Abstract: An integrated metrology and lithography/etch system and method (10) for micro-electronics device manufacturing. A process control neural network (30) is used to develop an estimated process control parameter (32) for controlling an etching process (28). The process control neural network is responsive to a multi-parameter characterization of a patterned resist feature MPC(PR) (16) developed on a substrate. The process control parameter is used as a feed-forward control for the etching process to develop an actual final mask feature. A multi-parameter characterization of the actual final mask feature MPC(HM) (36) is used as an input to a training neural network (40) for mapping to an ideal process control parameter. The ideal process control parameter is compared to the estimated control parameter to develop an error parameter (46), which is then used to train the process control neural network.

Abstract: An integrated metrology and lithography/etch system and method (10) for micro-electronics device manufacturing. A process control neural network (30) is used to develop an estimated process control parameter (32) for controlling an etching process (28). The process control neural network is responsive to a multi-parameter characterization of a patterned resist feature MPC(PR) (16) developed on a substrate. The process control parameter is used as a feed-forward control for the etching process to develop an actual final mask feature. A multi-parameter characterization of the actual final mask feature MPC(HM) (36) is used as an input to a training neural network (40) for mapping to an ideal process control parameter. The ideal process control parameter is compared to the estimated control parameter to develop an error parameter (46), which is then used to train the process control neural network.