File:Resilient Acquisition- Unlocking High-Velocity Learning with Model-Based Engineering to Deliver Capability to the Fleet Faster (IA resilientacquisi1094563181).pdf
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[edit]Resilient Acquisition: Unlocking High-Velocity Learning with Model-Based Engineering to Deliver Capability to the Fleet Faster
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| Author |
Rapp, Travis J. |
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| Title |
Resilient Acquisition: Unlocking High-Velocity Learning with Model-Based Engineering to Deliver Capability to the Fleet Faster |
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| Publisher |
Monterey, California. Naval Postgraduate School |
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| Description |
As the nation's security needs call for a growing naval fleet, the public private industrial base for construction and weapon system acquisition will be stressed to perform at a high level of operational excellence. Underperformance in defense acquisitions is found to be caused by complexity, uncertainty, and risk manifested through poor requirements that are unadaptable to the changing reality of the global security landscape. This thesis hypothesizes that use of model-based engineering (MBE) will enable the needed efficiency and responsiveness. This thesis demonstrates real-world and original examples of MBE consisting of digital tools motivated by the principles of traceability and high-velocity design iteration that collectively connect requirements to technical specifications in a model-centric format. Subjects: High-VelocityLearning,Model-BasedEngineering,NavalEngineering,MechanicalEngineering,SystemDesignandManagement |
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| Language | English | |
| Publication date | June 2019 | |
| Current location |
IA Collections: navalpostgraduateschoollibrary; fedlink |
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| Accession number |
resilientacquisi1094563181 |
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| Source | ||
| Permission (Reusing this file) |
This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States. | |
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| This file has been identified as being free of known restrictions under copyright law, including all related and neighboring rights. | ||
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| current | 09:17, 24 July 2020 |  | 1,275 × 1,650, 168 pages (12.02 MB) | Fæ (talk | contribs) | FEDLINK - United States Federal Collection resilientacquisi1094563181 (User talk:Fæ/IA books#Fork8) (batch 1993-2020 #26622) |
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