標題: An efficient method for creating benchmark classifications for automatic workpiece classification systems
作者: Hsu, SH
Hsia, TC
Wu, MC
工業工程與管理學系
Department of Industrial Engineering and Management
關鍵字: automatic workpiece classification system;classification benchmarks;full-data classification;lean classification
公開日期: 1998
摘要: The usefulness of an automatic workpiece classification system depends primarily on the extent to tt which its classification results are consistent with users judgements. Thus, to evaluate the effectiveness of an automatic, classification system it is necessary to establish classification benchmarks based on users' judgements. Such benchmarks al are typically established by having subjects perform pair comparisons of all workpieces iir a set of sample workpieces. The result of such comparisons is called a full-data classification. However; when the number of sample workpieces is very large, such exhaustive comparisons become impratical. This paper proposes a more efficient method, called lean classification, in which data on comparisons between the samples and a small number of typical workpieces are used to infer the complete classification results. The proposed,method has been verified by using a small set of 36 sample workpieces and by computer simulation with medium to large sets of 100 to 800 sample workpieces. The results reveal that the method could produce a classification that was 71% consistent with the full-data classification while using only 10% of the total data.
URI: http://hdl.handle.net/11536/91
ISSN: 0268-3768
期刊: INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
Volume: 14
Issue: 7
起始頁: 481
結束頁: 494
顯示於類別:期刊論文


文件中的檔案:

  1. 000075299900004.pdf