Estimating change propagation risk using TRLs and system architecture

Thesis: S.M. in Engineering and Management, Massachusetts Institute of Technology, School of Engineering, System Design and Management Program, 2017.

Bibliografische gegevens
Hoofdauteur: Garg, Tushar
Andere auteurs: Steven D. Eppinger.
Formaat: Thesis
Taal:eng
Gepubliceerd in: Massachusetts Institute of Technology 2017
Onderwerpen:
Online toegang:http://hdl.handle.net/1721.1/110134
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author Garg, Tushar
author2 Steven D. Eppinger.
author_facet Steven D. Eppinger.
Garg, Tushar
author_sort Garg, Tushar
collection MIT
description Thesis: S.M. in Engineering and Management, Massachusetts Institute of Technology, School of Engineering, System Design and Management Program, 2017.
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spelling mit-1721.1/1101342022-01-12T19:58:09Z Estimating change propagation risk using TRLs and system architecture Garg, Tushar Steven D. Eppinger. System Design and Management Program. Massachusetts Institute of Technology. Engineering and Management Program System Design and Management Program. System Design and Management Program Engineering and Management Program. System Design and Management Program. Thesis: S.M. in Engineering and Management, Massachusetts Institute of Technology, School of Engineering, System Design and Management Program, 2017. Cataloged from PDF version of thesis. Includes bibliographical references (pages 27-28). Risk estimation is a key activity for product development and technology integration programs. There are a number of decision support tools that help project managers identify and mitigate risks in a project, however few explicitly consider the effects of architecture on risk. We propose a novel risk estimation framework that includes considerations of the system architecture. By starting with traditional project management literature, we define risk as a combination of likelihood and impact. We use Technology Readiness Levels as our measure for likelihood, and given that change propagates through interfaces, we used metrics that relate to connectivity to estimate impact. To analyze the connectivity, we model systems using networks of nodes and edges and calculate centrality metrics. This framework is applied to an industry example and we visualize the data in different formats to aid in analysis. The insights gained from this analysis are discussed, and we conclude that the risk estimation framework provides estimates that are in line with the experience of engineers at the company. by Tushar Garg. S.M. in Engineering and Management 2017-06-21T18:20:57Z 2017-06-21T18:20:57Z 2017 2017 Thesis http://hdl.handle.net/1721.1/110134 986999863 eng MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission. http://dspace.mit.edu/handle/1721.1/7582 28 pages application/pdf Massachusetts Institute of Technology
spellingShingle Engineering and Management Program.
System Design and Management Program.
Garg, Tushar
Estimating change propagation risk using TRLs and system architecture
title Estimating change propagation risk using TRLs and system architecture
title_full Estimating change propagation risk using TRLs and system architecture
title_fullStr Estimating change propagation risk using TRLs and system architecture
title_full_unstemmed Estimating change propagation risk using TRLs and system architecture
title_short Estimating change propagation risk using TRLs and system architecture
title_sort estimating change propagation risk using trls and system architecture
topic Engineering and Management Program.
System Design and Management Program.
url http://hdl.handle.net/1721.1/110134
work_keys_str_mv AT gargtushar estimatingchangepropagationriskusingtrlsandsystemarchitecture