| contributor author | Bruno Agard | |
| contributor author | Andrew Kusiak | |
| date accessioned | 2017-05-09T00:13:35Z | |
| date available | 2017-05-09T00:13:35Z | |
| date copyright | August, 2004 | |
| date issued | 2004 | |
| identifier issn | 1087-1357 | |
| identifier other | JMSEFK-27822#627_1.pdf | |
| identifier uri | http://yetl.yabesh.ir/yetl/handle/yetl/130353 | |
| description abstract | The paper presents a model and an algorithm for selection of subassemblies based on the analysis of prior orders received from the customers. The parameters of this model are generated using association rules extracted by a data mining algorithm. The extracted knowledge is applied to construct a model for selection of subassemblies for timely delivery from the suppliers to the contractor. The proposed knowledge discovery and optimization framework integrates the concepts from product design and manufacturing efficiency. The ideas introduced in the paper are illustrated with an example and an automotive case study. | |
| publisher | The American Society of Mechanical Engineers (ASME) | |
| title | Data Mining for Subassembly Selection | |
| type | Journal Paper | |
| journal volume | 126 | |
| journal issue | 3 | |
| journal title | Journal of Manufacturing Science and Engineering | |
| identifier doi | 10.1115/1.1763182 | |
| journal fristpage | 627 | |
| journal lastpage | 631 | |
| identifier eissn | 1528-8935 | |
| keywords | Manufacturing | |
| keywords | Wire | |
| keywords | Algorithms | |
| keywords | Data mining AND Optimization | |
| tree | Journal of Manufacturing Science and Engineering:;2004:;volume( 126 ):;issue: 003 | |
| contenttype | Fulltext | |