Please use this identifier to cite or link to this item: https://dair.nps.edu/handle/123456789/4899
Full metadata record
DC FieldValueLanguage
dc.contributor.authorRebecca DeCrescenzo, Mihiri Rajapaksa-
dc.date.accessioned2023-05-06T23:37:49Z-
dc.date.available2023-05-06T23:37:49Z-
dc.date.issued2023-05-01-
dc.identifier.citationAPAen_US
dc.identifier.urihttps://dair.nps.edu/handle/123456789/4899-
dc.descriptionSYM Presentationen_US
dc.description.abstractAs 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.en_US
dc.description.sponsorshipAcquisition Research Programen_US
dc.language.isoen_USen_US
dc.publisherAcquisition Research Programen_US
dc.relation.ispartofseriesAcquisition Management;SYM-AM-23-133-
dc.subjectAdditive Manufacturingen_US
dc.subjectDecision Scienceen_US
dc.subjectReadinessen_US
dc.subjectContracten_US
dc.titleLeveraging Machine Learning and AI to Identify Novel Additive Manufacturing Technological Capabilities to Improve Fleet Readinessen_US
dc.typePresentationen_US
Appears in Collections:Annual Acquisition Research Symposium Proceedings & Presentations

Files in This Item:
File Description SizeFormat 
SYM-AM-23-133.pdf859.62 kBAdobe PDFView/Open


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.