Abstract: A system includes a processor. The processor is configured to generate, based on historical data and a product identifier of a product associated with a reverse engineering project, a decision recommendation associated with a second user role. The processor is also configured to generate, based on a query, a role-based task associated with a first user having a first user role. The processor is further configured to provide the decision recommendation to a second device associated with a second user having the second user role, to receive first task data from a first device associated with the first user, to generate at least one reverse engineering task based on at least the product identifier, to generate a reverse engineering artifact by performing the at least one reverse engineering task, and to store the first task data and the reverse engineering artifact in a memory.

Abstract: A system aggregates data related to a non-conformance system in an aircraft and allocates resources to repairing the non-conformance condition. The system includes a service bus that receives and distributes the non-conformance condition and an optimizer tool that generates repair alternatives. The optimizer tool allows dynamic reconfiguration of rules to activate and deactivate or change a weight of individual rules in a rule set.

Abstract: A system aggregates data related to a non-conformance system in an aircraft and allocates resources to repairing the non-conformance condition. The system includes a service bus that receives and distributes the non-conformance condition and an optimizer tool that generates repair alternatives. The optimizer tool allows dynamic reconfiguration of rules to activate and deactivate or change a weight of individual rules in a rule set.

Abstract: A platform management system, apparatus, and method are disclosed that track schedule interruption data and at least one of delay risk data, deferral risk data, deferral data, and dispatch reliability data over time, compute cross-correlations between the schedule interruption data and the at least one of the delay risk data, the deferral risk data, the deferral data, and the dispatch reliability data, and computing a statistically significant probability of a schedule interruption based on the cross-correlations and a trend of the at least one of the delay risk data, the deferred maintenance data, the deferral data, and the dispatch reliability data projected over a predetermined time period into the future, and that compute delay risk data based on projected schedule interruption data and delay data.

Abstract: Described herein is an apparatus that includes a disruption severity module and flight recommendation module. The disruption severity module calculates a disruption severity index value associated with an unscheduled maintenance event of an aircraft. The disruption severity index value is calculated based on a plurality of flight operation factors affected by the unscheduled maintenance event. The flight recommendation module recommends one of resolving the unscheduled maintenance event of the aircraft before a subsequent flight of the aircraft or flying the aircraft without resolving the unscheduled maintenance event of the aircraft based on the disruption severity index value.