Multi-objective optimization of laser cutting for flash memory modules with special shapes using grey relational analysis

This paper presents a novel effective method for optimizing laser cutting of specially shaped electronic printed circuit board (PCB) carrier substrates of advanced integrated circuit (IC) back-end packages that have multiple performance characteristics identified using grey relational analysis (GRA). Laser cutting parameters, including laser beam parameters (average laser power and Q-switch frequency), focusing parameters (laser beam focusing spot size), and machine parameters (laser cutting speed), were optimized based on multiple performance characteristics. Some characteristics of the specially shaped flash memory module for IC packages, such as smart disk (SD) cards are verified. The characteristics of interest are the average surface roughness on a PCB substrate cross-section, and the maximum width of the heat-affected zone (HAZ). Eight experiments were conducted using GRA to optimize the settings for laser beam cutting parameters to generate various quality characteristics. Analysis of the grey relational grade indicates that parameter significance and the optimal parameter combination for the laser cutting process are identified. The analytical results from two confirmation experiments using the optimal parameters confirm that laser cutting technology can be effectively applied to cut substrates into special shapes.