2026-09-20T09:55:51Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/1467052022-12-01T03:26:49Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023
Roemer, Thomas
Youcef-Toumi, Kamal
Tresansky, Andrew C.
Massachusetts Institute of Technology. Department of Mechanical Engineering
Sloan School of Management
2022-11-30T19:42:33Z
2022-11-30T19:42:33Z
2022-05
2022-08-25T19:15:51.736Z
https://hdl.handle.net/1721.1/146705
Clinical trials final product manufacturing is a high-mix low-volume process that is difficult to automate and consequently highly manual. Furthermore, automation technologies often require substantial capital investments, and it is desirable to evaluate them in-silico prior to major capital outlays. This project used Simio (a modeling software) to develop a model of clinical trial autoinjector labeling and packaging which was used to identify candidate steps for automation. Then prototype solutions were developed for the candidate steps, data collected from the prototypes, and analyzed using the same Simio model to determine displacement or productivity effects. These economic effects were then analyzed using a discounted cash flow/net present value analysis, and further analyzed using real options analysis. Finally, this project aimed to codify the model-identify-prototype-model process used in this project for application to other potential automation projects. This project identified up to $380k of combined positive NPV between two automation projects given certain utilization assumptions.
S.M.
M.B.A.
Massachusetts Institute of Technology
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https://rightsstatements.org/page/InC-EDU/1.0/
Assessment and Operationalization of Automation in Final Product Manufacturing
Thesis
application/pdf
Master
Master of Science in Mechanical Engineering
Master of Business Administration
Publication
unknown
unknown
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<Abstract>Clinical trials final product manufacturing is a high-mix low-volume process that is difficult to automate and consequently highly manual. Furthermore, automation technologies often require substantial capital investments, and it is desirable to evaluate them in-silico prior to major capital outlays. This project used Simio (a modeling software) to develop a model of clinical trial autoinjector labeling and packaging which was used to identify candidate steps for automation. Then prototype solutions were developed for the candidate steps, data collected from the prototypes, and analyzed using the same Simio model to determine displacement or productivity effects. These economic effects were then analyzed using a discounted cash flow/net present value analysis, and further analyzed using real options analysis. Finally, this project aimed to codify the model-identify-prototype-model process used in this project for application to other potential automation projects. This project identified up to $380k of combined positive NPV between two automation projects given certain utilization assumptions.</Abstract>
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