{"id":{"repo_id":"mit","oai_identifier":"oai:dspace.mit.edu:1721.1/78484"},"canonical_url":"https://search.dev.ndltd.org/etd/mit/oai:dspace.mit.edu:1721.1/78484","repository":{"repo_id":"mit","name":"MIT","base_url":"https://dspace.mit.edu/oai/request"},"display":{"title":"Analytic framework for TRL-based cost and schedule models","abstract":"Many government agencies have adopted the Technology Readiness Level (TRL) scale to help improve technology development management under ever increasing cost, schedule, and complexity constraints. Many TRL-based cost and schedule models have been developed to monitor technology maturation, mitigate program risk, characterize TRL transition times, or model schedule and cost risk for individual technologies as well technology systems and portfolios. In this thesis, we develop a 4-level classification of TRL models based on the often-implicit assumptions they make. For each level, we clarify the assumption, we list all supporting theoretical and empirical evidence, and then we use the same assumption to propose alternative or improved models whenever possible. Our results include a justification of the GAO's recommendations on TRL, two new methodologies for robust estimation of transition variable medians and for forecasting TRL transition variables using historical data, and a set of recommendations for TRL-based regression models.","abstract_html":"Many government agencies have adopted the Technology Readiness Level (TRL) scale to help improve technology development management under ever increasing cost, schedule, and complexity constraints. Many TRL-based cost and schedule models have been developed to monitor technology maturation, mitigate program risk, characterize TRL transition times, or model schedule and cost risk for individual technologies as well technology systems and portfolios. In this thesis, we develop a 4-level classification of TRL models based on the often-implicit assumptions they make. For each level, we clarify the assumption, we list all supporting theoretical and empirical evidence, and then we use the same assumption to propose alternative or improved models whenever possible. Our results include a justification of the GAO's recommendations on TRL, two new methodologies for robust estimation of transition variable medians and for forecasting TRL transition variables using historical data, and a set of recommendations for TRL-based regression models.","abstract_has_math":false,"creators":["El-Khoury, Bernard"],"institution":"Massachusetts Institute of Technology","degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":"Massachusetts Institute of Technology. Engineering Systems Division.","school":null,"contributors":[],"advisors":["C. Robert Kenley and Deborah Nightingale."],"committee_chairs":[],"committee_members":[],"year":2012,"date_issued":"2012","date_published":"2012","updated_at":"2026-07-22T22:21:56Z","subjects":["Engineering Systems Division.","Technology and Policy Program."],"languages":["eng"],"rights":["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."],"rights_urls":["http://dspace.mit.edu/handle/1721.1/7582"],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/1721.1/78484","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["C. 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Many TRL-based cost and schedule models have been developed to monitor technology maturation, mitigate program risk, characterize TRL transition times, or model schedule and cost risk for individual technologies as well technology systems and portfolios. In this thesis, we develop a 4-level classification of TRL models based on the often-implicit assumptions they make. For each level, we clarify the assumption, we list all supporting theoretical and empirical evidence, and then we use the same assumption to propose alternative or improved models whenever possible. Our results include a justification of the GAO's recommendations on TRL, two new methodologies for robust estimation of transition variable medians and for forecasting TRL transition variables using historical data, and a set of recommendations for TRL-based regression models."]},{"key":"dc:description.degree","label":"Dc Description Degree","values":["S.M.in Technology and Policy"]},{"key":"dc:title","label":"Title","values":["Analytic framework for TRL-based cost and schedule models"]}]}],"canonical_facts":{"dc:contributor.advisor":["C. Robert Kenley and Deborah Nightingale."],"dc:contributor.department":["Massachusetts Institute of Technology. Engineering Systems Division.","Massachusetts Institute of Technology. Technology and Policy Program."],"dc:contributor.other":["Massachusetts Institute of Technology. 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In this thesis, we develop a 4-level classification of TRL models based on the often-implicit assumptions they make. For each level, we clarify the assumption, we list all supporting theoretical and empirical evidence, and then we use the same assumption to propose alternative or improved models whenever possible. Our results include a justification of the GAO's recommendations on TRL, two new methodologies for robust estimation of transition variable medians and for forecasting TRL transition variables using historical data, and a set of recommendations for TRL-based regression models."],"dc:description.degree":["S.M.in Technology and Policy"],"dc:identifier.uri":["http://hdl.handle.net/1721.1/78484"],"dc:language.iso":["eng"],"dc:publisher":["Massachusetts Institute of Technology"],"dc:rights":["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."],"dc:rights.uri":["http://dspace.mit.edu/handle/1721.1/7582"],"dc:subject":["Engineering Systems Division.","Technology and Policy Program."],"dc:title":["Analytic framework for TRL-based cost and schedule models"],"dc:type":["Thesis"]},"updated_at":"2026-07-22T22:21:56Z"}