Methods to Reduce Backlogged Maintenance of Los Angeles Class Submarines

The United States Navy’s submarine fleet operates independently in high-risk situations around the globe. These missions are of vital importance to the nation’s national security, requiring the vessels to maintain very high standards of material condition and readiness. However, increased operationa...

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Main Author: Musselwhite, Steven Andrew
Other Authors: Sapsis, Themistoklis
Format: Thesis
Published: Massachusetts Institute of Technology 2022
Online Access:https://hdl.handle.net/1721.1/139425
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author Musselwhite, Steven Andrew
author2 Sapsis, Themistoklis
author_facet Sapsis, Themistoklis
Musselwhite, Steven Andrew
author_sort Musselwhite, Steven Andrew
collection MIT
description The United States Navy’s submarine fleet operates independently in high-risk situations around the globe. These missions are of vital importance to the nation’s national security, requiring the vessels to maintain very high standards of material condition and readiness. However, increased operational needs, personnel shortages in the civilian workforce, and other factors have resulted in a significant backlog in submarine maintenance. Submarines are governed by stricter standards than other naval assets, preventing them from deploying until required preventive maintenance items and inspections have been completed. This thesis investigates historical performance data to build predictive models for component failures that could be used to shift periodicities for preventive items and reduce the existing backlog. Test components from the Los Angeles class of attack submarines were chosen for this investigation. Non-parametric and parametric models are fitted to these components, providing quantitative methods to manage the risks associated with periodicity shifts. This process can identify components that consistently fail within the existing periodicity as well as those that have successfully operated beyond that point due to previous deferrals. This presents an opportunity to improve the efficiency of submarine maintenance, although the quality of the Navy’s records was identified as a potential limiting factor.
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spelling mit-1721.1/1394252022-01-15T03:28:17Z Methods to Reduce Backlogged Maintenance of Los Angeles Class Submarines Musselwhite, Steven Andrew Sapsis, Themistoklis Massachusetts Institute of Technology. Department of Mechanical Engineering The United States Navy’s submarine fleet operates independently in high-risk situations around the globe. These missions are of vital importance to the nation’s national security, requiring the vessels to maintain very high standards of material condition and readiness. However, increased operational needs, personnel shortages in the civilian workforce, and other factors have resulted in a significant backlog in submarine maintenance. Submarines are governed by stricter standards than other naval assets, preventing them from deploying until required preventive maintenance items and inspections have been completed. This thesis investigates historical performance data to build predictive models for component failures that could be used to shift periodicities for preventive items and reduce the existing backlog. Test components from the Los Angeles class of attack submarines were chosen for this investigation. Non-parametric and parametric models are fitted to these components, providing quantitative methods to manage the risks associated with periodicity shifts. This process can identify components that consistently fail within the existing periodicity as well as those that have successfully operated beyond that point due to previous deferrals. This presents an opportunity to improve the efficiency of submarine maintenance, although the quality of the Navy’s records was identified as a potential limiting factor. Nav.E. S.M. 2022-01-14T15:10:43Z 2022-01-14T15:10:43Z 2021-06 2021-06-29T19:28:17.350Z Thesis https://hdl.handle.net/1721.1/139425 In Copyright - Educational Use Permitted Copyright MIT http://rightsstatements.org/page/InC-EDU/1.0/ application/pdf Massachusetts Institute of Technology
spellingShingle Musselwhite, Steven Andrew
Methods to Reduce Backlogged Maintenance of Los Angeles Class Submarines
title Methods to Reduce Backlogged Maintenance of Los Angeles Class Submarines
title_full Methods to Reduce Backlogged Maintenance of Los Angeles Class Submarines
title_fullStr Methods to Reduce Backlogged Maintenance of Los Angeles Class Submarines
title_full_unstemmed Methods to Reduce Backlogged Maintenance of Los Angeles Class Submarines
title_short Methods to Reduce Backlogged Maintenance of Los Angeles Class Submarines
title_sort methods to reduce backlogged maintenance of los angeles class submarines
url https://hdl.handle.net/1721.1/139425
work_keys_str_mv AT musselwhitestevenandrew methodstoreducebackloggedmaintenanceoflosangelesclasssubmarines