The use of grey relational analysis to determine laser cutting parameters for QFN packages with multiple performance characteristics

Abstract

This paper reports an application of the grey relational analysis (GRA) to directly optimize laser cutting of a quad flat non-lead (QFN) strip using six performance characteristics. The most important performance characteristics include the cutting depth, the width of heat affected zone (HAZ), and the width of cutting line for both epoxy and Cu+epoxy materials along the cutting path. During the GRA, higher grades are obtained from any of the deeper (more complete) cutting depth, reduced widths of the HAZ and reduced widths of the cutting line. From nine experiments based on the orthogonal array of L9(3 4), a current of 29 A, a frequency of 2 kHz, and a cutting speed of 2 mm/s were found to be the best parameters for laser cutting of a QFN strip with a thickness of 0.9 mm. Moreover, the analysis of variance (ANOVA) is also employed to determine the contribution of each control parameter on the cutting quality characteristics. The three largest measured contributions on the cutting quality in decreasing order are the frequency, the current, and the cutting speed. Compared with the Taguchi optimization method, the GRA approach is significantly simpler because it directly assigns appropriate weighting factors to the required qualities. Finally, confirmation experiments are performed to ensure the robustness of the GRA predicted optimal configuration for laser cutting a QFN strip.