Digital Supply Chain Connectivity and Capacity Analysis for Strategic Production Planning in Biosurgery Oxidized Regenerated Cellulose

Ethicon, a subsidiary of Johnson & Johnson (J&J), is experiencing increased demand within its Oxidized Regenerative Cellulose (ORC) product line. This increase in demand is causing challenges within the current ORC value stream as production dynamics and manufacturing capacities are being stretched to meet growing consumer needs. In addition, the ORC digital data thread is disjointed across multiple enterprise resource planning (ERP) systems and various teams. Consequently, planning activities that support strategic investment decisions are increasingly burdensome and require a significant level of effort. This project analyzes and quantifies the ORC manufacturing process through a statistical lens and applies process flow modeling, descriptive statistics analysis, and optimization techniques to support strategic and tactical capacity planning. An optimization algorithm is presented that minimizes the revenue shortfall for Ethicon given current ORC manufacturing capacity and product demand profiles. This optimization algorithm is projected to minimize the shortfall in revenue to 11.8% of maximum expected revenue. 1Additionally, this project strives to connect Ethicon’s various channels of information flow within ORC manufacturing and build the digital thread using Microsoft’s PowerBI.

Name thesis:degree_name

Master

Department dc:contributor.department

Massachusetts Institute of Technology. Department of Mechanical Engineering

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2023

Author dc:creator

• Jiang, Justin

Advisors dc:contributor.advisor

• Roemer, Thomas
• Frey, Daniel

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/1721.1/151556

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/151556