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dc.contributor.advisorBryan R. Moser and Joel Harbour.en_US
dc.contributor.authorPowers, Roxane (Roxane Bloodworth)en_US
dc.contributor.otherSystem Design and Management Program.en_US
dc.date.accessioned2016-09-27T15:14:32Z
dc.date.available2016-09-27T15:14:32Z
dc.date.copyright2016en_US
dc.date.issued2016en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/104386
dc.descriptionThesis: Nav. E., Massachusetts Institute of Technology, Department of Mechanical Engineering, 2016.en_US
dc.descriptionThesis: S.M. in Engineering and Management, Massachusetts Institute of Technology, School of Engineering, Institute for Data, Systems, and Society, System Design and Management Program, 2016.en_US
dc.descriptionCataloged from PDF version of thesis.en_US
dc.descriptionIncludes bibliographical references (pages 85-87).en_US
dc.description.abstractSince the early 2000's, the US Navy has endeavored to decrease the Total Ownership Cost (TOC) of their ships through a decrease in Operating and Support costs. This led to a large-scale effort by ship program managers to decrease crew size on current and prospective ships. Also during this time period, the rapid-onset improvement of technology led to the increase and complexity of automated systems and equipment installed on ships. These combining trends have caused ships to evolve from a fully manually operated system into a socio-technical system. But does increasing automation to support minimally manned ships lead to the expected performance? To answer this question, a thorough understanding of how the Navy currently determines its manpower requirements was obtained. The purpose was to discover the driving factors that influence manpower requirements, which are mission, installed systems, maintenance and training. Next, the process that the Navy uses to develop and manage technology was explored. The purpose was to discern the driving factors that influence technology selection, which are capability, maturity and cost. Since the Defense Acquisition System (DAS) is the framework that intersects manpower requirements, technology selection and ship design, a brief overview of DAS is given. Using key acquisition documents from DDG-51, LCS, and DDG-1000 programs, the selection, classification and implementation of automated technology on these platforms were explored. This data was then combined with the baseline manpower model to highlight key manpower and automation strategies for each platform and then study the resulting performance. From these case studies, it was determined that automation as a manpower reduction strategy gives mixed cost and readiness performance results. Although automation leads to lower manpower costs, increases in maintenance, training and shore support also occur. Some of these costs were offset through the use of human system integration early in the ship design, however, the maintenance and training costs of high-degree-automation systems was higher than estimated.en_US
dc.description.statementofresponsibilityby Roxane Powers.en_US
dc.format.extentxiv, 98 pagesen_US
dc.language.isoengen_US
dc.publisherMassachusetts Institute of Technologyen_US
dc.rightsM.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.en_US
dc.rights.urihttp://dspace.mit.edu/handle/1721.1/7582en_US
dc.subjectInstitute for Data, Systems, and Society.en_US
dc.subjectMechanical Engineering.en_US
dc.subjectEngineering Systems Division.en_US
dc.subjectSystem Design and Management Program.en_US
dc.titleAutomation as a manpower reduction strategy in navy shipsen_US
dc.typeThesisen_US
dc.description.degreeNav. E.en_US
dc.description.degreeS.M. in Engineering and Managementen_US
dc.contributor.departmentSystem Design and Management Program.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Mechanical Engineering
dc.contributor.departmentMassachusetts Institute of Technology. Engineering Systems Division
dc.contributor.departmentMassachusetts Institute of Technology. Institute for Data, Systems, and Society
dc.identifier.oclc958163875en_US


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