Manufacturing technology faces challenges with new packages/process when confronting the need for high yields. Identifying product defects associated with the manufacturing process is a critical part of electronics manufacturing. In this project,we focus on how to use AXI to identify BGA Head-in-Pillow (HIP),which is challenging for AXI testing. Our goal is to help us understand the capabilities of current AXI machines.
For the study we used two boards exhibiting HIP defects with four types of AXI machines at four sites in Flextronics manufacturing,or vendor laboratory. The AXI machines used have different X-ray technologies: Laminography and Tomosynthesis. We collected three sets of data with AXI 1 machine (Laminography),and AXI 4 machines (Tomosynthesis); one set of data with AXI2 (Tomosynthesis); and 4 sets data for AXI3 (Tomosynthesis). We studied AXI measurement data with the different AXI Algorithm Threshold settings. The data indicated clearly that the Algorithm Threshold settings are very critical for detecting HIP,including open. The defective HIP pins are validated by using 2DX and CT scan.
The test data consist of Defects Escaped %,False call PPM and also Gage R & R. The AXI images for HIP pins,false call pins and defects escaped pins are presented in the paper. The 2DX and CT images are provided for identifying HIP type (shape and size).
Author(s)
Alejandro Castellanos,Adalberto Gutierrez,Gilberto Martin,Matthew Vandiver,Ranga Dematampitiya,Hung Le,Elliott Le,Phuong Chau,Hao Cui,An Qi Zhao,Wei Bing Qian,Fuqing Li,Jacky Yao,Jiyang Zhang,Leonard Brisan,Cristian Gurka,Shane Young,Johann Bruenner,Martin Novak,Nadarajan M Singaram,Zhen (Jane) Feng,David Geiger,Murad Kurwa