RELIABILITY ANALYSIS AND OPERATIONAL RISK MATRIX OF SAFETY VALVES

This research investigates the application of reliability theory to safety valves, emphasizing fundamental concepts such as the reliability function R(t), failure function F(t), failure rate λ(t), Mean Time To Failure (MTTF), and Mean Time Between Failures (MTBF). A practical case study, based on data collected from a petrochemical operator, illustrates how reliability analysis can identify critical failure modes such as blockage, leaks, early opening, and corrosion, highlighting their severe consequences in safety-related applications. This research applies reliability theory to safety valves, utilizing statistical models like Exponential and Weibull distributions to analyse failure modes such as blockage, leaks, early opening, and corrosion. A key finding is that valve reliability significantly declines after approximately 3,000 operational hours, emphasizing the need for predictive maintenance strategies based on historical and real-time operational data. The study advocates for integrating reliability and maintenance analysis throughout the safety valve lifecycle, shifting from reactive to proactive maintenance to reduce unexpected failures and optimize costs. The study develops an integrated mathematical methodology for failure probability estimation. A case study from a petrochemical operator uses risk assessment tools like risk matrices to prioritize maintenance actions. Data analysis reveals an MTBF of 4250 hours, a CoV of 0.577, and reliability dropping to 49.3% at 3000 hours and 30.8% at 5000 hours. Valve blockage and leaks are critical risks, while premature opening and corrosion are medium risks. Recommendations include using the exponential distribution for reliability analysis, implementing predictive maintenance after 3000 hours, periodic inspections and fluid filtration for valve blockages, and seal replacements and leak-tightness checks for leaks.