scholarly journals Solder Joint Reliability Modeling by Sequential Artificial Neural Network for Glass Wafer Level Chip Scale Package

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 143494-143501 ◽  
Author(s):  
Cadmus C. A. Yuan ◽  
Chang-Chi Lee
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Solder Joint ◽  
Glass Wafer ◽  
Wafer Level ◽  
Solder Joint Reliability ◽  
Reliability Modeling ◽  
Joint Reliability ◽  
Chip Scale Package ◽  
Artificial Neural

Effects of Void, Crack, and PCB Thickness on the Solder Joint Reliability of Wafer-Level Chip-Scale Package (WLCSP) Assemblies

2002 ◽  
Author(s):  
John Lau ◽  
Yida Zou ◽  
Sergio Camerlo
Keyword(s):  
Solder Joint ◽  
Printed Circuit Board ◽  
Temperature Cycling ◽  
Circuit Board ◽  
J Integral ◽  
Wafer Level ◽  
Solder Joint Reliability ◽  
Printed Circuit ◽  
Joint Reliability ◽  
Chip Scale Package

The creep analyses of solder-bumped wafer-level chip-scale package (WLCSP) on printed circuit board (PCB) subjected to temperature cycling loading are presented. Emphasis is placed on the effects of PCB thickness on the solder joint reliability of the WLCSP assembly. Also, the effects of crack-length on the crack tip characteristics such as the J-integral in the WLCSP solder joint are studied by the fracture mechanics method. Finally, the effects of voids on the crack growth in the WLCSP solder joint are investigated.

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