2026-09-26T15:34:15Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/94072021-07-05T14:03:20Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023
Anna Thornton.
Chen, Tony J. (Tony Jeng-Horng), 1975-
Massachusetts Institute of Technology. Department of Mechanical Engineering
2005-08-22T18:07:59Z
2005-08-22T18:07:59Z
1999
1999
http://hdl.handle.net/1721.1/9407
43189226
Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 1999.
Includes bibliographical references (p. 73-75).
Over the last decade, the importance of quality has increased significantly. Quality improvement efforts involve mitigating the impact of manufacturing variation through robust design, statistical process control (SPC), and inspection. This thesis focuses on the last: how to choose an inspection plan to remove the most variation at the lowest cost. The optimal inspection plan balances the cost of inspection and rework against the cost of increased quality. This thesis describes an empirical analysis and prototype software that employs Monte Carlo simulation and simulated annealing to identify the optimal inspection plan. This thesis demonstrates the functionality of the theory and the software through an example from the aircraft industry.
by Tony J. Chen.
S.M.
80 p.
4690979 bytes
4690740 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
Mechanical Engineering
Quantitative selection of inspection plans for variation risk management
Thesis
application/pdf
Publication
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unknown
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