Developing Business AI Implementation Methodology and Proof of Concept ML Models to Improve Suture Quality at Extrusion/Orientation

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.

Name thesis:degree_name

Master

Department dc:contributor.department

Sloan School of Management

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2021

Author dc:creator

• Rawden, Katherine Suzanne

Advisors dc:contributor.advisor

• Freund, Daniel
• Simchi-Levi, David

Statement dc:rights

• In Copyright - Educational Use Permitted
• Copyright retained by author(s)

Licence dc:rights.uri

• https://rightsstatements.org/page/InC-EDU/1.0/

Handle dc:identifier.uri

https://hdl.handle.net/1721.1/139021

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/139021