RELIABILITY AND RISK ANALYSIS OF A FLOWSTATION CRITICAL EQUIPMENT

ABSTRACT

Flow station installations are complex and need to be maintained properly to keep expected performance. Critical equipment failures on these installations might induce great threats on productivity, personnel safety, and environment. During the operation and maintenance (O&M) activities, lot of data were collected, and it has great potential values to help understand the condition of flow station facilities, and in making reliable decisions. The aim of the research was to carry out reliability and risk analysis of a flow station’s critical equipment, using Oredo flow station Ologbo Nigeria. The failure data from Oredo flow satiation failure log report from 2011 to 2020 was used to carry out quantitative analysis using parametric analysis techniques to compute the reliability characterization of the subsystem, such as Failure Rate (λ), the Mean Time to Failure (MTTF), Probability Density Function (PDF), Reliability Function R(t) of the system and predict failures of critical equipment. Different goodness of fit test was used depending on the distribution that we were dealing with; Kolmogorov-Smirnov for Lognormal/Gumbel distribution, Mann’s Test for Weibull Distribution and Bartlett’s test for Exponential Distribution. Also, we carried out qualitative analysis such as Failure Mode Effect and Criticality Analysis (FMEA/FMECA) and Reliability Centered Maintenance (RCM) on the flow station’s critical equipment. The risk priority number and failure mode criticality number were used in ranking the risk. while Pareto analysis was used to identify the significant few failure modes. The quantitative analysis showed that among the critical equipment for an interval of three years, the most reliable subsystem was Instrumentation Air Compressor B (IACB) with a reliability function of 0.83 and the least reliable was Export Pump B with a reliability function of 0.13 and the reliability function of the critical equipment as a system was 0.43. The qualitative analysis showed that the largest contributing factor to the high criticality numbers of these devices was their high Time-To- Repair with respect to the other devices in the subsystem. The largest contributing factor to the high criticality index of the Gas Compressor K- 3600 was the increase failure rate with respect to the other devices in the Gas Compressor K- 3600. Furthermore, the highest Severity class from the Failure Mode Criticality Matrix were Gas Generator and Export Pump B which is Severity class I. while the least are Instrumentation Air Compressor A (IACA), Gas Compressor K-3600, Export Pump A and Booster Pump A which belong to Severity class III viii respectively. In addition, from the criticality analysis the critical equipment was classifying into classes A, B and C.