An Analysis of Depot Repair Capacity as a Criterion in Transportation Mode Selection in the Retrograde Movement of Reparable Assets

To support smaller reparable asset inventories, current Air Force supply and transportation policies direct the expedited evacuation of reparables by bases and deployed units to the source of repair. Mode selection is based on the asset. Focusing on the asset and moving it quickly is an efficient and effective method of getting assets to where they are needed in a timely manner in the forward portion of the supply pipeline. However, in the reverse portion of the pipeline, the demand for a particular type of asset may no longer be the most important factor in how it is transported. The quantity of the asset at the depot pipeline may already exceed the repair shops capacity. In such an instance, the rapid movement of an asset to the depot, results in the asset being added to the backlog of items already awaiting repair. The focus should shift to the capacity to repair the asset. Since the depots have budget and manning constraints and do not operate on 24-hour shifts, 365 days a year, their capacity to fix reparable assets is limited. With finite repair resources, the question of when an asset can be repaired should be involved in mode determination. This thesis will evaluate current Air Force retrograde transportation mode selection policy. Using Warner Robins Air Logistics Center reparable asset production data, this thesis will compare depot pipeline inventory for a random sample of reparable assets against the depot\u27s repair capacity. If depot pipeline quantity is greater than the depot repair rate, then use of premium transportation is inappropriate, unless it is the lowest cost mode. The difference in cost between the mode used and the alternate mode will demonstrate the potential savings of using depot repair capacity as a determinant of mode selection

Depot repair capacity as a criterion for transportation mode selection in the retrograde movement of reparable assets

To support smaller reparable asset inventories, current Air Force logistics policies direct the “expedited evacuation of reparables ... to the source of repair.” Mode selection is based on the asset. Focusing on the asset is an efficient and effective method of getting assets to where they are needed in a timely manner in the forward portion of the supply pipeline. However, in the reverse portion of the pipeline, the demand for an asset may no longer be critical to how it is transported. The quantity of the asset at the depot may already exceed repair capacity. In this instance, rapid movement results in the asset being added to the backlog already awaiting repair, thus retrograde modal selection focus should shift to repair capacity. Since the depots face budget and manning constraints and do not operate on a continuous basis, their repair capacity is limited. With finite repair resources, the question of when an asset can be repaired should be involved in mode determination. A stock-point modeling approach was used, with depot production requirements as a surrogate for demand in calculating shipping priority. Using Warner Robins Air Logistics Center reparable asset production data, this article illustrates potential savings in transportation that are possible utilizing an alternative factor in modal choice decision for the retrograde or reverse portion of the pipeline

Imitation in international relations: Analogies, vicarious learning, and foreign policy

10.1080/03050620304593International Interactions293237-26

Review of Solar Energetic Particle Models

Solar Energetic Particles (SEP) events are interesting from a scientific perspective as they are the product of a broad set of physical processes from the corona out through the extent of the heliosphere, and provide insight into processes of particle acceleration and transport that are widely applicable in astrophysics. From the operations perspective, SEP events pose a radiation hazard for aviation, electronics in space, and human space exploration, in particular for missions outside of the Earth’s protective magnetosphere including to the Moon and Mars. Thus, it is critical to imific understanding of SEP events and use this understanding to develop and improve SEP forecasting capabilities to support operations. Many SEP models exist or are in development using a wide variety of approaches and with differing goals. These include computationally intensive physics-based models, fast and light empirical models, machine learning-based models, and mixed-model approaches. The aim of this paper is to summarize all of the SEP models currently developed in the scientific community, including a description of model approach, inputs and outputs, free parameters, and any published validations or comparisons with data