Evaluating Strategies for Wide Scale Replacement of Human Inspection with Machine Vision

A stable and cost-effective workforce is key to manufacturing life-saving medical devices. However, an ongoing global labor shortage is causing national economic challenges and causing companies to have significant workforce shortages, delaying operations and production activities. Additionally, human visual inspections of medical devices are less reliable and effective than new technological inspections with machine and artificial intelligence vision systems. This research explores the efficiency of human visual inspections, the impact new technology, such as machine and AI vision, can add, how to lead technological change, and an approach to implementing this change at a medical device manufacturing company. Specifically, it examines best practices and a specific strategy for identifying machine and AI vision opportunities at a large manufacturing company where quality is extremely important. It also examines strategies to quickly identify improvement areas and get manufacturing excited about new technology. Finally, it compares a traditional field visit approach to a data driven opportunity identification approach. Ultimately, it proposes a data-driven approach using visual tools to communicate opportunities to management in order to get the buy-in to proceed with these technological improvements.

Name thesis:degree_name

Master

Department dc:contributor.department

Sloan School of Management

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2022

Author dc:creator

• Sakerka, Lauren

Advisors dc:contributor.advisor

• Welsch, Roy
• 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/1721.1/146709

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/146709