MBSE Applications to Optimize Predictive Maintenance Scheduling in Military Aviation

This paper presents the operational and data models of a commercial aircraft maintenance scheduling optimization tool applied to the United States Air Force (USAF) KC-46A. Condition Based Maintenance Plus (CBM+) advancements are also modeled in the tool by optimally scheduling predictive maintenance (PMx) actions during regular scheduled inspection periods (i.e., A and C letter checks). These models detail how the USAF can apply commercial solutions in line with the KC-46A's commercial derivative sustainment strategy while realizing the benefits of CBM+. In response to the introduction of more modern aircraft derived from commercial platforms, Georgia Tech Research Institute (GTRI) is researching how to automate maintenance scheduling for fleets of USAF aircraft by leveraging commercial best practices that integrate different check types into a single schedule. This approach could allow reduction in the number of checks and increased aircraft availability while supporting military-specific planning requirements. Related to this, GTRI is aware of the USAF's desire to accelerate its transition from a scheduled/preventative maintenance strategy to a more predictive maintenance (PMx) mindset (via CBM+). To help make the transition as smooth as possible within the USAF and other branches, a Model-Based Systems Engineering (MBSE) approach is used to detail the operational activities and data required for the shift in strategy. Using work previously accomplished by Technical University (TU) Delft as a springboard, this paper reports on GTRI's research into developing such MBSE products.