Finishing property estimation device, finishing property estimation method, and program

Abstract

This finishing property estimation device for a coating film including coating of a base coating material which contains a coloring pigment and / or a bright material comprises a control unit which executes finishing property estimation processing for estimating the finishing property of the coating film on the basis of a coloring pigment contribution value that indicates the contribution of the coloring pigment included in the base coating material to finishing of the coating film and a bright material contribution value that indicates the contribution of the bright material included in the base coating material to the finishing of the coating film.

Description

Finished product quality estimation device, finished product quality estimation method, and program

[0001] This application claims priority to Japanese Patent Application No. 2024-050653, filed on March 27, 2024, the contents of which are incorporated herein by reference.

[0002] When developing paint colors for automobiles and other vehicles, colors are often selected from existing libraries (past colors) in the early stages, and paint colors are mostly selected with an emphasis on design (closeness to the target). However, estimating the paint film finish, which is derived from the pigment composition of the paint color, often relies on the knowledge of paint color design experts, making it difficult for engineers and designers with little experience in paint color design to estimate. Furthermore, when paint colors are selected without sufficient prior estimation of finish, defects are discovered at an advanced stage in the paint color design, and there have been cases where major rework was required.

[0003] Patent Publication No. 2021-140420

[0004] An object of the present invention is to provide a technique for estimating the finish quality of a coating film.

[0005] One aspect of the present invention is a finish quality estimation device for a paint film that includes a base paint containing a color pigment and / or a luster material, and is equipped with a control unit that executes a finish quality estimation process to estimate the finish of the paint film based on a color pigment contribution value that indicates the contribution of the color pigment contained in the base paint to the finish of the paint film, and a luster material contribution value that indicates the contribution of the luster material contained in the base paint to the finish of the paint film.

[0006] One aspect of the present invention is a method for estimating the finish of a paint film that includes a base paint containing a color pigment and / or a luster material, the method comprising a finish estimation step of estimating the finish of the paint film based on a color pigment contribution value that indicates the contribution of the color pigment contained in the base paint to the finish of the paint film, and a luster material contribution value that indicates the contribution of the luster material contained in the base paint to the finish of the paint film.

[0007] According to the present invention, a technique for estimating the finish quality of a coating film can be provided.

[0008] FIG. 1 is an explanatory diagram illustrating an overview of a finishability estimation device according to a first embodiment; FIG. 2 is a diagram illustrating an example of a hardware configuration of a finishability estimation device 10 according to an embodiment; FIG. 3 is a flowchart illustrating an example of a flow of processing executed by the finishability estimation device 10 according to an embodiment; FIG. 4 is a diagram illustrating a paint manufacturing device 30; FIG. 5 is a diagram illustrating an example of a first embodiment; FIG. 6 is a diagram illustrating an example of a second embodiment; FIG. 7 is a diagram illustrating an example of a comparative embodiment; FIG. 8 is a diagram illustrating an example of a comparative embodiment.

[0009] (First embodiment) (Finishedness estimation device) Hereinafter, embodiments of the present invention will be described in detail with reference to the drawings. FIG. 1 is an explanatory diagram illustrating an overview of a finishedness estimation device 10 of the first embodiment. The finishedness estimation device 10 is a device that estimates the finishedness of a paint film including a base paint coating containing a color pigment and / or a luster material. The finishedness estimation device 10 includes a control unit 11 that includes a processor 91, such as a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), or an NPU (Neural Network Processing Unit), and a memory 92, all connected via a bus.

[0010] The control unit 11 executes, for example, an information acquisition process and a finish quality estimation process.

[0011] (Information Acquisition Process) The information acquisition process is a process for acquiring information used in the finish quality estimation process. The information acquired by the information acquisition process includes a color pigment contribution value indicating the contribution of the color pigment contained in the base paint to the finish of the paint film, and a luster material contribution value indicating the contribution of the luster material contained in the base paint to the finish of the paint film. The paint film is, for example, a multi-layer paint film obtained by applying a clear paint after applying a base paint. The paint film may also be a paint film obtained by applying a base paint without applying a clear paint.

[0012] The color pigment contribution value A is, for example, the sum of the products of the content of each type of color pigment in the base paint and a coefficient set for each type of color pigment. The color pigment contribution value A is calculated, for example, by equation (1).

[0013] In formula (1), x ｉ indicates the content of each color pigment, and α ｉ indicates the coefficient set for each color pigment. The coefficient α set for each color pigment ｉ is a value set according to the degree to which each color pigment affects the quality of the finished paint film. Factors that affect the quality of the finished paint film include pigment dispersibility and the contribution to viscoelasticity when added to the paint. For example, the coefficient α of a color pigment that tends to deteriorate the quality of the finished paint ｉ For example, the coefficient α is set to 0 for pigments that do not change the quality of the finished paint film (e.g., color pigments with good dispersibility), and 1 for pigments that tend to deteriorate the quality of the finished paint film (e.g., color pigments with poor dispersibility). ｉ is set.

[0014] Coefficient α set for each color pigment ｉ The coefficients can be set relatively depending on the degree to which each color pigment affects the quality of the finish. The degree to which each color pigment affects the quality of the finish can be confirmed, for example, by preparing base paints that differ only in the type of color pigment for each color pigment, applying each, measuring the finish of the resulting paint film, and comparing the results.

[0015] The finish properties to be measured include Wa, Wb, Wc, Wd, We, Short Wave (SW), and Long Wave (LW), which are measured using, for example, a Wave Scan (trade name, manufactured by BYK Gardner). The distinctness to be measured includes, for example, distinctness of image (DOI), which is measured using a Wave Scan (trade name, manufactured by BYK Gardner). The gloss to be measured includes, for example, 20° gloss, 60° gloss, and 85° gloss, which are measured using a micro-TRI-gloss gloss meter (trade name, manufactured by BYK Gardner).

[0016] Coefficient α set for each color pigment ｉ The value may be calculated using machine learning or the like by learning the type of color pigment and measurement results of finish for paint films containing various color pigments. For example, base paints differing only in the type of color pigment are prepared and applied, and the finish of the resulting paint films is measured, thereby collecting data on combinations of color pigment type and measurement results of finish. By performing machine learning based on the data on combinations of color pigment type and measurement results of finish, a predictive model can be generated that inputs the type of color pigment and outputs finish.

[0017] The value determined by the type and content of the color pigment may be calculated using machine learning or the like by learning the type and content of each color pigment and the measurement results of finish for paint films containing various color pigments. For example, base paints with different types and contents of color pigment are prepared and applied, and the finish of the resulting paint films is measured, thereby collecting data on combinations of the type and content of the color pigment and the measurement results of finish. By performing machine learning based on the data on combinations of the type and content of the color pigment and the measurement results of finish, it is possible to generate a prediction model that uses the type and content of the color pigment as input and outputs finish. The value determined by the type and content of the color pigment is calculated using x in formula (1). ｉ α ｉ It can be used as.

[0018] The coefficients set for each color pigment may vary depending on the conditions of the base paint. Specifically, for example, when the base paint contains a specific type of color pigment, the coefficient α ｉ The estimation accuracy can be improved by changing the coefficient α depending on the content of the pigment. In addition, when the base paint contains a lustrous material and also a specific type of color pigment or matting agent, the coefficient α set for each color pigment can be ｉ The accuracy of the estimation can be improved by varying the content of a particular type of color pigment or matting agent.

[0019] The luster pigment contribution value is, for example, the sum of the products of the luster pigment content in the base paint and a coefficient set for each luster pigment. The luster pigment contribution value B is calculated, for example, by equation (2).

[0020] In formula (2), y ｉ indicates the content of each glittering material, and β ｉ indicates the coefficient set for each glittering material. The coefficient β set for each glittering material ｉ is a value set according to the degree to which each luster pigment affects the quality of the finished coating. Factors of luster pigments that affect the quality of the finished coating include the type of substrate, particle size, particle size distribution, thickness (including substrate and coating layer), etc. For example, the coefficient β of luster pigments that tend to deteriorate the quality of the finished coating is ｉ is set to a large value. For example, the coefficient β is set to 1 for glittering materials that do not change the quality of the finished paint film (such as aluminum flakes with a small particle size), and 2 for glittering materials that tend to deteriorate the quality of the finished paint film (such as oxide-coated natural mica with a thick coating layer). ｉ is set.

[0021] For example, a glittering material with a low surface smoothness of the base material tends to have a poor finish, so the coefficient β ｉ is set to a relatively large value. For example, glitter particles with large particle diameters tend to have a poor finish, so the coefficient β ｉ is set to a relatively large value. For example, glitter pigments containing coarse particles tend to have a poor finish, so the coefficient β ｉ is set to a relatively large value. For example, thick glittering materials tend to have a poor finish, so the coefficient β ｉ is set to a relatively large value. For example, because sharp-shaped glittering materials tend to have poor finishes, the coefficient β ｉ is set to a relatively large value.

[0022] Coefficient β set for each glittering material ｉThe coefficients can be set relatively according to the degree to which each lustrous pigment affects the quality of the finish. The degree to which each lustrous pigment affects the quality of the finish can be confirmed, for example, by preparing base paints for each lustrous pigment, each differing only in the type of lustrous pigment, applying each, measuring the finish of the resulting coating film, and comparing the results.

[0023] Coefficient β set for each glittering material ｉ The luminous pigment density may be calculated using machine learning or the like by learning the type of luminous pigment and measurement results of finish for coating films containing various luminous pigments. For example, base coatings differing only in the type of luminous pigment are prepared and applied, and the finish of the resulting coating films is measured, thereby collecting data on combinations of the type of luminous pigment and the measurement results of finish. By performing machine learning based on the data on combinations of the type of luminous pigment and the measurement results of finish, a predictive model can be generated that inputs the type of luminous pigment and outputs finish.

[0024] The value determined by the type and content of the luster material may be calculated using machine learning or the like by learning the type and content of each luster material and the measurement results of finish for coating films containing various luster materials. For example, base paints with different types and contents of luster material are prepared and applied, and the finish of the resulting coating films is measured, thereby collecting data on combinations of the type and content of the luster material and the measurement results of finish. By performing machine learning based on the data on combinations of the type and content of the luster material and the measurement results of finish, it is possible to generate a prediction model that inputs the type and content of the luster material and outputs finish. The value determined by the type and content of the luster material is calculated using y in formula (2). ｉ β ｉ It can be used as.

[0025] The coefficients set for each luminous material may vary depending on the conditions of the base paint. In particular, when the base paint contains a specific color pigment, the coefficient β set for each type of luminous material may be ｉ The estimation accuracy can be improved by changing the content of the pigment.

[0026] (Finish Quality Estimation Process) The finish quality estimation process is a process for estimating the finish quality of a paint film based on a color pigment contribution value and a luster pigment contribution value. The finish quality of a paint film can be, for example, the smoothness, image clarity, or gloss of the paint film, and the present invention is particularly effective in estimating image clarity. The finish quality of a paint film may be expressed by calculating the quality of smoothness, image clarity, or gloss as an index. Furthermore, the finish quality estimation process calculates an estimate of the finish quality of the paint film based on the color pigment contribution value and the luster pigment contribution value. However, depending on the difference in the contribution of the color pigment and the luster pigment to the finish quality of the paint film, the color pigment contribution value or the luster pigment contribution value may be multiplied by a constant to adjust the magnitude of the contribution of the color pigment contribution value and the luster pigment contribution value.

[0027] The finish quality estimation process is a process for estimating the finish quality of a coating film by calculating an estimated value of the finish quality using an equation including the addition of a color pigment contribution value and a luster pigment contribution value. For example, the finish quality estimation process uses a color pigment contribution value A and a luster pigment contribution value B as variables and calculates an estimated value of the finish quality using a function f(A, B) including the addition of A and B.

[0028] f(A, B) is, for example, the square root of the sum of the squares of A and B, and is expressed by equation (3).

[0029] The larger f(A, B) is, the poorer the quality of the finish is. In other words, f(A, B) is a value that indicates the defects in the smoothness, sharpness, or gloss of the finished coating film. Therefore, the coefficient α set for each color pigment is ｉ and the coefficient β set for each glittering material ｉis set to a large value for color pigments or luster pigments that tend to deteriorate the quality of the finish. In the first embodiment, the finish quality estimation device 10 calculates the estimated value of the finish quality based on the color pigment contribution value A and the luster pigment contribution value B, and therefore can estimate the finish quality of the paint film based on the contributions of both the color pigment and the luster pigment. When the finish quality estimation device 10 calculates and expresses the finish quality of the paint film as an index of the quality of smoothness, vividness, or gloss, it may calculate the index of the quality of smoothness, vividness, or gloss using a calculation formula that includes the above-mentioned f(A, B) as its reciprocal. In this case, the larger the calculated index value, the better the quality of the finish.

[0030] In addition, the coefficient α of color pigments, which tends to improve the quality of the finish, ｉ For example, the coefficient α of a color pigment that tends to improve the quality of the finish may be set to 1 for a pigment that does not change the quality of the finish of the paint film (for example, a color pigment with high dispersibility), and 0.1 for a pigment that tends to deteriorate the quality of the finish of the paint film (for example, a color pigment with poor dispersibility). ｉ is set to a large value.

[0031] The coefficient α of color pigments that tends to improve the quality of the finish ｉ The glitter coefficient β tends to improve the quality of the finish when a large value is set for ｉ For example, a large value is set for the coefficient β of a luminous material that tends to improve the quality of the finish, such as 1 for a luminous material that does not change the quality of the finish of the paint film (for example, aluminum flakes with a small particle size), and 0.1 for a luminous material that tends to deteriorate the quality of the finish of the paint film (for example, natural mica). ｉ is set to a large value.

[0032] The coefficient α of color pigments that tends to improve the quality of the finish ｉ The coefficient β of the glittering material is set to a large value and tends to improve the quality of the finish. ｉ When a large value is set for f(A, B), the larger f(A, B) is, the better the quality of the finish.

[0033] 2 is a diagram showing an example of the hardware configuration of the finishability estimation device 10 in an embodiment. The finishability estimation device 10 includes a control unit 11 including a processor 91 and a memory 92 connected by a bus, and executes a program. By executing the program, the finishability estimation device 10 functions as a device including the control unit 11, an interface unit 12, and a storage unit 13.

[0034] More specifically, the processor 91 reads out a program stored in the storage unit 13 and stores the read program in the memory 92. The processor 91 executes the program stored in the memory 92, whereby the finishability estimation device 10 functions as a device including the control unit 11, the interface unit 12, and the storage unit 13.

[0035] The control unit 11 controls the operation of each functional unit included in the finishability estimation device 10. The control unit 11, for example, acquires information stored in the memory unit 13. The process of acquiring information stored in the memory unit 13 is specifically reading. The control unit 11 may, for example, output various types of information to the memory unit 13, and the memory unit 13 records the information output to the memory unit 13. The control unit 11, for example, acquires information acquired by the interface unit 12. The control unit 11, for example, controls the interface unit 12 to transmit the information to be transmitted to the destination.

[0036] The control unit 11 executes, for example, an information acquisition process and a finish quality estimation process.

[0037] The interface unit 12 includes a communication interface for connecting the finishability estimation device 10 to an external device. The interface unit 12 communicates with the external device via wired or wireless communication. The external device is, for example, a device that transmits network information. The interface unit 12 acquires network information by communicating with the device that transmits the network information.

[0038] The interface unit 12 may be configured to include input devices such as a mouse, a keyboard, a touch panel, etc. The interface unit 12 may be configured as an interface that connects these input devices to the finishability estimation device 10. In this way, the input device of the interface unit 12 accepts input of various information to the finishability estimation device 10 via a wired or wireless connection. Note that various information such as network information does not necessarily have to be input to the communication interface of the interface unit 12, but may be input to the input device of the interface unit 12. When various information is input to the input device of the interface unit 12, the interface unit 12 does not need to be configured to be able to communicate with an external device.

[0039] The interface unit 12 outputs, for example, various types of information. The interface unit 12 includes a display device such as a CRT (Cathode Ray Tube) display, a liquid crystal display, or an organic EL (Electro-Luminescence) display, and a speaker. The interface unit 12 may be configured as an interface that connects these display devices or speakers to the finishability estimation device 10. Therefore, the display device and speaker included in the interface unit 12 output, for example, information input to an input device of the interface unit 12 as an image or sound.

[0040] The control unit 11 may, for example, control the operation of a display device or speaker that constitutes the interface unit 12 to output the estimated color candidates, the object-dependent score of each color, and the user-dependent score.

[0041] The storage unit 13 is configured using a computer-readable storage medium device (non-transitory computer-readable recording medium) such as a magnetic hard disk drive or a semiconductor storage device. The storage unit 13 stores various information related to the finishability estimation device 10. The storage unit 13 stores various information generated by the operation of the control unit 11, such as estimated color candidates. The storage unit 13 may exist on a cloud, for example.

[0042] 3 is a flowchart showing an example of the flow of processing executed by the finishability estimation device 10 of the embodiment. The control unit 11 executes an information acquisition process to acquire information used for estimating the finishability (step S11). The control unit 11 executes a finishability estimation process to estimate the finishability (step S12). The control unit 11 outputs the estimated finishability to a predetermined output destination (step S13). The predetermined output destination is, for example, a display device or speaker constituting the interface unit 12.

[0043] The control unit 11 may execute a display process. The display process is a process of displaying an estimated finish quality value and the content rate of each type of color pigment and luster material in the paint corresponding to the estimated finish quality value. The control unit 11 controls, for example, a display device constituting the interface unit 12 to display the estimated finish quality value and the content rate of each type of color pigment and luster material in the paint corresponding to the estimated finish quality value on the display device. For example, a paint color designer can use the estimated finish quality value as a criterion for judging the paint color design by checking the display of estimated finish quality values ​​for multiple paints. For example, if the estimated finish quality value is f(A, B) shown in Equation (3), a larger f(A, B) indicates a lower quality of the finish. Therefore, the paint color designer can decide to use a paint with a smaller estimated finish quality value and not use a paint with a larger estimated finish quality value.

[0044] Second Embodiment In a second embodiment, the coating film is a multi-layer coating film obtained by applying a clear coating after applying a base coating. In the second embodiment, the information acquisition process acquires a contribution value of the clear coating and / or coating conditions (hereinafter referred to as a "third contribution value") in addition to the color pigment contribution value and the luster pigment contribution value.

[0045] The contribution value of a clear paint is a value set, for example, according to the degree to which each crosslinking system in the clear paint affects the quality of the paint film finish. Examples of crosslinking systems in clear paints include isocyanate-hydroxyl group crosslinking systems, acid-epoxy crosslinking systems, and melamine-hydroxyl group crosslinking systems. The degree to which each crosslinking system in the clear paint affects the quality of the paint film finish can be confirmed, for example, by preparing and applying paints that differ only in each crosslinking system of the clear paint, measuring the finish of the resulting paint film, and comparing the results.

[0046] The contribution value of the painting conditions is a value set according to the degree to which each painting condition of the base paint and the clear paint affects the quality of the paint film finish, for example. Examples of painting conditions for the base paint and the clear paint include the painting process (2 coat 1 bake process, single base 3 wet process, double base 3 wet process, etc.), paint film thickness, and surface orientation during setting (horizontal or vertical). For example, if the paint film thickness of the clear paint is thin, the finish tends to be poor, so the contribution value of the painting conditions is set to a relatively large value. For example, if the surface orientation during setting is vertical, the finish tends to be poorer than when it is horizontal, so the contribution value of the painting conditions is set to a relatively large value. The degree to which each painting condition of the base paint and the clear paint affects the quality of the paint film finish can be confirmed, for example, by painting the base paint and the clear paint while changing only the painting conditions, measuring the finish of the resulting paint film, and comparing the results.

[0047] The contribution value of the clear paint may be calculated using machine learning, etc., by learning the type of crosslinking system and the measurement results of the finish for coating films containing each crosslinking system of the clear paint. The contribution value of the painting conditions may be calculated using machine learning, etc., by learning the measurement results of each painting condition and the finish for coating films with different painting conditions.

[0048] The third contribution value may be either one of the contribution value of the clear paint and the contribution value of the coating conditions, or may include both.

[0049] In the second embodiment, the finish quality estimation process estimates the finish quality of the coating film based on a third contribution value in addition to the color pigment contribution value and the luster pigment contribution value. For example, the finish quality estimation process uses the color pigment contribution value A, the luster pigment contribution value B, and the third contribution values ​​C and D as variables, and calculates an estimated value of the finish quality using a function g(A, B, C, D) that corrects a function f(A, B) that includes the addition of A and B.

[0050] g(A, B, C, D) is expressed by, for example, equation (4).

[0051] The third contribution values ​​C and D are values ​​determined by the type of clear paint and / or the painting conditions. In equation (4), f(A, B) is scaled by C and increased or decreased by D. A larger g(A, B, C, D) indicates poorer quality of finish. In other words, g(A, B, C, D) is a value that indicates defects in the smoothness, sharpness, or gloss of the paint film. Therefore, the third contribution values ​​C and D are set to large values ​​for clear paints that tend to deteriorate the quality of finish or painting conditions that tend to deteriorate the quality of finish.

[0052] In the second embodiment, the finish quality estimation device 10 calculates the estimated finish quality using an equation including the color pigment contribution value A, the luster pigment contribution value B, and the third contribution values ​​C and D, thereby enabling estimation of the finish quality of the paint film based on the contributions of the color pigment, luster pigment, clear paint, and painting conditions. When calculating and expressing the finish quality of the paint film as an index of smoothness, vividness, or gloss, the finish quality estimation device 10 may calculate the index of smoothness, vividness, or gloss using a calculation equation including the reciprocal of g(A, B, C, D). In this case, the higher the calculated index value, the better the quality of the finish.

[0053] (Paint blend creation device / paint manufacturing device) Figure 4 is a diagram showing the paint manufacturing device 30. Information indicating the content rate of each type of color pigment and luster material in the paint is input to the paint manufacturing device 30 from the finish quality estimation device 10. The paint manufacturing device 30 manufactures paint that meets the content rates of each type of color pigment and luster material indicated by the input information. The paint manufacturing device 30 is provided with predetermined paints, and manufactures paint by blending the prepared paints to achieve the paint blend indicated by the input information.

[0054] (Experimental Results) The following describes an experiment conducted to verify the estimation accuracy of the finish quality estimation device 10. The correlation between the estimated finish quality calculated from the paint and the finish quality measured from the painted board was investigated. Note that the coefficient α ｉ and the coefficient β set for each glittering material ｉ The coefficient was set by preparing and applying base paints with different coloring materials or luster materials, measuring the finish of the resulting paint film, and comparing the measurement results. In this study, the finish measured from the painted board was measured using the measurement value Wa (wavelength 0.1 to 0.3 mm) that can be measured using a BYK-Gardner WaveScan DOI (trade name).

[0055] Fig. 5 is a diagram showing an example of the first embodiment. Fig. 5 is a graph in which the estimated value of finish calculated by formula (3) is plotted on the vertical axis and the measured value of finish is plotted on the horizontal axis. In the example shown in Fig. 5, 149 painted plate samples with the same crosslinking system of the clear paint and the same painting process were used. In the graph shown in Fig. 5, the correlation coefficient R between the estimated value of finish and the measured value was 0.77, and a correlation was observed.

[0056] Fig. 6 is a diagram showing an example of the first embodiment. Fig. 6 is a graph in which the estimated value of finish calculated by equation (3) is plotted on the vertical axis and the measured value of finish is plotted on the horizontal axis. In the example shown in Fig. 6, 11 painted plate samples were used under four conditions (standard condition, variation 1, variation 2, variation 3) with different crosslinking systems or painting processes for the clear paint, for a total of 44 painted plate samples. In this case, the correlation coefficient R between the estimated value of finish and the measured value was 0.57, indicating little correlation.

[0057] FIG. 7 is a diagram showing an example of the second embodiment. FIG. 7 is a graph in which the estimated value of finish quality calculated by equation (4) is plotted on the vertical axis and the measured value of finish quality is plotted on the horizontal axis. The samples used in the example shown in FIG. 7 are the same as those used in the example shown in FIG. 6. In this case, the correlation coefficient R between the estimated value of finish quality and the measured value was 0.90, indicating a high correlation. This means that the finish quality estimation device 10 according to the second embodiment can correct the estimated value of the finish quality of a paint film based on the contributions of the clear paint and painting conditions.

[0058] 8 and 9 are diagrams showing comparative examples. The samples used in the examples shown in FIGS. 8 and 9 are the same as those used in the example shown in FIG. 5. FIG. 8 is a graph with the color pigment contribution value A on the vertical axis and the measured values ​​of finish quality on the horizontal axis. FIG. 9 is a graph with the luminous pigment contribution value B on the vertical axis and the measured values ​​of finish quality on the horizontal axis. In the graphs shown in FIGS. 8 and 9, the correlation coefficients R were 0.25 and 0.63, respectively, indicating no correlation. Therefore, it can be seen that the finish quality estimation device 10 according to the first embodiment can accurately estimate finish quality by using both the color pigment contribution value A and the luminous pigment contribution value B to estimate finish quality.

[0059] Other Embodiments One embodiment of the present invention has been described in detail above with reference to the drawings, but the specific configuration is not limited to that described above, and various design changes and the like can be made within the scope that does not deviate from the gist of the present invention.

[0060] A function f(A, B) involving the addition of A and B can be generalized as shown in equation (5). In equation (5), l, m, and n are positive real numbers. Equation (3) is an equation obtained by changing equation (5) to m=n=2 and l=1 / 2.

[0061] A part or all of the finishability estimation device 10 in the above-described embodiment may be implemented by a computer. In this case, a program for implementing this function may be recorded on a computer-readable recording medium, and the program may be loaded into a computer system and executed. Note that the term "computer system" as used herein includes an OS and peripheral hardware. Furthermore, the term "computer-readable recording medium" refers to portable media such as flexible disks, optical magnetic disks, ROMs, and CD-ROMs, as well as recording devices such as hard disks built into computer systems. Furthermore, the term "computer-readable recording medium" may include media that dynamically store programs for a short period of time, such as communication lines used when transmitting programs via networks such as the Internet or telephone lines, and media that store programs for a fixed period of time, such as volatile memory within the computer systems that serve as the server or client in such cases. The program may be for realizing part of the above-mentioned functions, or may be capable of realizing the above-mentioned functions in combination with a program already recorded in a computer system, or may be realized using a programmable logic device such as an FPGA (Field Programmable Gate Array).

[0062] According to the present invention, a technique for estimating the finish quality of a coating film can be provided.

[0063] 10...Finishability estimation device, 11...Control unit, 12...Interface unit, 13...Storage unit

Claims

1. A finish quality estimation device for a paint film including a base paint containing a color pigment and / or a luster material, comprising: a control unit that executes a finish quality estimation process to estimate the finish quality of the paint film based on a color pigment contribution value that indicates the contribution of the color pigment contained in the base paint to the finish of the paint film, and a luster material contribution value that indicates the contribution of the luster material contained in the base paint to the finish of the paint film.

2. The finish quality estimation device according to claim 1, wherein the finish quality estimation process estimates the finish quality by calculating an estimated value of the finish quality using a formula that includes the addition of the color pigment contribution value and the lustrous pigment contribution value.

3. The finish quality estimation device according to claim 2, wherein the finish quality estimation process estimates the finish quality by calculating the square root of the sum of squares of the color pigment contribution value and the luster pigment contribution value.

4. A finish quality estimation device described in any one of claims 1 to 3, wherein the color pigment contribution value is the sum of the products of the content of each type of color pigment in the base paint and a coefficient set for each type of color pigment.

5. A finish quality estimation device according to any one of claims 1 to 3, wherein the luster material contribution value is the sum of the products of the luster material content in the base paint and a coefficient set for each luster material.

6. A finish quality estimation device according to any one of claims 1 to 3, wherein the finish quality is the smoothness, clarity, or gloss of the coating film.

7. The finish quality estimation device according to claim 6, wherein the finish quality is calculated and expressed as an index of smoothness, clarity, or gloss quality.

8. A finishability estimation device as claimed in any one of claims 1 to 3, wherein the paint film is a multi-layer paint film obtained by applying a clear paint after applying the base paint, and the finishability estimation process includes a process of correcting the finishability estimated based on the color pigment contribution value and the luster material contribution value based on a third contribution value indicating the contribution of the clear paint to the finish of the paint film and / or the contribution of the painting conditions to the finish of the paint film.

9. A finish quality estimation device as described in any one of claims 1 to 3, wherein the control unit executes a display process that displays a value indicating the finish quality and the content rate of each type of color pigment and luster material in the paint corresponding to the quality of the finish.

10. A method for estimating the finish of a paint film including a base paint containing a color pigment and / or a luster material, comprising: a finish estimation step of estimating the finish of the paint film based on a color pigment contribution value indicating the contribution of the color pigment contained in the base paint to the finish of the paint film, and a luster material contribution value indicating the contribution of the luster material contained in the base paint to the finish of the paint film.

11. A program for causing a computer to execute the finishability estimation method according to claim 10.

Images