2026-09-20T11:16:32Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/1390212022-01-15T03:40:57Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023
Freund, Daniel
Simchi-Levi, David
Rawden, Katherine Suzanne
Sloan School of Management
Massachusetts Institute of Technology. Department of Civil and Environmental Engineering
2022-01-14T14:45:07Z
2022-01-14T14:45:07Z
2021-06
2021-06-10T19:13:24.348Z
https://hdl.handle.net/1721.1/139021
0000-0002-0061-3734
Digital transformation has begun to infiltrate all industries, signifying the advent of a new era: the fourth industrial revolution Through the digital transformation of business processes, key bottlenecks that limit firm growth can be mitigated, allowing for unprecedented scalability, scope, and opportunities for learning.
The goals of this project are twofold within the value chain of a product family of absorbable sutures. The first goal is to provide an assessment of the driving motivations and structural transformation required for a medical device manufacturer to deploy business artificial intelligence (AI) and evolve into a digital firm. The second goal is to apply digital transformation methodology and machine learning (ML) to a proof of concept use case.
To accomplish the first goal, a road map was developed for the deployment of business AI and an assessment of the digital maturity of the suture value chain was conducted. Random forest and linear regression ML models were developed to assist in root cause analysis at the extrusion/orientation process step of the suture manufacturing process.
S.M.
M.B.A.
Massachusetts Institute of Technology
In Copyright - Educational Use Permitted
Copyright retained by author(s)
https://rightsstatements.org/page/InC-EDU/1.0/
Developing Business AI Implementation Methodology and Proof
of Concept ML Models to Improve Suture Quality at
Extrusion/Orientation
Thesis
application/pdf
Master
Master of Science in Civil and Environmental Engineering
Master of Business Administration
Publication
unknown
unknown
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<Abstract>Digital transformation has begun to infiltrate all industries, signifying the advent of a new era: the fourth industrial revolution Through the digital transformation of business processes, key bottlenecks that limit firm growth can be mitigated, allowing for unprecedented scalability, scope, and opportunities for learning.
The goals of this project are twofold within the value chain of a product family of absorbable sutures. The first goal is to provide an assessment of the driving motivations and structural transformation required for a medical device manufacturer to deploy business artificial intelligence (AI) and evolve into a digital firm. The second goal is to apply digital transformation methodology and machine learning (ML) to a proof of concept use case.
To accomplish the first goal, a road map was developed for the deployment of business AI and an assessment of the digital maturity of the suture value chain was conducted. Random forest and linear regression ML models were developed to assist in root cause analysis at the extrusion/orientation process step of the suture manufacturing process.</Abstract>
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