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Purpose From on-board automotive diagnostics to real-time aircraft state of health, the implementation of health monitoring and management systems are an increasing trend. Further, reductions in operating budgets are forcing many companies and militaries to consider new operating and support environments. Combined with longer service lives for aircraft and other systems, maintenance and operations processes must be reconsidered. The majority of research efforts focus on health monitoring techniques and technologies, leaving others to determine the maintenance and logistics impact on the systems. The paper aims to discuss these issues. Design/methodology/approach This research analyzes the impact of a health monitoring system on a squadron of aircraft. Flight, maintenance and logistics operations are stochastically modeled to determine the impact of program decisions on supply metrics. An arena discrete event simulation is utilized to conduct this research on 20 components on each of the 12 aircraft modeled. Costs and availability are recorded for comparison across three sparing scenarios to include economic order quantity (EOQ) for baseline and health monitoring cases and a just-in-time (JIT) health monitoring set of simulations. Findings Data are presented for EOQ and JIT supply methods. A comparison of health monitoring enabled supply to current methods shows cost savings and availability gains. The different methodologies are compared and discussed as a trade-space for programmatic decisions. Originality/value This work demonstrates the ability of health monitoring systems and condition based maintenance to affect supply ordering decisions. The development of trade-spaces within operating environments is demonstrated along with the ability to conduct cost benefit analyses.

Across many industries, systems are exceeding their intended design lives, whether they are ships, bridges or military aircraft. As a result failure rates can increase and unanticipated wear or failure conditions can arise. Health monitoring research and application has the potential to more safely lengthen the service life of a range of systems through utilization of sensor data and knowledge of failure mechanisms to predict component life remaining. A further benefit of health monitoring when combined across an entire platform is system health management. System health management is an enabler of condition based maintenance, which allows repair or replacement based on material condition, not a set time. Replacement of components based on condition can enable cost savings through fewer parts being used and the associated maintenance costs. The goal of this research is to show the management of system health can provide savings in maintenance and logistics cost while increasing vehicle availability through the approach of condition based maintenance.This work examines the impact of prediction accuracy uncertainty in remaining useful life prognostics for a squadron of 12 aircraft. The uncertainty in this research is introduced in the system through an uncertainty factor applied to the useful life prediction. An ARENA discrete event simulation is utilized to explore the effect of prediction error on availability, reliability, and maintenance and logistics processes. Aircraft are processed through preflight, flight, and post-flight operations, as well as maintenance and logistics activities. A baseline case with traditional time driven maintenance is performed for comparison to the condition based maintenance approach of this research.This research does not consider cost or decision making processes, instead focusing on utilization parameters of both aircraft and manpower. The occurrence and impact of false alarms on system performance is examined. The results show the potential availability, reliability, and maintenance benefits of a health monitoring system and explore the diagnostic uncertainty.