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Aircraft Maintenance Management to Unanticipated Failure Events


OBJECTIVE: This topic seeks the development, testing and demonstration of a novel approach to planning and scheduling of aircraft maintenance practices at the depot level when unanticipated fault/failures are discovered upon arrival of the aircraft. DESCRIPTION: The Air Force"s Air Logistics Centers are charged with the responsibility to maintain the Air Force"s aircraft fleet to its maximum readiness level at all times by ascertaining that maintenance, repair and overhaul tasks are carried out optimally in terms of the time each aircraft spends at the depot, the cost of repair, the quality of service, etc., i.e., these critical assets will be available and perform reliably when needed. The ALCs perform scheduled aircraft maintenance following a well-defined planning and scheduling protocol that involves initial inspection, disassembly, repair, assembly and testing upon the arrival of the aircraft at the depot. Historical records, maintenance logs, observations, etc., are typically used to define a sequence of repair tasks for critical aircraft components/systems and to allocate maintenance shops for actions dictated by the schedule. This"routine"maintenance schedule is pursued in the absence of anomalous or unanticipated events detected during the initial inspection stages. In the event, though, of a severe unanticipated occurrence (cracks on critical airframe components, leaks, corrosion, missing components, etc.) the current schedule, as a static tool, does not allow for dynamic re-planning to accommodate efficiently and effectively the new status of the vehicle so that significant repair delays are avoided or minimized. Maintenance efficiency is an important initiative for ALCs and a major driver for this topic. The proposed re-planning tool must deliver relevant information about the status of the aircraft and integrate this information into the maintenance/repair schedule. It must integrate seamlessly with legacy (Concerto, PDMSS, EMIS data mart, RCAN) and future systems (as available) from static data to real-time, as necessary. It must produce schedules that are constantly improved by genetic algorithms which are informed by existing scheduling systems. Streamlining the amount of time an aircraft spends in the depot is the motivation for initiatives like High Velocity Maintenance (HVM) and others enabling improvements in aircraft operational availability. Technologies that improve the information available to the maintainer will enhance the HVM process and provide measurable gains. A dynamic planning and re-planning technology is required that is capable of evaluating the impact of such unanticipated events on the overall maintenance schedule, re-planning on-the-fly to optimize depot resources available and expedite the time the aircraft spends on the ground. Dynamic re-planning can be viewed as a fault-tree modeling and constrained optimization problem. It must be integrated seamlessly into existing software while it accommodates learning and adaptation algorithms allowing for continuous improvement of the depot maintenance/repair practices. The contractor must identify metrics to show quantifiable improvements with re-planning in terms of the mean time the asset spends on the ground, the efficiency and quality of service, etc. The contractor must develop and test in simulation initially an optimized re-planning strategy in the presence of unanticipated events to prioritize repair activities and demonstrate quantifiable benefits to the ALCs. Access to available data and information regarding current planning/scheduling practices will be provided to the contractor by Warner Robins ALC. PHASE I: Phase I work will focus on the conceptualization, initial development and demonstration via simulation of the dynamic re-planning tool and associated models given the discovery of an unanticipated fault/failure event upon initial inspection of the aircraft. PHASE II: This phase of the program will build upon the findings of Phase I and develop, test and evaluate an optimized re-planning tool; the tool must be integrated into available schedules and exhibit attributes of learning and adaptation; it must consider other related ALC activities aimed to achieve improved maintenance efficiency, such as High Velocity Maintenance, Work Scope Optimization, etc. Transitioning of the final re-planning package to AF operations must be considered. PHASE III: This phase will result in a fieldable package that can be installed in ALCs and other AF facilities to augment current planning/scheduling software and improve the efficiency of maintenance and related operations. REFERENCES: 1. Camci, F., Valentine, G.S.,"Optimum Maintenance Scheduling for Complex Systems using Mixed Integers Linear Programming,"60th Meeting of the Society of MFPT, April 2006. 2. Vachtsevanos, G., Lewis, F., Roemer, M., Hess, A., and Wu, B.,"Intelligent Fault Diagnosis and Prognosis for Engineering Systems", John Wiley and Sons, September, 2006.
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