Real-Time Quality Evaluation of Wire Bonding Using Input Impedance

Input impedance characterizes the dynamic property of a linear system. A few existing technologies thus exploit input electrical impedance of wire bonders as the signature to monitor ultrasonic wire bonding processes. However, the waveforms of "impedance" in these technologies are evaluated only approximately. To overcome the shortcoming, we propose a method to detect the true waveforms of both the real and imaginary part of the input impedance. In the method, the voltage and current at the input port of a wire bonder are probed and processed to obtain impedance via Hilbert Transform. Because dynamics of a bonding process represented by these waveforms is fully responsible for the resulted bonding quality, a quality evaluation system based on pattern recognition of these waveforms is further proposed. An artificial neural network using back propagation as training scheme learns from a set of training data to correlate a few features of the impedance waveforms with the bonding strength of the corresponding bond identified by shearing tests. Through a set of verification data, the built system is validated to be capable of evaluating bonding quality right after a bonding process. The proposed method is not only in situ and real-time, but also sensorless, which means that the system is easy to be implemented without interfering operation