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<p>In this research project, we provide a method in which we incorporated a nonlinear model to allocate consolidated automated support system (CASS) stations utilizing real demand. In reviewing available literature, we frame the allocation of CASS stations as a problem of discrete capacity allocation with stochastic demand, and note that similar problems exist in the allocation of other types of service capacity (e.g., hospital beds). We employed a nonlinear model to present a better method for allocation. Currently, NAVAIR PMA 260 uses an algebraic formula to determine CASS station allocation. The nonlinear model takes into account factors that the algebraic formula does not, such as aircraft readiness and CASS station utilization. With the model, we generated an optimized allocation of CASS stations based on average demand from aircraft maintenance action forms received at a Fleet Readiness Center over a given period of time. Then, we demonstrate that the optimized allocation can account for monthly, non-stationary demand inputs, as potentially seen in a fleet response plan. Compared to the current allocation of the Fleet Readiness Center analyzed, the optimized allocation improves CASS station utilization rates with a decreased overall number of CASS stations, without an adverse change in aircraft readiness.
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<br>Subjects: Consolidated automated support system; CASS; eCASS; non-linear programming; resource allocation; discrete stochastic capacity allocation; queuing congestion; utilization; operational availability; readiness</div>
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<dl><dd>Rorer, James L.</dd>
<dd>Asifuinagomez, Luis F.</dd></dl></div>
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