Neural network based process control of integrated circuit wire bonding machine

The electrical connections between an integrated circuit (IC) die and the package external leads are made by gold wires in a process called wire bonding. This task is done with a special wire bonding machine. This machine has several parameters to set. These settings are dependent on many factors, including wire size, die material, package size, etc. At present, the machine operator sets these parameters in an ad-hoc fashion based on guidelines and their experience. This paper describes an iterative neural network based closed loop controller for regulating two important characteristics of wire bond, ball size and shear strength density. This controller provides the settings for four parameters that have major impact on these two metrics. The performance is tested on actual machine; results show successful process control