenance and topological modification initiatives on the asset and the system’s availability as a driver of profitability. A methodology based on fuzzy-FMEA is proposed to collect and process imprecise data about reliability and maintainability of the components of the facility. Furthermore, Monte Carlo-based RAM experiments are performed. The selection of parameters for conducting Monte Carlo experiments is done after the defuzzification of MTBF and MTTR values defined in the FMEA stage. The proposed procedure allows for the prediction of the system’s reliability across hypothetical scenarios, incorporating design tweaks and potential improvements. As a case study, the proposed was applied to a Pumping and Vaporization facility in a Chilean LNG plant. Sensitivity analysis was performed on critical elements, leading to an optimization strategy for key components like Open Rack Vaporizers (ORV) and Submerged Combustion Vaporizers (SCV). The anticipated availability rate was found to be 99.95% over an 8760 h operating period. Final conclusions and managerial insights are discussed.

Keywords

• LNG plants
• maintenance
• RAM analysis
• optimization
• Monte Carlo experiments