Please use this identifier to cite or link to this item:
https://doi.org/10.1007/s001700050024
DC Field | Value | |
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dc.title | Conceptual design of fixtures using machine learning techniques | |
dc.contributor.author | Kumar, A.S. | |
dc.contributor.author | Subramaniam, V. | |
dc.contributor.author | Teck, T.B. | |
dc.date.accessioned | 2014-06-17T05:10:05Z | |
dc.date.available | 2014-06-17T05:10:05Z | |
dc.date.issued | 2000 | |
dc.identifier.citation | Kumar, A.S.,Subramaniam, V.,Teck, T.B. (2000). Conceptual design of fixtures using machine learning techniques. International Journal of Advanced Manufacturing Technology 16 (3) : 176-181. ScholarBank@NUS Repository. <a href="https://doi.org/10.1007/s001700050024" target="_blank">https://doi.org/10.1007/s001700050024</a> | |
dc.identifier.issn | 02683768 | |
dc.identifier.uri | http://scholarbank.nus.edu.sg/handle/10635/58029 | |
dc.description.abstract | Fixtures are work-holding devices which are used to locate and hold a workpiece during most of the machining operations. The design of a fixture is a complex and an intuitive process, which requires knowledge and experience. Automating the fixture design process is difficult and this is attributed to the problem of capturing the design knowledge. Recent advances in artificial intelligence, in particular in machine learning, have provided methods for capturing design knowledge. In this paper, an attempt to use machine learning for capturing the fixture design knowledge and using it for generating the conceptual design of fixtures automatically is presented with case studies. | |
dc.description.uri | http://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1007/s001700050024 | |
dc.source | Scopus | |
dc.type | Article | |
dc.contributor.department | MECHANICAL & PRODUCTION ENGINEERING | |
dc.description.doi | 10.1007/s001700050024 | |
dc.description.sourcetitle | International Journal of Advanced Manufacturing Technology | |
dc.description.volume | 16 | |
dc.description.issue | 3 | |
dc.description.page | 176-181 | |
dc.description.coden | IJATE | |
dc.identifier.isiut | NOT_IN_WOS | |
Appears in Collections: | Staff Publications |
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