2026-09-21T18:22:50Zhttps://dspace.mit.edu/server/oai/request

oai:dspace.mit.edu:1721.1/1556262024-07-11T03:30:31Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023

Rebentisch, Eric Vidhate, Chetan System Design and Management Program. 2024-07-10T20:20:18Z 2024-07-10T20:20:18Z 2024-05 2024-06-11T19:54:16.787Z https://hdl.handle.net/1721.1/155626 This thesis presents an integrated model for analyzing product configuration complexity and cost, aiming to provide a comprehensive framework for decision-making in product configuration management. The research begins with a literature review to identify relevant complexity metrics, narrowing down to two primary metrics: structural and organizational complexity. The selected metrics are integrated into a hybrid model that conceptualizes product configuration complexity as a function of these factors. The model incorporates mathematical formulations for assessing structural and organizational complexities, allowing for a nuanced understanding of the challenges inherent in product configuration. Furthermore, a cost model is developed to quantify the financial implications of product configuration decisions, considering factors such as transport, assembly, and quality control costs. The model is applied to hypothetical scenarios, demonstrating utility in informing decision-making processes within original equipment manufacturers (OEMs). Future work is proposed to enhance the model by incorporating risk and uncertainties, conducting cost-benefit analyses, and refining the algorithm for optimal performance. Overall, this thesis contributes to the advancement of product configuration management practices by providing a comprehensive framework for analyzing complexity and cost in product configuration. S.M. Massachusetts Institute of Technology In Copyright - Educational Use Permitted Copyright retained by author(s) https://rightsstatements.org/page/InC-EDU/1.0/ Measuring the product configuration complexity and cost for mass-customization of automobiles: A qualitative and quantitative study of the product variant complexity, its associated cost Thesis application/pdf Master Master of Science in Engineering and Management Publication unknown unknown <Publication xmlns="https://www.openaire.eu/cerif-profile/1.1/" id="8978aefa-cebe-4206-9e01-f45d6c96dace"> <Type xmlns="https://www.openaire.eu/cerif-profile/vocab/COAR_Publication_Types">http://purl.org/coar/resource_type/c_1843</Type> <Title>Measuring the product configuration complexity and cost for mass-customization of automobiles: A qualitative and quantitative study of the product variant complexity, its associated cost</Title> <PublishedIn> <Publication> </Publication> </PublishedIn> <PublicationDate>2024-05</PublicationDate> <Authors> <Author> <DisplayName>Vidhate, Chetan</DisplayName> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> </Authors> <Editors> </Editors> <Publishers> <Publisher> <DisplayName>Massachusetts Institute of Technology</DisplayName> <OrgUnit /> </Publisher> </Publishers> <License>https://rightsstatements.org/page/InC-EDU/1.0/</License> <Abstract>This thesis presents an integrated model for analyzing product configuration complexity and cost, aiming to provide a comprehensive framework for decision-making in product configuration management. The research begins with a literature review to identify relevant complexity metrics, narrowing down to two primary metrics: structural and organizational complexity. The selected metrics are integrated into a hybrid model that conceptualizes product configuration complexity as a function of these factors. The model incorporates mathematical formulations for assessing structural and organizational complexities, allowing for a nuanced understanding of the challenges inherent in product configuration. Furthermore, a cost model is developed to quantify the financial implications of product configuration decisions, considering factors such as transport, assembly, and quality control costs. The model is applied to hypothetical scenarios, demonstrating utility in informing decision-making processes within original equipment manufacturers (OEMs). Future work is proposed to enhance the model by incorporating risk and uncertainties, conducting cost-benefit analyses, and refining the algorithm for optimal performance. Overall, this thesis contributes to the advancement of product configuration management practices by providing a comprehensive framework for analyzing complexity and cost in product configuration.</Abstract> <Access xmlns="http://purl.org/coar/access_right" > </Access> </Publication>