The shape and size of free-air-ball formation deeply affect the quality of wire bonding. It not only affects the bondability of first bond (ball bond), but also affects the possibility of processing low loop height bonding for thin form packages and high I/O fine pitch packages. Several parameters, such as tail length, spark gap, supplied voltage, current and time of electrical flame-off unit etc., will affect the free-air-ball formation. This paper represents a study of using error-back-propagation neural network method to analyze the effect of each parameter and to predict the final result of the ball forming. From the experiment, it is shown that neural network can not only be used to precisely predict the size of ball formation, but also saves sampling time.

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