Speaker
Description
AFTAC has demonstrated a new approach to analyzing data gaps that identifies and helps to understand drivers of our network performance. Every data gap is now assigned unique identifier, characterized and then cataloged for analysis. Previously, we have struggled to link non-associated data gaps with specific system components or maintenance actions. This new methodology shows how data gaps not resulting in unscheduled maintenance can be used as indicators for an upcoming hard failure. Planned scheduled maintenance activity then allows preemptive action to prevent larger outages. The analysis of these cataloged gaps have been crucial in both AFTAC engineering and maintenance planning by development of models projecting future network behavior. The results allow for performance optimization of the CTBTO network we are responsible for while greatly increasing cost effectiveness and reducing risk for AFTAC.
