2026-09-22T04:14:20Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/179122022-01-31T21:45:27Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023
Richard Roth, Randolph E. Kirchain, Jr. and Frank R. Field, III.
Akehurst, Colleen Beth, 1976-
Massachusetts Institute of Technology. Technology and Policy Program.
Massachusetts Institute of Technology. Engineering Systems Division
Technology and Policy Program
2005-06-02T19:09:31Z
2005-06-02T19:09:31Z
2004
2004
http://hdl.handle.net/1721.1/17912
56727063
Thesis (S.M.)--Massachusetts Institute of Technology, Engineering Systems Division, Technology and Policy Program, 2004.
Includes bibliographical references (p. 79-81).
Manufacturing facilities ramping up a new production process are faced with critical decisions, which determine the ability of that process to be cost efficient. Without quantitative analyses, these decisions are made with limited data and may cause manufacturing problems. Two critical decisions are examined in this research: what level of structured training to provide to employees and what cycle time to run when compared with the long-term optimal cycle time. By examining these decisions and their impact on two production metrics, unplanned equipment downtime and reject rate, a series of analyses are presented. A framework for conducting analyses is developed using Process Based Cost Modeling. This framework is applied to various automobile part manufacturing processes. The results indicate that production experience is critical for reducing the two performance metrics of unplanned downtime and reject rate. Additional analyses indicate that to achieve the best cycle times, a significant investment in structured training should be provided. Analytically determining the optimal cycle time is critical to improving production ramp-up because costs increase when running other cycle times. Future work would apply this framework to other manufacturing processes and gather additional data on the processes examined here.
by Colleen Beth Akehurst.
S.M.
81 p.
3101159 bytes
3100967 bytes
application/pdf
application/pdf
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
Technology and Policy Program.
The benefits of structured training on manufacturing process ramp-up : a process based cost model approach
Thesis
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<Abstract>Manufacturing facilities ramping up a new production process are faced with critical decisions, which determine the ability of that process to be cost efficient. Without quantitative analyses, these decisions are made with limited data and may cause manufacturing problems. Two critical decisions are examined in this research: what level of structured training to provide to employees and what cycle time to run when compared with the long-term optimal cycle time. By examining these decisions and their impact on two production metrics, unplanned equipment downtime and reject rate, a series of analyses are presented. A framework for conducting analyses is developed using Process Based Cost Modeling. This framework is applied to various automobile part manufacturing processes. The results indicate that production experience is critical for reducing the two performance metrics of unplanned downtime and reject rate. Additional analyses indicate that to achieve the best cycle times, a significant investment in structured training should be provided. Analytically determining the optimal cycle time is critical to improving production ramp-up because costs increase when running other cycle times. Future work would apply this framework to other manufacturing processes and gather additional data on the processes examined here.</Abstract>
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