Applying Hierarchical Clustering to Discover the Typical Process Route

Abstract:

Article Preview

In order to discover the typical process route (TPR) in the Computer Aided Process Planning (CAPP) database, Hierarchical Clustering algorithm is adopted. A mathematics model based on the data matrix was built to describe the process route (PR). On the base of the operation code, the distance between operations, between the PRs, between clusters were measured to evaluate the PR similarity. Then, the PR clusters were eventually merged by the hierarchical clustering algorithm. Three methods are listed to confirm the clustering granularity that determines the clustering result. This TPR discovery method is successfully applied to discover the axle sleeves’ TPR.

Info:

Periodical:

Materials Science Forum (Volumes 532-533)

Edited by:

Chengyu Jiang, Geng Liu, Dinghua Zhang and Xipeng Xu

Pages:

949-952

Citation:

S. N. Liu et al., "Applying Hierarchical Clustering to Discover the Typical Process Route", Materials Science Forum, Vols. 532-533, pp. 949-952, 2006

Online since:

December 2006

Export:

Price:

$38.00

[1] S.C. Park: Computer-Aided Design, Vol. 35 (2003), p.1109.

[2] A.K. Jain, A. Topchy, M.H.C. Law and J.M. Buhmann: Proceedings of the 17th International Conference on Pattern Recognition, Vol. 1 (2004), p.260.

[3] S. Seal, S. Komarina and S. Aluru: Information Processing Letters, Vol. 93 (2005), p.143.

[4] W. Gao, G. Yin and E. Cheng: Computer Integrated Manufacturing System, Vol. 10 (2004), p.843.

[5] P.A. Vijaya, M. Narasimha Murty and D.K. Subramanian: Pattern Recognition Letters, Vol. 25 (2004), p.505.

[6] S. Oh and J. Kim: Information Processing Letters, Vol. 91 (2004), p.135.

[7] J. Han and M. Kamber: Data Mining: Concepts and Techniques (Higher Education Press, China 2001).

Fetching data from Crossref.
This may take some time to load.