Updating a User Friendly Combined Lifetime Failure Distribution

This paper explores methods for updating the CMBL distribution as new data become available. The initial results obtained in applying Method 1, a Bayesian sequential updating methodology, to the CMBL distribution shows some promise. The method developed in this effort for updating the CMBL distribution and other TTF distributions, should be valuable in enhancing maintenance planning and real-time situational awareness processes. This method, used in enterprise level and prognostics and health management (PHM) modeling, should more accurately help provide instant feedback on the current status of equipment; provide tactical assessment of the readiness of equipment for the next campaign; identify parts, services, etc. that are likely to be required during the next campaign; provide a realistic basis for scheduling and optimizing equipment maintenance schedules; and help ensure that the useful life of expensive components is maximized while reducing the incidence of unplanned maintenance.