Model for risk and reliability analysis of complex production systems: Application to FPSO/flow-Riser system

A model for risk and reliability analysis of complex multifunctional production process systems is presented. The model employs Monte-Carlo and Markov Chain algorithms that uses a weighted index to train and simulate the fuzzy hazard data sets which represents failure outcomes of risk component transient and non-transient systems. Early simulation results shows that hazard rates and the risk of containment loss from typical floating production and storage offloading (FPSO)-Riser system for the risk components in parallel or series increases exponentially with time and decreases as safety ratings fraction increases. The reliability value decreases with time and safety fraction (SFAC) for all fuzzy hazard classifications. The results of the computed mean time before repair (MTBR) show that the minimum computed years before repair range from about 0.5 computed year for worst case (fuzzy class 1, very likely to fail) to almost 5 million computed years for the best case (fuzzy class 5, remote to fail) assuming availability is 80%. This new method for risk assessment would allow users of the technique generate skewed failure data hazard rates to predict actual failure outcomes of multifunctional processes and complex risk systems.