Product Code: JLA_19_1_55

Authors:
Young Whan Park
Taehyung Kim
Sehun Rhee
Department of Mechanical Engineering, Hanyang University, Sungdang-Gu, Seoul 133-791, Korea

When laser marking on a silicon wafer is performed during chip scale packaging processing, predicting the quality of the marked region may be necessary to increase productivity. Research to estimate marking line geometry after marking has been carried out. The methods to evaluate the line geometry after marking have limited applicability in production. Therefore, in this study, a process monitoring system was applied to laser micromaterial processing and an algorithm for quality estimation was developed using fuzzy theory. The monitoring system consisted of a sensor which measured the plasma light generated during laser marking by means of a coaxial monitoring method. Relationships between marking linewidth and sensor signals as a function of laser power were analyzed. In order to determine marking quality, a fuzzy inference algorithm used estimated marking widths by predicted neural network model and the feature values extracted from sensor signals. A quality monitoring program was developed using the proposed algorithm.