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Massachusetts Institute of Technology

Assessing the impact of container marking implementation

Abstract

dc:description.abstract

Amgen is implementing new capabilities across the Amgen manufacturing network in order to code containers at the unit-level to reduce the possibility of mix-ups of unlabeled drug products. In order to prepare for the roll-out of these new capabilities, an assessment of the impact to throughput, packaging yield and eject rates was conducted. Discrete event simulation was utilized to assess the impact of implementing these new container marking capabilities on a vial inspection and packaging line at one of Amgen's key manufacturing sites. The impact assessment confirms that the new capabilities will have no impact to the throughput of the production line and minimal to no impact on packaging yield and eject rates. This assessment provides confidence that implementation can move forward without concerns of negative impacts to the production lines.

Degree

thesis:*
Department dc:contributor.department
Leaders for Global Operations Program at MIT
Grantor dc:publisher
Massachusetts Institute of Technology
Year dc:date.issued
2016

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Zielske, Iris Marie
Advisor dc:contributor.advisor
  • Jarrod Goentzel and Y. Karen Zheng.

Subjects

dc:subject × 4

Rights

dc:rights
Statement dc:rights
  • M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.
Language dc:language.iso
eng

Identifiers

dc:identifier.*
Handle dc:identifier.uri
http://hdl.handle.net/1721.1/105629
OAI identifier oai:identifier
oai:dspace.mit.edu:1721.1/105629

Chain of custody

source
Harvested from
MIT
Base URL
dspace.mit.edu/oai/request
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
citation

Zielske, Iris Marie. Assessing the impact of container marking implementation. Massachusetts Institute of Technology, 2016. http://hdl.handle.net/1721.1/105629