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dc.contributor.advisorRoy Welsch and Daniel Whitney.en_US
dc.contributor.authorFrackleton, Conor Jen_US
dc.contributor.otherLeaders for Global Operations Program.en_US
dc.coverage.spatialn-us---en_US
dc.date.accessioned2014-10-08T15:27:22Z
dc.date.available2014-10-08T15:27:22Z
dc.date.copyright2014en_US
dc.date.issued2014en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/90759
dc.descriptionThesis: M.B.A., Massachusetts Institute of Technology, Sloan School of Management, 2014. In conjunction with the Leaders for Global Operations Program at MIT.en_US
dc.descriptionThesis: S.M., Massachusetts Institute of Technology, Department of Mechanical Engineering, 2014. In conjunction with the Leaders for Global Operations Program at MIT.en_US
dc.description5en_US
dc.descriptionCataloged from PDF version of thesis.en_US
dc.descriptionIncludes bibliographical references (page 64).en_US
dc.description.abstractThe need to improve risk assessment methods for automation projects within United States manufacturers exists due to a shift toward increased in factory automation stemming from industry pressure to reduce manufacturing costs and increase production rates. This study explores the hypothesis that a risk assessment method, based on technology maturity analysis, can be used to reduce the time to decision, reduce the influence of personal bias, and improve the estimation of risk impact when evaluating proposed automation systems. The risk assessment method is based on the Technology Readiness Level (TRL) framework, coupled with a mathematical simulation of the manufacturing process. During the pilot implementation, a team of evaluators gathered data to create a process simulation, assessed the TRLs of automation proposals, and analyzed the risk of each proposal. After concluding the pilot, the evaluation team was interviewed to determine the success of the risk assessment method. The interviews revealed that the method resulted in a faster time to decision and improved estimations of risk, but failed to significantly reduce the influence of personal bias during the evaluation process.en_US
dc.description.statementofresponsibilityby Conor J. Frackleton.en_US
dc.format.extent72 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.subjectSloan School of Management.en_US
dc.subjectMechanical Engineering.en_US
dc.subjectLeaders for Global Operations Program.en_US
dc.titleTechnology maturity analysis for assessing capacity and schedule risk of future automation projectsen_US
dc.typeThesisen_US
dc.description.degreeM.B.A.en_US
dc.description.degreeS.M.en_US
dc.contributor.departmentLeaders for Global Operations Program at MITen_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Mechanical Engineering
dc.contributor.departmentSloan School of Management
dc.identifier.oclc891375963en_US


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