Open AccessEnhanced Die Attach Process Defect Recognition on QFN Leadframe Packages
Author(s) -
Marque Ryan Salcedo,
Alyssa Grace S. Gablan,
Jerome J. Dinglasan,
Frederick Ray I. Gomez
Publication year - 2021
Publication title -
journal of engineering research and reports
Language(s) - English
Resource type - Journals
ISSN - 2582-2926
DOI - 10.9734/jerr/2021/v20i317286
Subject(s) - automated optical inspection , die (integrated circuit) , quad flat no leads package , automated x ray inspection , process (computing) , computer science , feature (linguistics) , magnification , engineering drawing , inspection time , visual inspection , moiré pattern , engineering , mechanical engineering , image processing , artificial intelligence , materials science , computer vision , nanotechnology , layer (electronics) , psychology , developmental psychology , linguistics , philosophy , adhesive , image (mathematics) , operating system
Advanced packaging at the back-end semiconductor manufacturing characterizes various equipment capabilities per device requirement. High resolution imaging for inspection system during die attach process has gained its interest to feature automated selections during in-line processing. Increasing yet stringent requisites of today’s applications give us leading indicators of market’s demand at more functionality in a smaller and complex package. In light with the technology trend, vision inspection system is a well-known challenge. Instead of using a high magnification microscope off-line after assembly processing, leadframe inspection feature uses optical image-based system to recognize real-time feedback on lead-related defects. Such leadframe inspection activation provides good accuracy, monitoring process integrity in real-time for quad-flat no-leads (QFN) leadframe packages. This paper presents how leadframe inspection at die attach machine takes advantage of simultaneous detection of early die attach defect manifestations.