Color tolerancing system employing fuzzy logic

Abstract

A color measuring system uses fuzzy logic to establish acceptable pass/fail tolerances for production or inventory samples. The tolerances define a super ellipsoid which has six individual tolerance coordinates. Initially, the tolerances are defined by the high/low values of the pass samples in a training set which have been chosen to represent a population of visually rated pass and fail samples. A classifier template uses the super ellipsoid tolerances and ranks every sample in the training set. Any pass/fail ranking that differs from the visual rank is considered an error. All of the error distances are summed and all samples are passed through the fuzzy logic contained in an induction module to determine the changes needed in the super ellipsoid tolerances to minimize the error distance. The new tolerances are then passed to the classifier template for a new ranking of the training samples. The process is repeated until a minimum error distance is achieved. The final tolerances are then used by the classifier to rank subsequent samples as either pass or fail. Shade sorting can also be accomplished. In that case, the training samples are rated twice, first for the centroid color differences and then for the shade differences. The training set is processed by the classifier template/induction module to determine the two tolerances. The classifier then rates production/inventory samples to determine if they meet the centroid color needs, and then places the samples in the proper shade sort group.