Modeling and Control of the Lithographic Offset Color Printing Process Using Artificial Neural Networks

Abstract

This paper investigates the use of artificial neural networks (ANNs) for modeling and control of the lithographic offset color printing process. The color controller consists of two ANNs; the controller network, which learns an inverse model of the process, takes a set of desired colors as input and generates a set of ink key settings, while the model network learns a forward model of the process through which the controller network can be adapted by using the error backpropagation method. We use three-layer networks with “local” connections between neurons of adjacent layers for the process model as well as for the controller; the architectures address the spatial relationship of multiple inking zones and consider the crosswise ink flow effects existing in the printing process.