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The purpose of this paper is to explore various in-flight crew escape options of a prototype transport aircraft and finalize the option offering safest crew egress for different combinations of contingencies and flight conditions.

Various egress options were explored through simulation in a computational fluid dynamics (CFD) software using aircraft 3D CAD model and scalable digital mannequins. For this, certain important contingencies which best describe the extreme aircraft behaviour were identified. Crew escape options, which have least external interference in expected egress trajectory, were selected. Several test simulations representing each feasible combination of contingency, escape option and flight condition were simulated. The option which offers safe crew escape in each test case is deemed to be the safest egress option for the test aircraft.

Among five options explored, crew escape through forward ventral hatch provided the safest crew escape for all test cases. The selected option was validated for robustness with additional test cases modelling different anthropometric characteristics of 5th and 50th percentile pilot populations with different postures.

In-flight validation of safe crew escape option is infeasible by actual trial. Exploration of safe crew options for required number of test cases by any analytical method or by wind tunnels tests is tedious, time consuming and extremely expensive. On the other hand, exploration of safest crew option by CFD, besides being first of its kind, provides convenient option to configure, test and validate different test cases with unmatched benefits in time, cost and simplicity.

The purpose of this paper is to eliminate the wastes and inefficient procedures in the maintenance organization of aircraft so as to reduce its downtime and increase mission availability.

Customized lean Six Sigma (LSS) was applied at the task level and servicing cycle level to reduce the task content, cycle length and resources in servicing. The loading of the servicing facility was simulated through a simulation program developed from a statistical analysis of historical data for validating/simulating/determining optimum loading of servicing facility with refined tasks, reduced cycle length and resources. In simulation, the optimum combination of manpower, resources and infrastructure at the facility level was determined through sensitive analysis and design of experiments (DoE).

Optimization at the task level and its re-organization at the servicing cycle level reduced the cycle length by 55-68 per cent and manpower resources by 26 per cent. This further reduced facility-level manpower by 25 to 40 per cent, capacity requirements by more than 33 per cent and annual aircraft downtime by 78 per cent. The approach reduced the average number of aircraft undergoing servicing at each airbase at any time from 2.35 to just 0.76 and increased the mission availability to 20 per cent.

The hallmark of the paper has been the design of LSS approach from structured historical data and its validation through innovative simulation. The multi-pronged bottom-up approach practically bundles all wastes resident in the maintenance organization. The paper provides cursory approach to lean practitioners in the elimination of wastes in the maintenance of capital assets like aircraft.