The CORE team has developed a machine learning model called VAMPS (Vital Asset Material Point System) in order to predict the vitality of material to shipyard completion. VAMPS assigns a point system to each material, focusing on a material’s inherent attributes, intended purpose, and historical performance of wholesale respond.
The model produces one of three outcomes:
(1) a material is recommended for stock or prepositioning,
(2) if a material cannot be stocked, it is recommended to be ordered prior to the start of an availability, or
(3) the material can be ordered any point before or during an avail.
VAMPS can be applied on multiple scenarios, leveraging historical lessons learned from each of the shipyard’s material demands, prioritizing materials under the Bill of Materials (BOM) listing in support of wholesale posture planning, validating existing retail inventory at the shipyards, or recommending a list of materials for allowance review in support of ongoing or completed avails.
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