Downtime uncertainty reduction through the correct implementation of health monitoring tools

The objective of Integrated Vehicle Health Management (IVHM) is to increase platform availability and reduce maintenance times and costs through the use of health monitoring on key systems. The information generated using condition monitoring algorithms can be used to reduce maintenance times, improve the management of the support process and operate the fleet more efficiently. This paper discusses the effect of advanced health monitoring tools on the uncertainty of predicted downtimes and costs for vehicles and fleets and how they affect the management of the asset. If a health monitoring tool is to be installed it is critical to keep in mind that the objective is to maximise the use of the asset, not just reduce the average downtime. An improvement of the availability might not translate in a significant increase of effective active time since operational planning normally involves working with conservative estimations for the maintenance time. Thus, algorithms that result in a higher average downtime but present lower uncertainty can be more effective at maximising the use of a given vehicle. Most Cost Benefit Analyses (CBAs) focus on calculating the difference between the current average downtime and the expected downtime to determine the benefit of using algorithms to diagnose or predict a fault. Calculating the variation of these uncertainties with the introduction of health monitoring tools is critical to assess what the real impact on the downtime is going to be. The benefits of the approach presented in this paper are: (1) a better understanding of how uncertainties play a role in the downtime and maintenance cost of the asset, (2) being able to differentiate between improving the availability of the asset and its active operational time and (3) an improvement in the viability of CBAs for health monitoring to