The Performance Advancement of Test Algorithm Using Neural Network for Semiconductor Packages

Abstract:

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Availability of defect test algorithm that recognizes exact and standardized defect information in order to fundamentally resolve generated defects in industrial sites by giving artificial intelligence to SAT(Scanning Acoustic Tomograph), which previously depended on operator’s decision, to find various defect information in a semiconductor package, to decide defect pattern, to reduce personal errors and then to standardize the test process was verified. In order to apply the algorithm to the lately emerging Neural Network theory, various weights were used to derive results for performance advancement plans of the defect test algorithm that promises excellent field applicability.

Info:

Periodical:

Key Engineering Materials (Volumes 261-263)

Edited by:

Kikuo Kishimoto, Masanori Kikuchi, Tetsuo Shoji and Masumi Saka

Pages:

411-416

DOI:

10.4028/www.scientific.net/KEM.261-263.411

Citation:

J. Y. Kim et al., "The Performance Advancement of Test Algorithm Using Neural Network for Semiconductor Packages", Key Engineering Materials, Vols. 261-263, pp. 411-416, 2004

Online since:

April 2004

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Price:

$35.00

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