Aircraft Maintenance Management to Unanticipated Failure Events

ABSTRACT:The Air Forces Air Logistics Centers (ALCs) are charged to maintain the fleet at maximum readiness. In order to achieve this goal, the ALCs perform aircraft scheduled maintenance using well-defined planning and scheduling processes and procedures by assigning MRO tasks to minimize the time an aircraft spends at the depot and the associated maintenance costs. However, the current system does not allow for dynamic schedule re-planning that allows users to react to anomalous events or unscheduled maintenance requirements. Robbins-Gioia proposes to solve this problem by using advanced genetic algorithms to efficiently solve static and dynamic, large scale scheduling problems. With this innovative scheduling approach, we will improve that responsive and optimality of aircraft maintenance schedules to meet both preemptive and nonpreemptive maintenance requirements.BENEFIT:Initial market analysis shows that a general Maintenance Management System that addresses complicated scheduling and planning requirements can have applicability across the federal, state, and private business sectors. Any type of transportation maintenance facility or complex manufacturing facility that requires resource scheduling and re-planning may be applicable commercial markets for the technology sponsored by this SBIR research. Candidates include airlines, commercial aircraft and engine manufacturers, ship builders and dry dock maintainers, passenger and industrial rail transport, bus lines, and rental car companies.