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Military Logistics

Military Logistics. Battlespace Logistics Readiness & Sustainment Research RFP#JFL-03-143, Delivery Order #26. ASC PA 03-2409 9/12/03. BSIT0301 Modeling Sortie Generation, Maintenance, and Inventory Interactions for Unit Level Logistics Planners. PI: Manuel D. Rossetti

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Military Logistics

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  1. Military Logistics Battlespace Logistics Readiness & Sustainment Research RFP#JFL-03-143, Delivery Order #26 ASC PA 03-2409 9/12/03

  2. BSIT0301 Modeling Sortie Generation, Maintenance, and Inventory Interactions for Unit Level Logistics Planners • PI: Manuel D. Rossetti • Co-PI: Raymond R. Hill, WSU and Dr. Narayanan One of the primary performance measures for US Air Force fighter wing logistics organizations is the ability to successfully launch aircraft on time and in the proper configuration. The goal of this project is to develop simulation and mathematical modeling methodologies that will assist logistics managers in analyzing the effects of different resource allocation policies and identify potential risks in logistics plans.

  3. SMM0301 Maintenance Decision-Making under Prognostic and Diagnostic Uncertainty • PI: C. Richard Cassady • Co-PI: Heather Nachtmann and Ed Pohl A key challenge faced by USAF maintenance personnel is the uncertainty associated with the information provided by prognostic and diagnostic tools. This uncertainty makes it difficult for maintenance technicians to choose an appropriate course of action. This can potentially cause omission of necessary maintenance actions, performance of unnecessary tasks, and additional delays in returning aircraft to operational status. The goal is to develop a methodology based on mathematical modeling that can be used to provide a more reliable recommendation to the technician.

  4. MM0303 Quantifying the Impacts of Improvements to Prognostic and Diagnostic Capabilities • The objective is to develop a methodology based in mathematical modeling for analyzing the impacts of improvements to prognostic/diagnostic capabilities. • What impact do prognostic and diagnostic errors have on fleet readiness and the associated requirements for spare parts? • Given a specific investment in prognostic and diagnostic improvements, what will the impact be on fleet readiness and spare parts inventory measures? • Given a limited budget for prognostic and diagnostic improvements, how should the funds be allocated to optimize fleet readiness and spare parts inventory measures? • PI: C. Richard Cassady • Co-PI: Ed Pohl

  5. MM0302 Multi-State Selective Maintenance Decisions All military organizations depend on the reliable performance of repairable systems for the successful completion of operational missions. Maintenance cannot be performed during missions; therefore, the decision-maker must decide which systems to repair prior to the next mission. The primary objective of this project is to develop multi-state selective maintenance models that incorporate multi-state component status and multiple measures of system performance. • PI: C. Richard Cassady • Co-PI: Scott Mason and Ed Pohl

  6. PMD0302 Quantification of Logistics Capabilities • PI: Heather Nachtmann • Co-PI: Manuel D. Rossetti and Justin R. Chimka The project objective is to provide the groundwork for an established and accepted system of measurement that assigns value to logistics capabilities based upon each capability’s contribution to Air Force operational effectiveness. Specifically: (1) Develop a common language to describe logistics system requirements; (2) Enable logistics requirements to compete more equally with system hardware and operational requirements in the acquisition process; and (3) Improve operational effectiveness through enhanced logistics capability.

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