Basf Corporation

Craig J McClanahan

James Soss

David L Newton

Horst J Finkenauer

Jeff P Jones

James L Anderson, Jr

Cynthia J Frank

Stephen F Shufeldt

A method of visualizing a color deviation of an actual color on a vehicle panel being painted utilizing a computer. A reference color image is displayed on a monitor to confirm that the reference color image is the appropriate color image relating to the actual color. Differences between that displayed reference color image and the actual color are inputted into the computer and the reference image is then translated into a revised color image. The revised color image is displayed on the monitor along with the reference color image such that a user can visually compare the differences between that displayed reference color image and displayed revised color image. The displayed revised color image can then be compared to the actual color to determine if any color deviations between the revised color image and the actual color remain.

Method of visualizing a color deviation

A method for determining if a proposed color solution, such as paint, pigments, or dye formulations, is acceptable, is provided. The inputs to the system are the actual color values of an item, differential color values, a proposed color solution, and second color values associated with the proposed color solution. The system includes an artificial intelligence model to analyze the inputs and produce an output for communicating whether the proposed color solution is acceptable. The artificial intelligence model may be embodied in a neural network.

Method for determining acceptability of proposed color solution using an artificial intelligence model

A computer based system and method provides color solutions to a customer. A solution request from an operator located at a remote location is received and delivered to a central location over a computer network. A composite solution database is searched to determine a color solution as a function of the solution request.

Color management and solution distribution system and method

A system and method for converting a color formula from compositions such as paints, pigments, or dye formulations, is provided. The input to the system is a first color formula. The system includes an input device for entering a plurality of color formula values and an artificial intelligence conversion model coupled to the input device. The conversion model produces an output signal for communicating a second color formula. The artificial intelligence model may be embodied in a neural network. More specifically, the conversion model may be a back propagation neural network.

System and method for converting a color formula using an artificial intelligence based conversion model

A computer based system and method provides color solutions to a customer over a computer network. A solution request is received from an operator. A composite solution database is searched to determine a color solution as a function of the solution request.

A system and method for organizing a plurality of sets color values into a plurality of color groups, such as paint, pigments, or dye formulations, is provided. The inputs to the system are the color values of a proposed paint, dye or colorant formulation and color measurement angles. The system includes an input device for entering a plurality of sets of color values and an artificial intelligence cluster model coupled to the input device. The cluster model produces an output signal indicative of the one color group to which a set of color values belongs. The artificial intelligence model may be embodied in a neural network. More specifically, the cluster model may be a self-organizing map neural network.

System and method for organizing color values using an artificial intelligence based cluster model

A method and apparatus for color matching are provided, in which paint recipe neural networks are utilized. The color of a standard is expressed as color values. The neural network includes an input layer having nodes for receiving input data related to paint bases. Weighted connections connect to the nodes of the input layer and have coefficients for weighting the input data. An output layer having nodes are either directly or indirectly connected to the weighted connections and generates output data related to color values. The data to the input layer and the data from the output layer are interrelated through the neural network's nonlinear relationship. The paint color matching neural network can be used for, but not limited to, color formula correction, matching from scratch, effect pigment identification, selection of targets for color tools, searching existing formulas for the closest match, identification of formula mistakes, development of color tolerances and enhancing conversion routines.

Computer-implemented neural network color matching formulation applications

Computer-implemented neural network color matching formulation system

There is disclosed a metallic and nonmettalic water borne base coat compositions exhibiting excellent appearance. A method for long term stability and the introduction of aluminum flake pigments into a water borne coating is also disclosed. The method is based on storing the aluminum flake in a solvent environment with introduction of the aluminum flake in to the aqueous environment just before applying the base coat coating. A water reducible acrylic resin with nonionic and acid functionality has been disclosed that allows for direct introduction of aluminum flake in to an aqueous environment. The coating vehicle is based on acrylic latex vehicle which exhibits excellent drying and film properties. The rheology control agent employed allows for a drier application of the coating to the substrate. The coating compositions disclosed are also in compliance with current and proposed volatile organic compound regulations.

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Bowling Green, OH, United States of America

Craig J McClanahan