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Roy Welsch and Daniel Whitney. Frackleton, Conor J Leaders for Global Operations Program. Leaders for Global Operations Program at MIT Massachusetts Institute of Technology. Department of Mechanical Engineering Sloan School of Management n-us--- 2014-10-08T15:27:22Z 2014-10-08T15:27:22Z 2014 2014 http://hdl.handle.net/1721.1/90759 891375963 Thesis: M.B.A., Massachusetts Institute of Technology, Sloan School of Management, 2014. In conjunction with the Leaders for Global Operations Program at MIT. Thesis: S.M., Massachusetts Institute of Technology, Department of Mechanical Engineering, 2014. In conjunction with the Leaders for Global Operations Program at MIT. 5 Cataloged from PDF version of thesis. Includes bibliographical references (page 64). The 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. by Conor J. Frackleton. M.B.A. S.M. 72 pages eng Massachusetts Institute of Technology M.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. http://dspace.mit.edu/handle/1721.1/7582 Sloan School of Management. Mechanical Engineering. Leaders for Global Operations Program. Technology maturity analysis for assessing capacity and schedule risk of future automation projects Thesis application/pdf Publication unknown unknown <Publication xmlns="https://www.openaire.eu/cerif-profile/1.1/" id="fb7116e8-97ac-4a07-b055-5ada3eb0bda9"> <Type xmlns="https://www.openaire.eu/cerif-profile/vocab/COAR_Publication_Types">http://purl.org/coar/resource_type/c_1843</Type> <Language>eng</Language> <Title>Technology maturity analysis for assessing capacity and schedule risk of future automation projects</Title> <PublishedIn> <Publication> </Publication> </PublishedIn> <PublicationDate>2014</PublicationDate> <Authors> <Author> <DisplayName>Frackleton, Conor J</DisplayName> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> </Authors> <Editors> </Editors> <Publishers> <Publisher> <DisplayName>Massachusetts Institute of Technology</DisplayName> <OrgUnit /> </Publisher> </Publishers> <License>http://dspace.mit.edu/handle/1721.1/7582</License> <Keyword>Sloan School of Management.</Keyword> <Keyword>Mechanical Engineering.</Keyword> <Keyword>Leaders for Global Operations Program.</Keyword> <Abstract>The 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.</Abstract> <Access xmlns="http://purl.org/coar/access_right" > </Access> </Publication>