Patent ID: 7171394

Claim:
A method of optimizing a painting process for applying a paint layer on an article, the painting process controlled by a set of paint processing parameters, the method comprising: a) defining a functional relationship between the set of paint processing parameters and a paint layer property with a neural network having one or more neural layers to the one or more neural layers comprising a plurality of neural units having a plurality of neural network parameters, b) forming a paint optimization function that measures a combination of quality control parameters and paint transfer efficiency, the paint optimization function being a function of the paint layer property; and c) optimizing the paint optimization function by adjusting the one or more paint processing parameters utilizing the functional relationship defined in step a, wherein the functional relationship is defined by: obtaining a plurality of groups of values P k for the set of paint processing parameters and a value V for the paint layer property for each of the plurality of groups of values P k wherein k is an index number for each of the paint processing parameters with values from 1 to the number of processing parameters; and operating on each of the plurality of groups of values P k for the set of paint processing parameters with the neural network to provide an output O for each of the plurality of groups of values P k ; and adjusting the plurality of neural network parameters to minimize the differences between the output O and the value V for each of the one or more groups of values for a set of paint processing parameters to give a plurality of adjusted neural network parameters, and wherein the paint optimization function is given by: J =αΣ( FB−FT ) 2 +(1−α)( ΣFF/ΣFB ) wherein FB is an average thickness calculated from the functional relationship, FT is a target average film thickness, FF is the amount of paint sprayed, and α is a weighting factor with the value between 0 and 1.