Enhanced Die Attach Process Defect Recognition on QFN Leadframe Packages
Marque Ryan Salcedo
Operations 1 Assembly Manufacturing, STMicroelectronics, Inc., Calamba City, Laguna, Philippines.
Alyssa Grace Gablan *
Operations 1 Assembly Manufacturing, STMicroelectronics, Inc., Calamba City, Laguna, Philippines.
Jerome Dinglasan
Operations 1 Assembly Manufacturing, STMicroelectronics, Inc., Calamba City, Laguna, Philippines.
Frederick Ray Gomez
New Product Development & Introduction, STMicroelectronics, Inc., Calamba City, Laguna, Philippines.
*Author to whom correspondence should be addressed.
Abstract
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.
Keywords: Die attach process, error-proofing, leadframe inspection, lead-related defect, QFN, pattern recognition.