| dc.contributor.advisor |
Ding, Yu |
en_US |
| dc.creator |
Kim, Pansoo |
en_US |
| dc.date.accessioned |
2004-11-15T19:45:40Z |
|
| dc.date.available |
2004-11-15T19:45:40Z |
|
| dc.date.created |
2004-08 |
en_US |
| dc.date.issued |
2004-11-15T19:45:40Z |
|
| dc.identifier.uri |
http://handle.tamu.edu/1969.1/1076 |
|
| dc.description.abstract |
This dissertation presents a methodology for the near optimal design of fixture layouts in multi-station assembly processes. An optimal fixture layout improves the robustness of a fixture system, reduces product variability and leads to manufacturing cost reduction. Three key aspects of the multi-station fixture layout design are addressed: a multi-station variation propagation model, a quantitative measure of fixture design, and an effective and efficient optimization algorithm. Multi-station design may have high dimensions of design space, which can contain a lot of local optima. In this dissertation, I investigated two algorithms for optimal fixture layout designs. The first algorithm is an exchange algorithm, which was originally developed in the research of optimal experimental designs. I revised the exchange routine so that it can remarkably reduce the computing time without sacrificing the optimal values. The second algorithm uses data-mining methods such as clustering and classification. It appears that the data-mining method can find valuable design selection rules that can in turn help to locate the optimal design efficiently. Compared with other non-linear optimization algorithms such as the simplex search method, simulated annealing, genetic algorithm, the data-mining method performs the best and the revised exchange algorithm performs comparably to simulated annealing, but better than the others. A four-station assembly process for a sport utility vehicle (SUV) side frame is used throughout the dissertation to illustrate the relevant concepts and the resulting methodology. |
en_US |
| dc.description.provenance |
Made available in DSpace on 2004-11-15T19:45:40Z (GMT). No. of bitstreams: 2
etd-tamu-2004B-INEN-Kim-2.pdf: 892365 bytes, checksum: 592e79f19621967c565e346a7c8c6a9b (MD5)
etd-tamu-2004B-INEN-Kim-2.pdf.txt: 140040 bytes, checksum: 7048ec324fda367c586f3222bb9e54a3 (MD5) |
en |
| dc.format.extent |
892365 bytes |
|
| dc.format.extent |
140040 bytes |
|
| dc.format.medium |
electronic |
en_US |
| dc.format.mimetype |
application/pdf |
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| dc.format.mimetype |
text/plain |
|
| dc.language.iso |
en_US |
en_US |
| dc.publisher |
Texas A&M University |
en_US |
| dc.subject |
Fixture Layout Design |
en_US |
| dc.subject |
Data-mining Method |
en_US |
| dc.subject |
Revised Exchange Algorithm |
en_US |
| dc.subject |
E-optimality |
en_US |
| dc.title |
Near optimal design of fixture layouts in multi-station assembly processes |
en_US |
| thesis.degree.department |
Industrial Engineering |
en_US |
| thesis.degree.discipline |
Industrial Engineering |
en_US |
| thesis.degree.grantor |
Texas A&M University |
en_US |
| thesis.degree.name |
Ph. D. |
en_US |
| thesis.degree.level |
Doctoral |
en_US |
| dc.contributor.committeeMember |
Banerjee, Amarnath |
en_US |
| dc.contributor.committeeMember |
Curry, Guy L. |
en_US |
| dc.contributor.committeeMember |
Wang, Jyhwen |
en_US |
| dc.type.genre |
Electronic Dissertation |
en_US |
| dc.type.material |
text |
en_US |
| dc.format.digitalOrigin |
born digital |
en_US |
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