Summaries - Office of Research & Innovation
Back Aviation Depot Maintenance Throughput Optimization
|Division||Research & Sponsored Programs|
|Department||NPS Naval Research Program|
MacKinnon, Douglas J.
|Sponsor||NPS Naval Research Program (Navy)|
The Naval Aviation Enterprise is tasked with providing sufficient numbers of aircraft to meet readiness and operational surge requirements. Tactical aircraft, in particular, have experienced significant depot level maintenance delays, which have a corresponding deleterious effect on airwing and squadron operational availability. Given a projected induction schedule, we seek to identify an optimal allocation and matching of aircraft-to-depots to maximize squadron aircraft availability constrained by both current baseline conditions, and increased resource and capacity scenarios. This study will partner with OPNAV N81 to leverage simulation to test candidate maintenance policies. The following research questions will be addressed:
RQ1: How can the allocation of aircraft to depots be optimized that maximizes squadron aircraft availability, given a planned induction schedule?
RQ2: How might funds be optimally allocated to improve depot throughput, specifically should funds be distributed differently to specialist labor, parts, capacity, or other areas?
RQ3: How soon could existing backlogs be reduced to acceptable levels under the various funding scenarios discovered using the optimal allocation?
We plan to choose the aviation platform with the greatest percentage of depot level maintenance delays. We will gather all available data on maintenance activities at this depot, along with aircraft availability requirements to determine all relevant constraints and variables. We will utilize Pyomo, a Python-based optimization and modeling software, to model the system and define all binding constraints using available resources. Our efforts will also focus on resource reallocation should a funding increase become available.
This effort will result in deliverable thesis research of our mutual student (Maj Kyle Ellis, USMC) who has enrolled in OA 3201 (Linear Programming) with Dr. Rob Dell to advance his skills in optimization. Findings may be applied throughout DoD.
|Publications||Publications, theses (not shown) and data repositories will be added to the portal record when information is available in FAIRS and brought back to the portal|