2026-09-19T18:11:33Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/922262022-01-28T15:12:16Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023
Roy Welsch and Jung-Hoon Chun.
Bellows, William D. (William Devereaux)
Leaders for Global Operations Program.
Leaders for Global Operations Program at MIT
Massachusetts Institute of Technology. Department of Mechanical Engineering
Sloan School of Management
2014-12-08T18:57:49Z
2014-12-08T18:57:49Z
2014
2014
http://hdl.handle.net/1721.1/92226
897472041
Thesis: S.M., Massachusetts Institute of Technology, Department of Mechanical Engineering, 2014. In conjunction with the Leaders for Global Operations Program at MIT.
Thesis: M.B.A., Massachusetts Institute of Technology, Sloan School of Management, 2014. In conjunction with the Leaders for Global Operations Program at MIT.
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 57-58).
During manufacturing scale-up of a new product, new failure modes often surface which require corrective action. However, as production numbers of an insulin injection device pass 200 million per year, testing continues to find sub-assemblies with too-high injection forces, seemingly at random. Up until now, no corrective action has been effective in preventing these problems. These non-conforming sub-assemblies cause batches to be rejected, reducing the production yield at Sanofi's Site Frankfurt Devices (SFD) production facility. This thesis describes the current state of rejected batch problem solving and explores the application of new methods to better understand the root problems and improve the process. Frequency spectra analysis of testing data using the Fast Fourier Transform (FFT), combined with device physics, identified the key interaction points within the sub-assemblies. This model of part interactions has been verified through testing of purpose-built defective pieces and examination of defective parts. The verified model was then used to identify which components within sub-assemblies cause non-conformances. The root causes of several failure codes were determined, and results were further confirmed by rebuilding and retesting subassemblies with the identified problem components. These results confirm the usefulness of this novel application of frequency analysis to a new field of industrial troubleshooting. Various improvement and control methods are explored and next steps recommended for Sanofi to further improve quality control processes and thereby the production yield. The opinions expressed herein are solely those of the author and do not necessarily reflect those of Sanofi S.A.
by William D. Bellows.
S.M.
M.B.A.
63 pages
eng
Massachusetts Institute of Technology
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.
http://dspace.mit.edu/handle/1721.1/7582
Mechanical Engineering.
Sloan School of Management.
Leaders for Global Operations Program.
Analysis of randomly occurring high injection forces in an insulin delivery device
Thesis
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<Abstract>During manufacturing scale-up of a new product, new failure modes often surface which require corrective action. However, as production numbers of an insulin injection device pass 200 million per year, testing continues to find sub-assemblies with too-high injection forces, seemingly at random. Up until now, no corrective action has been effective in preventing these problems. These non-conforming sub-assemblies cause batches to be rejected, reducing the production yield at Sanofi's Site Frankfurt Devices (SFD) production facility. This thesis describes the current state of rejected batch problem solving and explores the application of new methods to better understand the root problems and improve the process. Frequency spectra analysis of testing data using the Fast Fourier Transform (FFT), combined with device physics, identified the key interaction points within the sub-assemblies. This model of part interactions has been verified through testing of purpose-built defective pieces and examination of defective parts. The verified model was then used to identify which components within sub-assemblies cause non-conformances. The root causes of several failure codes were determined, and results were further confirmed by rebuilding and retesting subassemblies with the identified problem components. These results confirm the usefulness of this novel application of frequency analysis to a new field of industrial troubleshooting. Various improvement and control methods are explored and next steps recommended for Sanofi to further improve quality control processes and thereby the production yield. The opinions expressed herein are solely those of the author and do not necessarily reflect those of Sanofi S.A.</Abstract>
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