Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
478829 | European Journal of Operational Research | 2008 | 13 Pages |
Abstract
Defects on semiconductor wafers tend to cluster and the spatial defect patterns contain useful information about potential problems in the manufacturing process. This study proposes to use model-based clustering algorithms via Bayesian inferences for spatial defect pattern recognition on semiconductor wafers. These new algorithms can find the number of defect clusters as well as identify the pattern of each cluster automatically. They are capable of detecting curvilinear patterns, ellipsoidal patterns and nonuniform global defect patterns. Promising results have been obtained from simulation studies.
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Science (General)
Authors
Tao Yuan, Way Kuo,