Clustering Data to Improve Packaging for the Semiconductor Industry

Semiconductor manufacturers are facing greater challenges because of complex manufacturing systems used and competitive business environment encountered. Improving the machine performance has been and will remain to be a critical role in deciding the success of a company. In this paper, we use the clustering, which belongs to one of data mining techniques, to classify the machines into groups given the machine performance record. The objective is to discover some previously unknown but may be interesting patterns related to improve performance. We integrate k-means and Self-Organizing Map (SOM) algorithm to cluster the machine data and show results in graphical form.

[1]  J. MacQueen.  Some methods for classification and analysis of multivariate observations , 1967 .

[2]  Sudipto Guha,et al.  ROCK: A Robust Clustering Algorithm for Categorical Attributes , 2000, Inf. Syst..

[3]  U. M. Feyyad.  Data mining and knowledge discovery: making sense out of data , 1996 .

[4]  Andreas Rudolph,et al.  Techniques of Cluster Algorithms in Data Mining , 2002, Data Mining and Knowledge Discovery.

[5]  Jiawei Han,et al.  Efficient and Effective Clustering Methods for Spatial Data Mining , 1994, VLDB.

[6]  Teuvo Kohonen,et al.  Self-Organizing Maps , 2010 .

[7]  Tian Zhang,et al.  BIRCH: an efficient data clustering method for very large databases , 1996, SIGMOD '96.

[8]  Anil K. Jain,et al.  Algorithms for Clustering Data , 1988 .

[9]  Anil K. Jain,et al.  Data clustering: a review , 1999, CSUR.

[10]  Omid Omidvar,et al.  Neural Networks and Pattern Recognition , 1997 .

[11]  Sudipto Guha,et al.  CURE: an efficient clustering algorithm for large databases , 1998, SIGMOD '98.

[12]  Vipin Kumar,et al.  Chameleon: Hierarchical Clustering Using Dynamic Modeling , 1999, Computer.

[13]  Ali S. Hadi,et al.  Finding Groups in Data: An Introduction to Chster Analysis , 1991 .

[14]  Padhraic Smyth,et al.  From Data Mining to Knowledge Discovery: An Overview , 1996, Advances in Knowledge Discovery and Data Mining.

[15]  Jiawei Han,et al.  Data Mining: Concepts and Techniques , 2000 .

[16]  R. J. Kuo,et al.  Integration of self-organizing feature map and K-means algorithm for market segmentation , 2002, Comput. Oper. Res..

[17]  Khurshid Ahmad,et al.  Choosing Feature Sets for Training and Testing Self-Organising Maps: A Case Study , 2001, Neural Computing & Applications.