Reliability analysis of the components frequently starts with the data that manufacturer provides. If enough failure data are collected from the field operations, the reliability should be recomputed and updated on the basis of the field failure data. However, when the failure time record for a component contains only a few observations, all statistical methodologies are limited. In this case, where the failure records for multiple number of identical components are available, a valid alternative is combining all the data from each component into one data set with enough sample size and utilizing the useful information in the censored data. The ROK Navy has been operating multiple Patrol Killer Guided missiles (PKGs) for several years. The Korea Multi-Function Control Console (KMFCC) is one of key components in PKG combat system. The maintenance record for the KMFCC contains less than ten failure observations and a censored datum. This paper proposes a Bayesian approach with a Dirichlet mixture model to estimate failure time density for KMFCC. Trends test for each component record indicated that null hypothesis, that failure occurrence is renewal process, is not rejected. Since the KMFCCs have been functioning under different operating environment, the failure time distribution may be a composition of a number of unknown distributions, i.e. a mixture distribution, rather than a single distribution. The Dirichlet mixture model was coded as probabilistic programming in Python using PyMC3. Then Markov Chain Monte Carlo (MCMC) sampling technique employed in PyMC3 probabilistically estimated the parameters’ posterior distribution through the Dirichlet mixture model. The simulation results revealed that the mixture models provide superior fits to the combined data set over single models.

Naval combat system developed in-country is progressing at an alarming rate since 2000. ROK navy will be achieved all vessels that have combat system in the near future. The importance of System Engineering and Integrated Logistics Support based on reliability analysis is increasing. However, reliability analysis that everyone trusted and recognized is not enough and applied practically for development of Defense Acquisition Program. In particular, Existing Reliability Analysis is focusing on reliability index (Mean Time Between Failure (MTBF) etc.) for policy decision of defense improvement project. Most of the weapon system acquisition process applying in the exponential distribution simply persist unreality due to memoryless property. Critical failures are more important than simple faults to ship’s operator. There are no confirmed cases of reliability analysis involved with critical failure that naval ship scheduler and operator concerned sensitively.Therefore, this study is focusing on Mean Time To Critical Failure (MTTCF), reliability on specific time and Operational Readiness Float (ORF) requirements related to critical failure of Patrol Killer Guided missile (PKG) combat system that is beginning of naval combat system developed in-country. Methods of analysis is applied parametric and non-parametric statistical techniques. It is compared to the estimates and proposed applications. The result of study shows that parametric and non-parametric estimators should be applied differently depending on purpose of utilization based on test of normality. For the first time, this study is offering Reliability of ROK Naval combat system to stakeholders involved with defense improvement project. Decision makers of defense improvement project have to active support and effort in this area for improvement of System Engineering.