Please use this identifier to cite or link to this item: https://dair.nps.edu/handle/123456789/4839
Title: Leveraging Machine Learning and AI to Identify Novel Additive Manufacturing Technological Capabilities to Improve Fleet Readiness
Authors: Rebecca DeCrescenzo, Mihiri Rajapaksa
Keywords: Additive Manufacturing
Decision Science
Readiness
Fleet
Contract
Issue Date: 1-May-2023
Publisher: Acquisition Research Program
Citation: APA
Series/Report no.: Acquisition Management;SYM-AM-23-071
Abstract: As competition between the United States and adversarial nations intensifies, the U.S. Navy faces a challenge to maintain advantages in the maritime domain. While the outcome of this competition will depend on many factors; one critical factor will be the speed and agility of the U.S. Navy to sustain the Navy’s operational availability (Ao). However, current logistics, supply chain, and manufacturing capabilities seem unable to meet the current demands of the Fleet. One technology that could support this is additive manufacturing (AM). Leveraging AM technologies to manufacture long lead time and high demand parts will enhance readiness and reduce logistic burdens. What seems certain is that the country that leverages AM technology the fastest can gain and maintain a technological lead. AM technology can augment traditional manufacturing techniques. Since some commercial practices must be modified to meet military requirements, this study looks at the current investment landscape across the U.S. Government (USG) in the AM technology space to see what AM USG contracts are available now across to explore potential contracting actions. This study identifies the organizations developing cutting edge AM technology that can be used by the U.S. Navy today to improve overall Fleet readiness.
Description: Proceedings Paper
URI: https://dair.nps.edu/handle/123456789/4839
Appears in Collections:Annual Acquisition Research Symposium Proceedings & Presentations

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