AU2023290761B2

AU2023290761B2 - Automatic adjustment method and automatic adjustment system

Info

Publication number: AU2023290761B2
Application number: AU2023290761A
Authority: AU
Inventors: Noriyuki Nakazawa; Yuki Numada; Kenji Takagi; Chunpiu YAU
Original assignee: Nippon Paint Industrial Coatings Co Ltd
Current assignee: Nippon Paint Industrial Coatings Co Ltd
Priority date: 2022-06-13
Filing date: 2023-05-08
Publication date: 2026-03-19
Anticipated expiration: 2043-05-08
Also published as: AU2023290761A1; CN119031985A; WO2023243257A1; JP7429456B2; JP2023181928A

Abstract

A change amount response curve data showing the relationship between the amount of change in each parameter and the amount of change in information associated with a coating material property is acquired for a coating composition before change, and a suitable amount of change in the ratio of addition of a coating material property adjusting material and/or a suitable amount of change in a production condition is calculated by a calculation unit using target data and the change amount response curve data. The suitable amount of change in the ratio of addition of a coating material property adjusting material and/or the suitable amount of change in a production condition is calculated using a Brute-force search method or a mathematical optimization method.

Description

26 Feb 2026

AUTOMATIC ADJUSTMENT METHOD AND AUTOMATIC ADJUSTMENT SYSTEM

TECHNICAL FIELD 5 [0001] The present disclosure relates to an automatic adjustment method and an automatic adjustment system, and in particular to an automatic adjustment method and an automatic adjustment system for a paint composition. 2023290761

BACKGROUND 10 [0002] It has conventionally been proposed to use theoretical formulas to adjust the viscosity, etc. of a paint composition and the color, gloss, etc. of a paint film obtained from the paint composition. For example, JP 2008-111116 A (PTL 1) proposes a method of, through the use of the Kubelka-Munk optical density formula, predicting the spectral reflectance when colorants are mixed 15 in a predetermined formulation and comparing the predicted reflectance of the adjusted color with the reflectance of the sample color to calculate the colorant formulation.

[0003] It has also been proposed to use machine learning techniques to automatically adjust the viscosity, etc. of a paint composition and the color, 20 gloss, etc. of a paint film obtained from the paint composition. For example, JP 2021-107781 A (PTL 2) proposes creating an artificial intelligence model with the formulation as an explanatory variable and the color as an objective variable and predicting the color in the case of coloring in a predetermined formulation. 25 CITATION LIST Patent Literature

[0004] PTL 1: JP 2008-111116 A PTL 2: JP 2021-107781 A 30 SUMMARY

[0005] However, amid growing demand for accurate adjustment of the color, gloss, viscosity, etc. of paint compositions in recent years, the calculations using the theoretical formula as in PTL 1 have problems in making more 35 accurate adjustment. The method using machine learning as in PTL 2 is capable of accurate automatic adjustment, but requires an enormous amount of learning

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data to perform machine learning. A failure to collect such an enormous amount of learning data makes it impossible to carry out the method, and also collecting such an enormous amount of learning data takes a long time.

[0006] It could therefore be helpful to provide an automatic adjustment 5 method and an automatic adjustment system that can accurately adjust paint compositions using a simple technique.

[0007] Disclosed herein is an automatic adjustment method and an automatic 2023290761

adjustment system. Various aspects and embodiments of automatic adjustment method and the automatic adjustment system disclosed herein are 10 set out in the following numbered statements: (1) An automatic adjustment method for a paint composition of determining, by calculation by a calculation unit of a computer, a suitable change amount in an addition ratio of a paint property adjustment material to a pre-adjustment paint composition and/or a suitable change amount in a 15 production condition for obtaining a target paint property when adjusting a paint composition under a predetermined production condition , the paint property adjustment material including at least one from among a plurality of types of colorants, one or more types of gloss modifiers, and one or more types of viscosity modifiers, and the target paint property including at least one of a 20 target color, a target gloss, and a target viscosity, the automatic adjustment method comprising: a change amount response curve data acquisition step of, based on a pre-change paint composition, obtaining in advance information of a paint property when only one parameter from among an addition ratio of one or more types of colorants of the plurality of types of colorants, an addition 25 ratio of the one or more types of gloss modifiers, an addition ratio of the one or more types of viscosity modifiers, and the production condition is varied, for each parameter, and acquiring change amount response curve data indicating a relationship between a change amount in each parameter and a change amount in the information of the paint property; and a calculation step 30 of calculating, by the calculation unit of the computer, the suitable change amount in the addition ratio of the paint property adjustment material to the pre-adjustment paint composition and/or the suitable change amount in the production condition, using target data including the at least one of the target color, the target gloss, and the target viscosity and the change amount response 35 curve data acquired in the change amount response curve data acquisition step , wherein in the calculation step, the suitable change amount in the addition ratio

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of the paint property adjustment material to the pre -adjustment paint composition and/or the suitable change amount in the production condition is calculated using a brute-force search technique. (2) An automatic adjustment method for a paint composition of 5 determining, by calculation by a calculation unit of a computer, a suitable change amount in an addition ratio of a paint property adjustment material to a pre-adjustment paint composition and/or a suitable change amount in a 2023290761

production condition for obtaining a target paint property when adjusting a paint composition under a predetermined production condition , the paint 10 property adjustment material including at least one from among a plurality of types of colorants, one or more types of gloss modifiers, and one or more types of viscosity modifiers, and the target paint property including at least one of a target color, a target gloss, and a target viscosity, the automatic adjustment method comprising: a change amount response curve data acquisition step of, 15 based on a pre-change paint composition, obtaining in advance information of a paint property when only one parameter from among an addition ratio of one or more types of colorants of the plurality of types of colorants, an addition ratio of the one or more types of gloss modifiers, an addition ratio of the one or more types of viscosity modifiers, and the production condition is varied, 20 for each parameter, and acquiring change amount response curve data indicating a relationship between a change amount in each parameter and a change amount in the information of the paint property; and a calculation step of calculating, by the calculation unit of the computer, the suitable change amount in the addition ratio of the paint property adjustment material to the 25 pre-adjustment paint composition and/or the suitable change amount in the production condition, using target data including the at least one of the target color, the target gloss, and the target viscosity and the change amount response curve data acquired in the change amount response curve data acquisition step , wherein in the calculation step, the suitable change amount in the addition ratio 30 of the paint property adjustment material to the pre -adjustment paint composition and/or the suitable change amount in the production condition is calculated using a mathematical optimization technique . (3) The automatic adjustment method according to ( 1) or (2), wherein in the calculation step: a change amount in at least one of color, gloss, and 35 viscosity when at least one from among addition ratios of the plurality of types of colorants, the addition ratio of the one or more types of gloss modifiers, the

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addition ratio of the one or more types of viscosity modifiers, and the production condition is changed is calculated using the change amount response curve data, and a change amount in the at least one from among the addition ratios of the plurality of types of colorants, the addition ratio of the 5 one or more types of gloss modifiers, the addition ratio of the one or more types of viscosity modifiers, and the production condition that reduces a difference between the at least one of color, gloss, and viscosity changed by 2023290761

the calculated change amount in the at least one of color, gloss, and viscosity and the at least one of the target color, the target gloss, and the target viscosity 10 is calculated. (4) The automatic adjustment method according to (1) or (2), wherein prior to the calculation step, data of a change amount in at least one of color, gloss, and viscosity when at least one from among addition ratios of the plurality of types of colorants, the addition ratio of the one or more types of 15 gloss modifiers, the addition ratio of the one or more types of viscosity modifiers, and the production condition is changed is obtained in advance, using the change amount response curve data, and in the calculation step, a change amount in the at least one from among the addition ratios of the plurality of types of colorants, the addition ratio of the one or more types 20 of gloss modifiers, the addition ratio of the one or more types of viscosity modifiers, and the production condition that reduces a difference between the at least one of color, gloss, and viscosity changed by the change amount in the at least one of color, gloss, and viscosity obtained in advance and the at least one of the target color, the target gloss, and the target viscosity is calculated. 25 (5) The automatic adjustment method according to any one of (1) to ( 4), wherein the calculation step includes: a first calculation substep of calculating a suitable change amount in an addition ratio of a gloss modifier and/or a viscosity modifier, using data of the target gloss and/or the target viscosity and the change amount response curve data acquired in the change amount response 30 curve data acquisition step; a second calculation substep of, using the suitable change amount in the addition ratio of the gloss modifier and/or the viscosity modifier obtained in the first calculation substep and the change amount response curve data, calculating a change amount in color resulting from adding the gloss modifier and/or the viscosity modifier by the suitable change 35 amount in the addition ratio obtained in the first calculation substep; and a third calculation substep of calculating a suitable change amount in an addition

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ratio of a colorant, using the change amount in color obtained in the second calculation substep and the change amount response curve data. (6) The automatic adjustment method according to (3), further comprising: a step of setting a numerical value generation range for a change 5 amount in at least one of the addition ratio of each colorant, the addition ratio of each gloss modifier, the addition ratio of each viscosity modifier, and the production condition; and a step of preparing a data group of change amounts 2023290761

in the addition ratio of the paint property adjustment material to the pre- adjustment paint composition and/or change amounts in the production 10 condition, by combining change amounts in at least one of the addition ratio of the colorant, the addition ratio of the gloss modifier, the addition ratio of the viscosity modifier, and the production condition generated within the set numerical value generation range, wherein in the calculation step: the change amount in at least one of color, gloss, and viscosity when the addition ratio of 15 the paint property adjustment material to the pre -adjustment paint composition and/or the production condition is changed by each numerical value of the prepared data group of the change amounts in the addition ratio of the paint property adjustment material to the pre-adjustment paint composition and/or the change amounts in the production condition is calculated using the change 20 amount response curve data, and the change amount in the at least one from among the addition ratios of the plurality of types of colorants, the addition ratio of the one or more types of gloss modifiers, the addition ratio of the one or more types of viscosity modifiers, and the production condition that reduces the difference between the at least one of color, gloss, and viscosity changed 25 by the calculated change amount in the at least one of color, gloss, and viscosity and the at least one of the target color, the target gloss, and the target viscosity is calculated. (7) The automatic adjustment method according to (2), wherein a convex optimization technique is used as the mathematical optimization 30 technique. (8) The automatic adjustment method according to (2), wherein a quadratic programming technique is used as the mathematical optimization technique. (9) The automatic adjustment method according to (2), wherein a 35 gradient descent technique is used as the mathematical optimization technique . (10) The automatic adjustment method according to any one of (1) to

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(9), wherein the pre-adjustment paint composition includes two or more of (A1) to (A3): (A1) the one or more types of colorants, (A2) the one or more types of gloss modifiers, and (A3) the one or more types of viscosity modifiers. (11) The automatic adjustment method according to any one of (1) to 5 (10), wherein the production condition includes one or more of (a) to (d): (a) one or more of viscosity and heating residue of paint, (b) one or more of roll peripheral speed, spray discharge amount, electrodeposition coating voltage, 2023290761

coating pressure, and paint flow rate in a step of applying the paint composition to a coated matter, (c) one or more of maximum arrival temperature of the 10 coated matter, baking temperature, and baking time in a baking step, and (d) one or more of environmental temperature and humidity of a production line and temperature of the paint. (12) The automatic adjustment method according to any one of (1) to (11), wherein the paint property adjustment material includes the plurality of 15 types of colorants, the target paint property includes the target color, the pre- adjustment paint composition includes the one or more types of colorants, the change amount response curve data acquisition step includes obtaining colors in advance by varying an addition ratio of one type of colorant and acquiring the change amount response curve data indicating a relationship between a 20 change amount in the addition ratio of the one type of colorant and a change amount in color, and the calculation step includes calculating a suitable change amount in the addition ratio of the colorant, using the target color and the change amount response curve data acquired in the change amount response curve data acquisition step. 25 (13) An automatic adjustment system for a paint composition configured to determine, by calculation by a calculation unit of a computer, a suitable change amount in an addition ratio of a paint property adjustment material to a pre-adjustment paint composition and/or a suitable change amount in a production condition for obtaining a target paint property when adjusting 30 a paint composition under a predetermined production condition , the paint property adjustment material including at least one from among a plurality of types of colorants, one or more types of gloss modifiers, and one or more types of viscosity modifiers, and the target paint property including at least one of a target color, a target gloss, and a target viscosity, the automatic adjustment 35 system further comprising an acquisition unit configured to, based on a pre- change paint composition, obtain in advance information of a paint property

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when only one parameter from among an addition ratio of one or more types of colorants of the plurality of types of colorants, an addition ratio of the one or more types of gloss modifiers, an addition ratio of the one or more types of viscosity modifiers, and the production condition is varied, for each parameter, 5 and acquire change amount response curve data indicating a relationship between a change amount in each parameter and a change amount in the information of the paint property, wherein the calculation unit is configured to 2023290761

calculate the suitable change amount in the addition ratio of the paint property adjustment material to the pre-adjustment paint composition and/or the suitable 10 change amount in the production condition, using target data including the at least one of the target color, the target gloss, and the target viscosity and the acquired change amount response curve data, and the calculation unit is configured to calculate the suitable change amount in the addition ratio of the paint property adjustment material to the pre -adjustment paint composition 15 and/or the suitable change amount in the production condition, using a brute - force search technique. (14) An automatic adjustment system for a paint composition configured to determine, by calculation by a calculation unit of a computer, a suitable change amount in an addition ratio of a paint property adjustment 20 material to a pre-adjustment paint composition and/or a suitable change amount in a production condition for obtaining a target paint property when adjusting a paint composition under a predetermined production condition , the paint property adjustment material including at least one from among a plurality of types of colorants, one or more types of gloss modifiers, and one or more types 25 of viscosity modifiers, and the target paint property including at least one of a target color, a target gloss, and a target viscosity, the automatic adjustment system further comprising an acquisition unit configured to, based on a pre- change paint composition, obtain in advance information of a paint property when only one parameter from among an addition ratio of one or more types of 30 colorants of the plurality of types of colorants, an addition ratio of the one or more types of gloss modifiers, an addition ratio of the one or more types of viscosity modifiers, and the production condition is varied, for each parameter, and acquire change amount response curve data indicating a relationship between a change amount in each parameter and a change amount in the 35 information of the paint property, wherein the calculation unit is configured to calculate the suitable change amount in the addition ratio of the paint property

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adjustment material to the pre-adjustment paint composition and/or the suitable change amount in the production condition, using target data including the at least one of the target color, the target gloss, and the target viscosity and the acquired change amount response curve data, and the calculation unit is 5 configured to calculate the suitable change amount in the addition ratio of the paint property adjustment material to the pre -adjustment paint composition and/or the suitable change amount in the production condition, using a 2023290761

mathematical optimization technique.

[0008]-[0020] [Omitted.] 10 [0021] It is thus possible to provide an automatic adjustment method and an automatic adjustment system that can accurately adjust paint compositions using a simple technique.

BRIEF DESCRIPTION OF THE DRAWINGS 15 [0022] In the accompanying drawings: FIG. 1 is a flowchart of an automatic adjustment method according to an embodiment of the present disclosure; FIG. 2 is a diagram for explaining a middle step of a change amount response curve data acquisition step; 20 FIG. 3 is a diagram illustrating the names of change amount response curves; FIG. 4A is a diagram for explaining a first step of a calculation step; FIG. 4B is a diagram for explaining the first step of the calculation step; 25 FIG. 5 is a block diagram of an automatic adjustment system according to an embodiment of the present disclosure; and FIG. 6 is a diagram illustrating an example of a change amount response curve.

30 DETAILED DESCRIPTION OF SPECIFIC EMBODIMENTS

[0023] Embodiments of the present disclosure will be described in detail below with reference to the drawings. In the present disclosure, the meanings of the terms are as follows. The “paint property adjustment material” is a general term for materials 35 used for adjusting paint properties, such as colorants, gloss modifiers, and viscosity modifiers. The “pre-adjustment paint composition” refers to a paint

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composition in which about 85  to 100  of predetermined amounts of materials having the same functions as paint property adjustment materials among the materials constituting a target paint composition are contained and whose properties are roughly similar to target properties. The pre-adjustment 5 paint composition may or may not contain a paint property adjustment material. The blending amount of each material may be unknown. The “calculation paint composition” refers to a paint composition made with one type of colorant to 2023290761

theoretically calculate the absolute value of color. The calculation paint composition contains a resin, solvent, hardener, etc. in addition to a paint 10 property adjustment material including a colorant. This material is not necessary in the case of not acquiring the change amount in color using the below-described Kubelka-Munk optical density formula, etc. by predictive calculation.

[0024] <Automatic adjustment method> 15 An automatic adjustment method according to an embodiment of the present disclosure is an automatic adjustment method for a paint composition of determining, by calculation by a calculation unit of a computer, a suitable change amount in the addition ratio of a paint property adjustment material to a pre-adjustment paint composition and/or a suitable change amount in a 20 production condition for obtaining a target paint property when adjusting a paint composition under a predetermined production condition . As an example, the automatic adjustment method according to this embodiment can be executed using the below-described automatic adjustment system according to an embodiment of the present disclosure. 25 [0025] Here, the paint composition is, for example, obtained as follows: A plurality of colorants are prepared for color pigments of various colors, where each colorant is prepared by dispersing a resin, a solvent, and one type of color pigment in an SG mill or the like. Then, in order to adjust to a given color, a resin, a solvent, and an additive are added to one or more colorants and mixed 30 together as the paint composition. Examples of the form of the paint composition include water-based paint, solvent-based paint, powder paint, and non-solvent paint, without being limited thereto. Examples of applications include coil paint, general industrial paint, automotive paint, automotive refinishing paint, architectural paint, heavy-duty anticorrosion paint, and 35 marine paint. Examples of coating methods include spray coating, roller coating, brush coating, roll coating (including natural and reverse rotation),

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curtain flow coating, die coating, electrodeposition coating, powder coating, and electrostatic coating. Examples of drying methods include baking drying, forced drying, natural drying, and ultraviolet curing. Examples of formulations include resin raw materials, pigments, design raw materials, solvents 5 (including water), and additives. Examples of resin raw materials include acrylic resin, polyester resin, epoxy resin, alkyd resin, fluororesin, urethane resin, aminomelamine resin, isocyanate resin, blocked isocyanate resin, and 2023290761

modified resins such as urethane-modified polyester resin. Examples of pigments include inorganic pigments, organic pigments, coloring pigments, 10 and extender pigments. Examples of design raw materials include luster materials such as metallics and pearls, aggregates, silica, resin beads, and wax. Examples of additives include viscosity modifiers, silicone additives, rust inhibitors, catalysts, and antifoaming agents.

[0026] In this embodiment, the paint property adjustment material includes at 15 least one from among a plurality of types of colorants, one or more types of gloss modifiers, and one or more types of viscosity modifiers. The paint property adjustment material preferably includes at least a plurality of types of colorants. The colorants contain color pigments. Examples of the color pigments include black pigment, white pigment, yellow pigment, green 20 pigment, red pigment, blue pigment, titanium oxide, and red iron oxide. Examples of the gloss modifiers include aggregate (sand, etc.), silica, reflective material, and alumina as components. Examples of the viscosity modifiers include synthetic resin-based viscosity modifiers, natural product- based viscosity modifiers, and inorganic viscosity modifiers. Examples of the 25 synthetic resin-based viscosity modifiers include polymer-type viscosity modifiers and association-type viscosity modifiers. Solvents such as water and organic solvents can also be used as viscosity modifiers.

[0027] The target paint property includes at least one of a target color, a target gloss, and a target viscosity. Other examples of the paint property, beside color, 30 gloss, and viscosity, include film thickness, contrast ratio, flip-flop property, smoothness, visual appearance, electrical resistance, contact angle, staining resistance, solar reflectance, ultraviolet transmittance, weather resistance, viscoelasticity, processability, paint film abnormality, spinnability, flash point, and foamability. 35 [0028] For color, a color system such as L* value, a* value, and b* value in L*a*b* color space (JIS Z8781-4 (2013)), XYZ color system, RGB color

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system, Yxy color system, Hunter Lab color system, L*C*h* color system, or Munsell color system may be used. Color can be measured using a known color measurement method. As an example, using a spectrophotometer CM-M6 (produced by Konica Minolta, Inc.), a light source is applied to a paint film 5 formed on a test plate at angles of 25, 45, and 75 where the light receiving part perpendicular to the paint film is 0, and L* value, a* value, and b* value are measured. Alternatively, a spectrophotometer X-Rite MA68II (produced by 2023290761

X-Rite, Inc.) may be used for measurement. The measurement angle may be adjusted as appropriate according to the purpose or equipment used. Any other 10 index may be used. For example, any index such as reflection spectrum data of reflection spectrum intensity for every 5 nm from 380 nm to 780 nm as color may be used. For gloss, glossiness may be used as an index, without being limited thereto. Glossiness can be measured using a known gloss measurement method. As an example, the 60 glossiness of a paint film formed on a test plate 15 is measured using a specular glossiness meter (glossmeter VG 7000 (produced by Nippon Denshoku Industries Co., Ltd.)) in accordance with JIS K 5600-4-7 (specular glossiness). Viscosity can be measured using a known viscosity measurement method. As an example, viscosity is measured in accordance with JIS K 5600-2-2 (flow cup method). For smoothness, it is preferable to use a 20 wave scan value as an index. The wave scan value can be measured using wave- scan (produced by BYK Gardner), as an example. The wave scan value is preferably one or more selected from du (wavelength 0.1 mm or less), Wa (wavelength 0.1 mm to 0.3 mm), Wb (wavelength 0.3 mm to 1.0 mm), Wc (wavelength 1.0 mm to 3.0 mm), Wd (wavelength 3.0 mm to 10.0 mm), We 25 (wavelength 10.0 mm to 30.0 mm), Lw (wavelength 1.2 mm to 12 mm), and Sw (wavelength 0.3 mm to 1.2 mm). A smaller wave scan value indicates less irregularity of the wavelength on the surface and better appearance quality of the paint film. Flip-flop property can be measured using multi-angle colorimeter BYK-mac i (produced by BYK Gardner), as an example. Specific 30 examples of paint film abnormality include unevenness, blister, crack, drip, pinhole, and frame. These can each be measured by a known method. For color, the obtained paint composition may be evaluated directly. As an example, the color of the paint composition can be measured in a state in which the paint composition is placed in a quartz glass cell using a 35 spectrophotometer CM-M6 (produced by Konica Minolta, Inc.). Adjusting any one of the properties of color, gloss, and viscosity may

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influence the other properties.

[0029] Examples of the production condition include substrate data, coating condition data, and measurement condition data. Examples of the substrate data include substrate type, substrate color, surface tension, and surface roughness . 5 Simple trade names and substance names may be used as data. In the case of roll coating, examples of the coating condition data include (i) equipment and device-related conditions such as line speed, roll peripheral speed, nip pressure, 2023290761

the number of rolls used, roll rotation direction, coating pressure, paint flow rate, applicator roll state, material, hardness, pickup roll type, and coating line 10 structure, (ii) paint composition-related conditions such as viscosity and adhesion amount, (iii) temperature and humidity -related conditions such as baking time in the baking step, temperature rise curve of the coated matter, maximum arrival temperature, baking furnace temperature, hot air speed, and environmental temperature and humidity, (iv) instrument-related conditions 15 such as colorimeter and glossmeter, and (v) other conditions such as physical property data and chemical property data including the type and color of the undercoat paint film, gloss, roughness, surface tension, and surface SP value . In the case of spray coating, examples of the coating condition data include the viscosity of the paint composition, discharge pressure, discharge amount, gun 20 type, baking temperature, setting time, and baking time in the baking step, and environmental temperature and humidity. In the case of electrodeposition coating, examples of the coating condition data include coating voltage, liquid temperature, energization time, coating direction (horizontal plane or vertical plane), and line speed. Examples of the measurement condition data include 25 colorimeter model, glossmeter model, measurement temperature, time from device energization, and individual measuring instrument name.

[0030] The production condition preferably includes one or more of (a) to (d): (a) one or more of the viscosity and heating residue of the paint ; (b) one or more of the roll peripheral speed, spray discharge amount, electrodeposition 30 coating voltage, coating pressure, and paint flow rate in the step of applying the paint composition to the coated matter; (c) one or more of the maximum arrival temperature of the coated matter, baking temperature, and baking time in the baking step; and (d) one or more of the environmental temperature and humidity of the production line and the temperature of the paint. 35 [0031] FIG. 1 is a flowchart of the automatic adjustment method according to the embodiment of the present disclosure.

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In this embodiment, first, a pre-change paint composition is prepared (step S101: the first step of the change amount response curve data acquisition step). The pre-change paint composition may be only a resin and a solvent, or may contain one or more types of paint property adjustment materials (colorant, 5 gloss modifier, and viscosity modifier, etc. ) in addition to the resin and solvent. Information of the paint property of the pre-change paint composition (also referred to as “pre-change paint property”) is obtained in advance. 2023290761

[0032] Next, in this embodiment, based on the pre-change paint composition (prepared in step S101), information of the paint property when only one 10 parameter from among the addition ratio of one or more types of colorants, the addition ratio of one or more types of gloss modifiers, the addition ratio of one or more types of viscosity modifiers, and each production condition is varied is obtained in advance for each parameter (step S102 : the middle step of the change amount response curve data acquisition step). The addition ratio can be 15 expressed, for example, in mass where the mass of the prepared pre-change paint composition is 100 .

[0033] In step S102, as the information of the paint property, at least one of color, gloss, and viscosity is obtained by measurement. The color, gloss, and viscosity can be measured by measuring the paint composition or the paint film 20 obtained from the paint composition. The measurement methods for color, gloss, and viscosity are, for example, as described above. The addition ratio of only one type of colorant, the addition ratio of only one type of gloss modifier, the addition ratio of only one type of viscosity modifier, or only one of the various production conditions is changed. Regarding color, for example, the 25 spectral reflectance when colorants are mixed in a predetermined formulation may be used to predict and calculate the change amount in color from the difference between before and after the addition to the paint composition through the use of the Kubelka-Munk optical density formula, etc.

[0034] FIG. 2 is a diagram for explaining the middle step of the change amount 30 response curve data acquisition step, illustrating an example in which the parameter to be changed is the addition ratio of the white colorant. Specifically, the addition ratio of the white paint composition is changed from 0  to 0.03 , 0.1 , 0.3 , 1 , 3 , and 10  relative to the total mass of the pre- change paint composition. In order to enable accurate fine adjustment, it is 35 preferable to change the addition ratio in increments of about 0.01  to 1  when the change amount is 1  or less, i.e. the change is large. The number of

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changes can be, for example, 2 to 20 for one parameter. As illustrated in FIG. 2, information of color, gloss, and viscosity when only one parameter is changed is obtained by measurement, for example. This is performed for each parameter (other colorants, gloss modifiers, viscosity modifiers, and 5 production conditions). It is also preferable to change each production condition in increments that are fine enough to perform accurate fine adjustment, taking into account the adjustment width of actual adjustment of 2023290761

the production condition.

[0035] Next, in this embodiment, change amount response curve data 10 indicating the relationship between the change amount in each parameter and the change amount in the information of the paint property is acquired (step S103: the latter step of the change amount response curve data acquisition step). In the example illustrated in FIG. 2, for change 1, data of the relationship between the change amount of changing the addition ratio of the white colorant 15 from 0  to 0.03  and the resultant change amount in color (the change amount in L* value (WL1), the change amount in a* value (Wa1), the change amount in b* value (Wb1)), the change amount in gloss (Wg1), and the change amount in viscosity (Wv1)) is obtained. Likewise, for each of other changes 2 to 6, data of the relationship between the change amount in the parameter and 20 the change amount in the information of the paint property is obtained. Although the number of pre-change paint compositions prepared may be one, in order to respond to various adjustments, it is preferable to prepare a plurality of pre-adjustment (pre-change) paint compositions and obtain data of the relationship between the change amount in the parameter and the change 25 amount in the information of the paint property for the color of each pre-change paint composition. For example, the plurality of pre-change paint compositions are prepared preferably in increments of 5 and more preferably in increments of 1 for color (L* value, a* value, b* value). For more efficiency, it is preferable to prepare pre-change paint compositions for each colorant type, and 30 they may be classified by color type, such as by using two or more of them. In the method according to this embodiment, the change amount response curve data consisting of the data obtained as described above is acquired. FIG. 3 illustrates an example of the names of change amount response curves. 35 Herein, the term “acquisition” includes not only the case of acquiring the change amount response curve data through calculation by a calculation

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unit (processor) of a computer but also the case of receiving the change amount response curve data by a communication unit of a computer, the case of reading the change amount response curve data recorded in memory by a reading unit, etc. For example, even in the case where the addition ratio of a colorant is 5 changed as only one parameter, if the target paint property include not only target color but also target gloss and target viscosity, it is preferable to obtain the change amount in not only color but also gloss and viscosity. This is 2023290761

because the change in the addition ratio of a colorant can influence not only color but also gloss and viscosity. 10 [0036] Next, in this embodiment, the calculation unit of the computer calculates a suitable change amount in the addition ratio of a paint property adjustment material to the pre-adjustment paint composition and/or a suitable change amount in a production condition, using the target data including at least one of the target color, target gloss, and target viscosity and the change 15 amount response curve data acquired in the change amount response curve data acquisition step (calculation step). The calculation step will be described in more detail below.

[0037] In this embodiment, in the calculation step, the change amount in at least one of color, gloss, and viscosity when at least one from among the 20 addition ratios of the plurality of types of colorants, the addition ratio of the one or more types of gloss modifiers, the addition ratio of the one or more types of viscosity modifiers, and the production condition is changed is calculated using the change amount response curve data (step S104: the first step of the calculation step). 25 Calculations in the case where the addition ratios of two or more types of additives are changed are as follows. Take two types of colorants as an example. With a first technique, the change amount in the paint property when the first type of colorant is added is calculated using the change amount response curve. For example, suppose the change is from “pre-adjustment paint 30 property” to “paint property 1”. Then, as the change amount when the second type of colorant is added, the change amount from “paint property 1” can be calculated using the change amount response curve. In the case where two types of colorants are added simultaneously, the respective change amounts from “paint property 0” are calculated for the two types of colorants, and are taken 35 to be change amounts 1 and 2. Then, the paint property after the change can be calculated as “pre-adjustment paint property” + “change amount 1” + “change

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amount 2”. With a second technique, particularly in the case where the change amount in the paint property resulting from adding the first type of colorant is small, the change amount resulting from adding the second type of colorant 5 can be calculated as the change amount from “pre-adjustment paint property” and taken to be “change amount 2’”. In the case where two types of colorants are added simultaneously, the change amount after the addition can be 2023290761

calculated as “pre-adjustment paint property” + “change amount 1” + “change amount 2’”. In this way, the change amount response curve can be made 10 common for the two types of colorants, so that the amount of data to be prepared can be reduced significantly. FIGS. 4A and 4B are diagrams for explaining the first step of the calculation step. A specific calculation method in the second technique will be described. 15 FIG. 4A illustrates the calculation results obtained by substituting , into the change amount response curve, the change amount in each paint film property when a white colorant is added in an addition ratio of each of 0.01 , 0.02 , and 0.03 . Likewise, FIG. 4B illustrates the calculation results in the case of a red colorant. The respective change amounts in L* value when 0.01  of the 20 white colorant is added and when 0.02  of the red colorant is added are WL (0.01) and RL (0.02). The change amount when the two colorants are added simultaneously can be calculated by adding together the respective change amounts in L* value when the two colorants are added separately, that is,

[WL(0.01) + RL(0.02)]. 25 It is also preferable to create a change amount response curve as an approximate curve (by the least squares method, for example) based on the change amount response curve data, and in the calculation step, use this change amount response curve to calculate the change amount in at least one of color, gloss, and viscosity when at least one from among the addition ratios of the 30 plurality of types of colorants, the addition ratio of the one or more types of gloss modifiers, the addition ratio of the one or more types of viscosity modifiers, and the production condition is changed.

[0038] Next, in this embodiment, such a change amount in at least one from among the addition ratios of the plurality of types of colorants, the addition 35 ratio of the one or more types of gloss modifiers, the addition ratio of the one or more types of viscosity modifiers, and the production condition that reduces

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the difference between at least one of color, gloss, and viscosity changed by the calculated change amount in at least one of color, gloss, and viscosity and at least one of target color, target gloss, and target viscosity is calculated (step S105: the latter step of the calculation step). 5 Although not limited, as an indicator, such a change amount in at least one from among the addition ratios of the plurality of types of colorants, the addition ratio of the one or more types of gloss modifiers, the addition ratio of 2023290761

the one or more types of viscosity modifiers, and the production condition that reduces the difference between the target value and the calculated value (for 10 example, reduces the difference to less than or equal to a predetermined threshold or minimize the difference) is calculated. More specifically, let g be gloss, v be viscosity, G be the allowable range of gloss, V be the allowable range of viscosity, and  be the difference from the target. Then, a value that minimizes E under the conditions |g|  G and |v|  V is calculated. Here, 15 E represents the color difference, and is given by E = (L *2 + a *2 + b *2 ) 1/2 .

[0039] As another example, data of the change amount in at least one of color, gloss, and viscosity when at least one from among the addition ratios of the plurality of types of colorants, the addition ratio of the one or more types of gloss modifiers, the addition ratio of the one or more types of viscosity 20 modifiers, and the production condition is changed may be acquired using the change amount response curve data prior to the calculation step, and in the calculation step, such a change amount in at least one from among the addition ratios of the plurality of types of colorants, the addition ratio of the one or more types of gloss modifiers, the addition ratio of the one or more types of 25 viscosity modifiers, and the production condition that reduces the difference between at least one of color, gloss, and viscosity changed by the change amount in at least one of color, gloss, and viscosity acquired in advance and at least one of target color, target gloss, and target viscosity may be calculated.

[0040] Here, it is preferable that the paint property adjustment material 30 includes a plurality of types of colorants and the target paint property includes a target color. In this case, it is preferable that the pre-adjustment paint composition includes one or more types of colorants, the change amount response curve data acquisition step includes obtaining colors in advance by varying the addition ratio of one type of colorant and acquiring change amount 35 response curve data indicating the relationship between the change amount in the addition ratio of one type of colorant and the change amount in color, and

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the calculation step includes calculating a suitable change amount in the addition ratio of the colorant using the target color and the change amount response curve data acquired in the change amount response curve data acquisition step. This is because color is often adjusted in paint adjustment, 5 although not limited.

[0041] In the case where the paint property adjustment material includes a plurality of types of colorants and one or more types of gloss modifiers and/or 2023290761

one or more types of viscosity modifiers, the calculation step is preferably performed as follows. 10 First, a suitable change amount in the addition ratio of a gloss modifier and/or a viscosity modifier is calculated using data of the target gloss and/or the target viscosity and the change amount response curve data acquired in the change amount response curve data acquisition step (first calculation substep). Next, using the suitable change amount in the addition ratio of the gloss 15 modifier and/or the viscosity modifier obtained in the first calculation substep and the change amount response curve data, the change amount in color resulting from adding the gloss modifier and/or the viscosity modifier by the suitable change amount in the addition ratio obtained in the first calculation substep is calculated (second calculation substep). 20 Next, a suitable change amount in the addition ratio of a colorant is calculated using the change amount in color obtained in the second calculation substep (and data of the target color) and the change amount response curve data (third calculation substep). Thus, the suitable change amount in the addition ratio of the colorant 25 can be calculated with the influence of the gloss modifier and/or viscosity modifier on color taken into account.

[0042] Here, the following preparation is preferably performed prior to the calculation step. A step of setting a numerical value generation range for the change amount in at least one of the addition ratio of each colorant, the addition 30 ratio of each gloss modifier, the addition ratio of each viscosity modifier, and each production condition and a step of preparing a data group of the change amounts in the addition ratio of the paint property adjustment material to the pre-adjustment paint composition and/or the change amounts in the production condition, which is formed by combining (for example, randomly) the change 35 amounts in at least one of the addition ratio of a colorant, the addition ratio of a gloss modifier, the addition ratio of a viscosity modifier, and a production

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condition generated within the set numerical value generation range, are performed prior to the calculation step. The data group is not limited, but is preferably consists of, for example, 100,000 to 10 million combinations. In the calculation step, the change amount in at least one of color, gloss, and viscosity 5 when the addition ratio of the paint composition and/or the production condition is changed by each numerical value of the prepared data group of the change amounts in the addition ratio of the paint property adjustment material 2023290761

to the pre-adjustment paint composition and/or the change amounts in the production condition is calculated using the change amount response curve data, 10 and such a change amount in at least one from among the addition ratios of the plurality of types of colorants, the addition ratio of the one or more types of gloss modifiers, the addition ratio of the one or more types of viscosity modifiers, and the production condition that reduces the difference between at least one of color, gloss, and viscosity changed by the calculated change 15 amount in at least one of color, gloss, and viscosity and at least one of target color, target gloss, and target viscosity is calculated. Efficient calculation can thus be performed. The numerical value generation range may be obtained based on a certain range from a preset standard value or actual value of the paint formulation after adjustment. This makes it possible to obtain a 20 calculation result with little deviation from the standard value or actual value. Alternatively, the numerical value generation range may be obtained based on at least one of the pass range of the weather resistance test and the pass range of the metamerism test for the paint film.

[0043] In this embodiment, in the calculation step, the suitable change amount 25 in the addition ratio of the paint property adjustment material to the pre - adjustment paint composition and/or the suitable change amount in the production condition is calculated using a brute-force search technique or a mathematical optimization technique.

[0044] The brute-force search technique is a technique in which, for example 30 in the case where 100,000 to 10 million patterns of change amounts are prepared in the change amount data group preparation step that may be performed prior to the calculation step, the change values in color, gloss, and viscosity are calculated for all of them using the change amount response curve data to determine each change amount in the case where the difference from 35 the target value is reduced in a brute-force manner.

[0045] The mathematical optimization technique is a technique of finding x1,

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x2, x3, and x4 as an optimization problem of a function of colorant addition ratio change amount x1, gloss modifier addition ratio change amount x2, viscosity modifier addition ratio change amount x3, and production condition change amount x4. 5 It is preferable to use a convex optimization technique as the mathematical optimization technique. It is also preferable to use a quadratic programming technique as the mathematical optimization technique. It is also 2023290761

preferable to use a gradient descent technique as the mathematical optimization technique. 10 The effects of the automatic adjustment method according to this embodiment will be described below.

[0046] In the automatic adjustment method according to this embodiment, in the calculation step, the change amount response curve data acquired in the change amount response curve data acquisition step is used to calculate the 15 suitable change amount in the addition ratio of the paint property adjustment material to the pre-adjustment paint composition and/or the suitable change amount in the production condition. This change amount response curve data is obtained using the pre-adjustment paint composition. Hence, the paint property can be automatically adjusted with high accuracy as compared with a 20 method of calculating the amount of colorant to be added to the pre-adjustment paint composition so as to minimize the gap between the absolute value of the color of the pre-adjustment paint composition with a known colorant mixing ratio and the colorant mixing ratio of the target paint composition theoretically calculated from the absolute value of the target color ( as described in the 25 EXAMPLES section below). In addition, the amount of data required is smaller than in the case of machine learning. Moreover, since the change amount response curve data is acquired in such a manner that information of the paint property when only one parameter from among the addition ratio of one or more types of colorants, the addition ratio of one or more types of gloss 30 modifiers, the addition ratio of one or more types of viscosity modifiers, and each production condition is varied is obtained in advance for each parameter, the influence of the change of only one parameter can be obtained accurately, with it being possible to enhance the accuracy of the calculation results in the subsequent calculation step. While measured values can typically contain 35 errors caused by measuring equipment, the method according to this embodiment uses not the absolute value but the change amount in the paint

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property for the change amount response curve data, so that such errors can be canceled and high-accuracy calculation can be performed. In the calculation step, the suitable change amount in the addition ratio of the paint property adjustment material to the pre-adjustment paint 5 composition and/or the suitable change amount in the production condition is calculated using the brute-force search technique or the mathematical optimization technique. These techniques enable accurate calculation of the 2023290761

suitable change amount in the addition ratio of the paint property adjustment material to the pre-adjustment paint composition and/or the suitable change 10 amount in the production condition from the obtained change amount response curve. As described above, the automatic adjustment method according to this embodiment can accurately adjust paint compositions using a simple technique. In particular, it has been found difficult to adjust color, gloss, and 15 viscosity simultaneously because they influence each other. According to the present disclosure, however, in the case where color, gloss, and viscosity are all subjected to change amount calculation as paint properties, color, gloss, and viscosity can be adjusted simultaneously with high accuracy.

[0047] When searching for a single solution using the brute-force search 20 technique, if there are many types of parameters and the number of parameters is large, the number of candidates increases explosively. In the case using the technique in the paint field, suppose there is only one solution. For one parameter, e.g. the addition amount of a colorant, when adding 0 mass to 10 mass of the colorant, there are 100 combinations if the addition amounts are 25 in increments of 0.1 . If there are two types of colorants, the number of combinations is 100  100 = 10,000. When materials are divided into 100 and coating conditions are divided into 10, for a total of 10 parameters, the number of combinations is 10 raised to the power of 20, which is an astronomical number. However, in the paint field, there are the following constraints: 1) 30 there is a range of specifications (there is a range of solutions), 2) there are a plurality of combinations that result in the same solution (for example, a paint composition can be adjusted to black by either using only a black colorant or mixing red, blue, and yellow colorants), and 3) in terms of paint film performance, the amount that can be added is within the limited range of the 35 addition amount of each colorant. Therefore, in practice it is easy to limit the range, such as 20 divisions in a range of 0  to 2 . Due to such specific

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reasons, it is possible to obtain a solution even when random combinations (the number of divisions of one parameter is the same but combinations are random) are used to reduce the number of combinations to a practically acceptable number, such as 10 raised to the power of 6, without calculating all 5 combinations. For this reason, the brute-force search technique can be particularly effectively used in the presently disclosed technology of calculating paint properties. 2023290761

In the production of a paint composition, the closest the color, gloss, or viscosity is to the target is not necessarily the best. For example, suppose 10 the specification for the color difference from the target is within 0.1, and the combination predicted to be closest to the target color uses five materials and has a color difference from the target of 0.01 and the combination predicted to be second closest to the target color uses two materials and has a color difference from the target of 0.02. The second closest combination, which is 15 inferior in color difference from the target by 0.01 but requires addition of a smaller number of materials, can then be determined to satisfy the specification and have the highest productivity. Suitability also needs to be determined based on various factors, such as avoiding the use of expensive materials and materials that are likely to adversely affect paint film performance as much as 20 possible. Although it is theoretically possible to incorporate such coefficients into the formula and perform calculation, in the case where color, productivity, price, paint film performance, etc. are incorporated in one formula, it is difficult to set these coefficients appropriately, and maintenance when factors are added later is complex. If the formula is complex, the solution cannot be 25 calculated in some cases. It is thus difficult to deal with the overall “optimization” of productivity and other factors only by mathematical optimization while a large number of materials are used as in the paint field. The brute-force search technique, on the other hand, calculates all solutions and then selects a suitable combination, and therefore is advantageous in that 30 it is easy to modify the program to meet the user ’s request, such as “selecting a combination that is within the specification ranges of color, gloss, and viscosity and has the smallest number of additives”, after calculating the solutions, and also there is no failure to calculate the solutions. Although it takes time to perform an enormous number of calculations, 35 it is possible to perform calculations in less than 10 seconds on a commercially available personal computer by limiting the numerical value generation range

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and by calculating 10 to 10 billion possible change amount response curves within the possible range in advance and simply selecting from them. In this way, the impact on workability can be minimized. The brute-force search technique can always calculate the optimal 5 solution no matter how complex the conditions and functions (other than convex functions) are.

[0048] The mathematical optimization technique is a technique of finding a 2023290761

solution to an optimization problem, and therefore is suitable for paint property adjustment that requires high accuracy. In addition, calculations can be 10 performed more efficiently and in a shorter time than in brute-force search, and one optimal combination can be obtained mathematically. For example, calculations can be performed easily by using convex optimization of a convex function. In particular, the use of the quadratic programming technique enables easier and faster calculations than convex optimization. 15 [0049] Here, the pre-adjustment paint composition preferably includes two or more of (A1) to (A3): (A1) one or more types of colorants, (A2) one or more types of gloss modifiers, and (A3) one or more types of viscosity modifiers. As mentioned above, colorants, gloss modifiers, and viscosity modifiers can each influence all of color, gloss, and viscosity. Hence, for example, even when 20 the addition ratio of a colorant is changed as only one parameter, as a result of gloss modifiers and viscosity modifiers being included in the pre-adjustment paint composition, such a change amount response curve that takes their influence into account can be obtained, and more accurate calculation results can be obtained in the subsequent calculation step. 25 [0050] <Automatic adjustment system> FIG. 5 is a block diagram of an automatic adjustment system according to an embodiment of the present disclosure. This system is an automatic adjustment system for a paint composition configured to determine, by calculation by a calculation unit of a computer, a suitable change amount in 30 the addition ratio of a paint property adjustment material to a pre -adjustment paint composition and/or a suitable change amount in a production condition for obtaining a target paint property when adjusting a paint composition under a predetermined production condition.

[0051] The paint property adjustment material includes at least one from 35 among a plurality of types of colorants, one or more types of gloss modifiers , and one or more types of viscosity modifiers. The target paint property includes

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at least one of a target color, a target gloss, and a target viscosity. Since the details of these are the same as those in the embodiment of the automatic adjustment method, their repeated description will be omitted.

[0052] As illustrated in FIG. 5, the system 10 includes a computer 11. The 5 computer 11 includes an acquisition unit 12 and a calculation unit 13.

[0053] The acquisition unit 12 is configured to, based on the pre-change paint composition including at least one from among one or more types of colorants, 2023290761

one or more types of gloss modifiers, and one or more types of viscosity modifiers, obtain in advance information of the paint property when only one 10 parameter from among the addition ratio of one or more types of colorants, the addition ratio of one or more types of gloss modifiers, the addition ratio of one or more types of viscosity modifiers, and each production condition is varied, for each parameter, and acquire change amount response curve data indicating the relationship between the change amount in each parameter and the change 15 amount in the information of the paint property. Since the details of this function are the same as those in the embodiment of the automatic adjustment method (change amount response curve data acquisition step ), their repeated description will be omitted. As mentioned above, the acquisition unit 12 may be, for example, a calculation unit (processor) of a computer (in this case, the 20 below-described calculation unit 13 may have this function or a calculation unit other than the calculation unit 13 may be used). Alternatively, the acquisition unit 12 may be, for example, a communication unit capable of receiving the change amount response curve data, or a reading unit having a function of reading the change amount response curve data recorded in memory. 25 [0054] The calculation unit 13 is configured to calculate the suitable change amount in the addition ratio of the paint property adjustment material to the pre-adjustment paint composition and/or the suitable change amount in the production condition, using target data including at least one of the target color, target gloss, and target viscosity and the acquired change amount response 30 curve data. The calculation unit may be a processor, etc. Since the details of the calculation are the same as those in the embodiment of the automatic adjustment method (calculation step), their repeated description will be omitted. The calculation unit calculates the suitable change amount in the addition ratio of the paint property adjustment material to the pre -adjustment 35 paint composition and/or the suitable change amount in the production condition using a brute-force search technique or a mathematical optimization

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technique. Since the details of these techniques are the same as those in the embodiment of the automatic adjustment method (calculation step), their repeated description will be omitted.

5 EXAMPLES

[0055] The presently disclosed techniques will be described in more detail below by way of examples, although the present disclosure is not limited to 2023290761

such.

[0056] First, the methods of preparing colorants used in Examples 1 to 3 and 10 Comparative Examples 1 to 2 will be described. <Preparation example of white colorant> 20 parts by mass of acrylic resin as a resin, 35 parts by mass of isophorone as an organic solvent, and 46 parts by mass of titanium oxide as a white pigment were mixed, and dispersed using a sand mill (dispersion 15 medium: glass beads) until the maximum particle size of coarse pigment particles would be 10 m or less, to prepare a white colorant. <Preparation example of other colorants> Black colorant 1, black colorant 2, a yellow colorant, and a red colorant were prepared in the same manner as in the preparation example of the white 20 colorant, except that the types and amounts of the materials were changed as shown in Table 1. The formulation of each colorant is shown in Table 1.

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[Table 1] Colorant preparation example Black colorant Black colorant White colorant Yellow colorant Red colorant 1 2 Acrylic resin 20 20 20 20 20

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[0057] [Table 1]

Isophorone 35 35 35 35 35 White pigment 46 0 0 0 0 Black pigment 1 0 20 0 0 0 Black pigment 2 0 0 20 0 0 Yellow pigment 0 0 0 46 0 - 26 -

Red pigment 0 0 0 0 46 Solid content concentration (mass) 66 40 40 66 66

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[0058] <Gloss modifier> As a gloss modifier, commercially available silica (silicon dioxide) used as a delustering agent was used. <Viscosity modifier> 5 As a viscosity modifier, isophorone used as a solvent was used.

[0059] <Preparation example of calculation paint composition W> 5 parts by mass of acrylic resin, 25 parts by mass of fluororesin, 35 2023290761

parts by mass of isophorone, and 35 parts by mass of cyclohexanone were added and the resin was uniformly dissolved using a disper. After this, 100 10 parts by mass of the white colorant were added and uniformly mixed using a disper to prepare calculation paint composition W (solid content concentration: 48 mass). <Preparation example of other calculation paint compositions> Calculation paint compositions K1, K2, Y, and R were prepared in the 15 same manner as in the preparation example of calculation paint composition W, except that the types and amounts of the materials were changed as shown in Table 2. The formulation of each calculation paint composition is shown in Table 2.

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[Table 2] Calculation paint composition preparation example

Calculation paint Calculation paint Calculation paint Calculation paint Calculation paint composition W composition K1 composition K2 composition Y composition R

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[0060] [Table 2]

Acrylic resin 5 5 5 5 5 Fluororesin 25 25 25 25 25 Isophorone 35 35 35 35 35 Cyclohexanone 35 35 35 35 35 White colorant 100 0 0 0 0 Black colorant 1 0 100 0 0 0 Black colorant 2 0 0 100 0 0 - 28 -

Yellow colorant 0 0 0 100 0 Red colorant 0 0 0 0 100 Solid content concentration (mass) 48 35 35 48 48

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[0061] <Preparation example of pre-adjustment paint composition 1> 5 parts by mass of acrylic resin, 25 parts by mass of fluororesin, 35 parts by mass of isophorone, and 35 parts by mass of cyclohexanone were added and the resin was uniformly dissolved using a disper. After this, 25 parts 5 by mass of the white colorant, 2 parts by mass of black colorant 1, 69 parts by mass of the yellow colorant, 4 parts by mass of the red colorant, and 2 parts by mass of gloss modifier 1 were added and uniformly mixed using a disper to 2023290761

prepare pre-adjustment paint composition 1 (solid content concentration: 47 mass). 10 [0062] <Preparation example of pre-adjustment paint compositions 2 to 4> Pre-adjustment paint compositions 2 to 4 were prepared in the same manner as in the preparation example of pre-adjustment paint composition 1, except that the types and amounts of the materials were changed as shown in Table 3. The formulation of each pre-adjustment paint composition is shown in 15 Table 3.

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[Table 3] Pre-adjustment paint composition preparation example Pre-adjustment paint Pre-adjustment paint Pre-adjustment paint Pre-adjustment paint composition 1 composition 2 composition 3 composition 4 Acrylic resin 5 5 5 5

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[0063] [Table 3]

Fluororesin 25 25 25 25 Isophorone 35 35 35 35 Cyclohexanone 35 35 35 35 White colorant 25 97 57 2 Black colorant 1 2 0 0 77 Black colorant 2 0 1 8 0 Yellow colorant 69 2 29 7 Red colorant 4 0 6 14 - 30 -

Gloss modifier 1 2 1 0 0 Gloss modifier 2 0 0 2 2 Solid content concentration (mass) 47 47 45 38

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[0064] Details of the materials used to prepare the paint compositions are as follows. - Acrylic resin: Paraloid B44 (produced by Rohm and Haas Company), solid content concentration: 100 mass. 5 - Fluororesin: KYNAR 500 (produced by Arkema S.A.), solid content concentration: 100 mass. - White pigment: TI-PURE R-706 (titanium oxide, produced by 2023290761

DuPont). - Black pigment 1: Mitsubishi Carbon Black MA-100 (carbon black, 10 produced by Mitsubishi Chemical Corporation). - Black pigment 2: SUNBLACK X15 (carbon black, produced by Shiraishi Calcium Kaisha, Ltd.). - Yellow pigment: TAROX Synthetic Iron Oxide LL-XLO (yellow iron oxide, produced by Titan Kogyo, Ltd.). 15 - Red pigment: TODA COLOR 140ED (iron oxide, produced by Toda Kogyo Corporation). - Gloss modifier 1: GASIL HP395 (synthetic silica, produced by INEOS Silicas). - Gloss modifier 2: SYLYSIA 435 (silicon dioxide, produced by Fuji 20 Silysia Chemical Ltd.). - Organic solvent: Isophorone (produced by Arkema S.A.). - Organic solvent: Cyclohexanone (produced by UBE Corporation).

[0065] <Preparation method for paint film of pre-adjustment paint composition> 25 Fine Tough G Primer (epoxy resin primer produced by Nippon Paint Industrial Coatings Co., Ltd.) as undercoat paint was applied to the surface of a material (zinc-aluminum alloy plated steel plate: 1,800 mm  300 mm  0.35 mm) with a roll coater (reference film thickness: 5 m) and then baked for 60 seconds under the condition that the material maximum arrival temperature was 30 210 C, to form an undercoat paint film. Following this, pre-adjustment paint composition 1 was applied onto the undercoat paint film with a roll coater (reference film thickness: 15 m), then baked for 60 seconds under the condition that the material maximum arrival temperature was 250 C, and then immediately cooled to obtain a paint 35 film of the paint composition.

[0066] Next, prediction for each of Examples and Comparative Examples will

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be described. First, the creation of a change amount response curve will be described.

[0067] <Change amount response curve creation example 1> A paint film of pre-change paint composition 1 was created, and data 5 of the color, gloss, and viscosity of the pre-change paint property was acquired. Next, 0.03  of the white colorant was added and a paint film was created in the same manner, and data of color L * value of post-change paint property 1 2023290761

was acquired. Likewise, 0.1 , 0.3 , 1 , 3 , and 10  of the white colorant were added and data of color L * value of post-change paint properties 2 to 7 10 respectively was acquired. From the pre-change paint property and post-change paint property 1 to 7, change amount response curve WL(x)-1 was obtained as an approximate curve using the least squares method or the like. In the same manner as above, paint property data of black colorant 1, yellow colorant, red colorant, gloss modifier 1, and viscosity modifier was 15 acquired and the respective change amount response curves were obtained. The results are shown in Table 4. Moreover, in the same manner as above, the nip pressure of the roll coater, which is one of the production conditions, was changed to –100 Kgf, – 50 Kgf, +50 Kgf, and +100 Kgf and paint films were produced, and change 20 amount response curve PL(x)-1 was obtained. Furthermore, in the same manner as above, the material maximum arrival temperature, which is one of the production conditions, was changed to 10 C, 20 C, –10 C, and –20 C, and change amount response curve D(x)-1 was obtained. 25 [0068] For pre-adjustment paint compositions 2 to 4 (pre-adjustment paint property; L * value: 29 to 90, a * value: –1 to 13, b * value: 2 to 36, gloss: 7 to 29, viscosity: 230 to 260 seconds), respective change amount response curves were obtained in the same manner as above. The results are shown in Table 4.

[0069] <Change amount response curve creation example 2> 30 <Absorption coefficient and scattering coefficient acquisition example 1> Three types of paint compositions: calculation paint composition W, calculation paint composition K1, and a paint composition obtained by mixing calculation paint composition W and calculation paint composition K1 in a ratio of 80:20, were each applied, and the spectral reflectance was measured 35 and the absorption coefficient K and scattering coefficient S of black pigment 1 were calculated.

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[0070] <Absorption coefficient and scattering coefficient acquisition example 2> The absorption coefficient K and scattering coefficient S of each of black pigment 2, yellow pigment, and red pigment were calculated in the same 5 manner as in absorption coefficient and scattering coefficient acquisition example 1, except that calculation paint composition K1 was changed to each of calculation paint compositions K2, Y, and R. 2023290761

[0071] Using these absorption coefficients, scattering coefficients, the refractive indexes of pigments and paint films, the Kubelka-Munk theory, the 10 Duncan’s theory, and the Sanderson correction formula , data of post-change paint property 1c of the paint film when 0.03  of white colorant was added to pre-change paint composition 1 was calculated. Likewise, 0.1 , 0.3 , 1 , 3 , and 10  of the white colorant were added and post-change paint properties 2c to 7c were obtained respectively. From the pre-change paint 15 property and post-change paint properties 1c to 7c, change amount response curve WL(x)-1c was obtained as an approximate curve using the least squares method or the like. In the same manner, a change amount response curve was created for each paint property, each parameter, and each pre -adjustment paint composition. The results are shown in Table 5. 20 [0072] <Pass criterion for paint adjustment> The criterion for pass determination was to satisfy all of the following three conditions. Here, L * , a * , and b * respectively denote the differences in L value, a value, and b value between the target and actual measured values. 1) The value of E = (L * ² + a * ² + b * ²) is 0.05 or less, and L * , 25 a * , b * are each 0.05 or less. 2) As the difference in gloss between the target and actual measured values, the difference from the standard plate is 0.3 or less when the gloss value is less than 10, 0.5 or less when the gloss value is 10 or more and less than 20, and 2.0 or less when the gloss value is 20 or more. 30 3) The difference in viscosity between the target and actual measured values is 5 seconds or less.

[0073] <Pass criterion for number of adjustments> For the four types of paint, an average number of adjustments of less than 3 was determined as pass, and an average number of adjustments of 3 or 35 more was determined as fail.

[0074] <Example 1>

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<Paint adjustment> Data input for correction formulation prediction The lower and upper limits of the correction formulation change range for each colorant and gloss modifier as paint property adjustment material were 5 set to any amounts in the range of 0  to 2  of the total amount of pre- adjustment paint. Likewise, the lower and upper limits of the correction formulation change range for viscosity modifier were set in the range of 0  2023290761

to 10  of the total amount of pre-adjustment paint, the lower and upper limits of the correction formulation change range for nip pressure were set in the 10 range of –100 Kgf to +100 Kgf, and the lower and upper limits of the correction formulation change range for maximum arrival temperature were set in the range of –20 C to 20 C. Based on the set correction formulation change ranges, 10 million sets of candidate data as candidates for a combination of paint property adjustment material correction formulation and coating 15 conditions (i.e. combination of the addition amounts of each colorant, gloss modifier, and viscosity modifier and coating conditions) were created.

[0075] <Formulation prediction using change amount response curve and brute-force search> The 10 million sets of candidate data for addition amounts were 20 substituted into change amount response curves WL(x)-1 to Tg(x)-1 shown in Table 4, thereby obtaining the predicted values of the paint property of post- adjustment paint composition 1. Specifically, the sum of the change amount in L value when substituting the addition amount of white colorant in the first candidate formulation of the 10 million combinations into WL(x)-1 and the 25 change amounts in L value when substituting the addition amounts of black colorant 1, yellow colorant, red colorant, gloss modifier 1, and viscosity modifier, nip pressure, and maximum arrival temperature respectively into KL(x)-1, YL(x)-1, RL(x)-1, ML(x)-1, SL(x)-1, PL(x)-1, and TL(x)-1 was the change amount in L * value of the first candidate formulation. In the same 30 manner, the respective change amounts in a * value, b * value, gloss, and viscosity of the candidate were obtained. This was repeated 10 million times. From among the sets of correction formulation candidate data in each of which the difference of predicted E value was 0.05 or less, the difference of the change amount in gloss was 0.3 or less, and the difference of the change 35 amount in viscosity was 5 seconds or less from the change amounts in target L * , a * , b * values, gloss, and viscosity of post-adjustment paint composition 1,

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one set of candidate data with the smallest total addition amount of paint property adjustment material was extracted to thus obtain the predicted values of the correction addition amount of paint property adjustment material and the correction change amount of coating condition. 5 [0076] <Acquisition of paint property of post-adjustment paint composition> The predicted correction formulation of paint property adjustment material was added to pre-adjustment paint composition 1 to adjust post- 2023290761

adjustment paint composition 1 and obtain its paint property.

[0077] <Readjustment of post-adjustment paint composition> 10 The paint property of post-adjustment paint composition 1 did not meet the pass criterion for the paint property target value, and therefore was determined as fail. The post-adjustment paint composition and post-adjustment paint composition property determined as fail in the previous adjustment were set as 15 the pre-adjustment paint composition and its property in the readjustment. As in the previous adjustment, 10 million sets of candidate data for correction formulation of paint property adjustment material were created. The 10 million sets of candidate data of correction formulation of paint property adjustment material and coating condition were substituted into change amount 20 response curves WL(x)-1, KL(x)-1, YL(x)-1, RL(x)-1, ML(x)-1, SL(x)-1, PL(x)-1, and TL(x)-1, thereby obtaining the predicted values of the paint property of the post-adjustment paint composition (the number of adjustments: 2). In the same manner as for pre-adjustment paint composition 1, the 25 predicted correction formulation of paint property adjustment material was added to the pre-adjustment paint composition to adjust the post -adjustment paint composition and obtain its paint property. This readjustment operation was repeated. Upon determining that the paint property of the post-adjustment paint composition met the pass criterion for its target value, the paint 30 adjustment was completed (the number of adjustments: 2). - Repeat operation 1 The same operation was carried out for two types of pre-adjustment paint compositions with different primary color lots. - Repeat operation 2 35 The same operation was carried out for pre-adjustment paint compositions 2, 3, and 4. For a total of eight types of paint compositions , i.e.

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the four types of paint including pre-adjustment paint composition 1 each with two types of primary color lots, the average number of adjustments until pass was 1.5 times.

[0078] <Example 2> 5 - Property prediction using change amount response curve The same procedure as in Example 1 was carried out, except that change amount response curves WL(x)-1 to TL(x)-1 shown in Table 4 were 2023290761

changed to change amount response curves WL(x)-1c to TL(x)-1c shown in Table 5 respectively. The average number of adjustments until pass was 2.8 10 times for the eight types of paint.

[0079] <Example 3> The same procedure as in Example 1 was carried out, except that the mathematical optimization technique was used instead of the brute-force search technique and a candidate with the smallest difference in E value, gloss, and 15 viscosity was obtained as the predicted value of correction addition amount and coating condition correction change amount. The average number of adjustments until pass was 2.3 times for the eight types of paint.

[0080] <Comparative Example 1> Through the use of basic spectral reflectance (primary data) when 20 mixing a colorant in a predetermined formulation, the color of any colorant mixing ratio was predicted and calculated using the absorption coefficient and scattering coefficient of the pigment, the refractive index of the pigment and paint film, the Kubelka-Munk theory, the Duncan’s theory, and the Sanderson correction formula, and the predicted value of the correction addition amount 25 of the colorant to be added to the pre-toning paint composition was calculated and adjusted so as to minimize the gap between the absolute value of the color of the pre-toning paint composition with a known colorant mixing ratio and the colorant mixing ratio of the target paint composition theoretically calculated from the absolute value of the target color. However, pass was not achieved 30 even after five adjustments. Moreover, the gloss and viscosity as paint properties and the gloss modifier and viscosity modifier as parameters could not be calculated due to the lack of established theoretical formulas.

[0081] <Comparative Example 2> 35 The same procedure as in Example 1 was carried out, except that the changes in color, gloss, and viscosity of 27 colors of paint (pre-adjustment

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paint property: L * value: 24 to 94, a * value: –3 to 10, b * value: –2 to 37, gloss: 3 to 55, viscosity: 130 seconds to 280 seconds) were learned using a neural network from the results of approximately 6,000 changes in paint property adjustment material, coating condition, and paint property to create artificial 5 intelligence for color prediction, and the predicted value of the correction addition amount and coating condition correction change amount was obtained using the brute-force search technique. Pass was not achieved with an average 2023290761

number of adjustments of 5.2 times for the eight types of paint.

[0082] <Evaluation Method> 10 Each paint property was measured as follows in each of Examples and Comparative Examples. 1) Measurement of color data For each paint film obtained by the paint film production method , color (L * , a * , and b * values or differences in L * , a * , and b * values from target standard 15 plate) was measured using a spectrophotometer LabScan XE (produced by HunterLab). 2) Measurement of gloss data For each paint film obtained by the paint film production method, 60° gloss was measured using a glossmeter VG7000 (produced by Nippon 20 Denshoku Industries Co., Ltd.). 3) Measurement of viscosity data For each paint composition obtained in the paint composition preparation example, the number of seconds when measuring each the paint composition with Ford Cup No. 4 at 25 C was taken to be the viscosity value. 25 [0083] In the present disclosure, the meanings of the terms are as follows. The “property adjustability” refers to whether each paint property of color, gloss, and viscosity meets the pass criterion for paint adjustment, that is, whether adjustment of each property is possible. “Adjustable” indicates that adjustment is possible. “Not adjustable” indicates that adjustment is not 30 possible. The “number of adjustments” refers to the average number of adjustments to meet the pass criterion for paint adjustment when a total of eight types of paint compositions, i.e. four types of paint compositions each with two types of primary color lots, are prepared and adjusted. A smaller number 35 of adjustments means higher prediction accuracy. The “limit adjustment color difference” refers to the limit (threshold)

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value within which the target color can be approached. For example, a limit adjustment color difference of 0.03 means that automatic toning is possible up to a color difference of 0.03 from the target color. The “production volume rate” refers to the proportion of the production 5 volume after adjustment where the planned production volume of the target paint composition is 1. A production volume rate not greatly exceeding 100  means that the prediction accuracy of the paint property prediction system and 2023290761

the accuracy of the correction formulation calculation method are high and, while allowing for some errors, the system is efficient without production of 10 more paint composition than necessary. The “required number of sets of data” refers to the number of sets of data that need to be acquired in advance in order to acquire a change amount response curve or acquire artificial intelligence through machine learning. The “required number of coatings” refers to the number of times 15 coating and measurement are performed in order to secure the required number of sets of data. In the case of creating change amount response curve data by calculation, coating and measurement are required when applying a calculation paint composition and measuring spectral reflectance.

20

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[Table 4] Change amount response curve Paint property adjustment material Coating conditions Paint Pre-change Pre-adjustment paint Viscosity Maximum arrival property paint property White colorant Black colorant 1 Black colorant 2 Yellow colorant Red colorant Gloss modifier 1 Gloss modifier 2 Nip pressure modifier temperature Color L* 60 ＷＬ（ｘ）－１ＫＬ（ｘ）－１ - ＹＬ（ｘ）－１ＲＬ（ｘ）－１ＭＬ（ｘ）－１ - ＳＬ（ｘ）－１ＰＬ（ｘ）－１ＴＬ（ｘ）－１

22220763_1 (GHMatters) P124802.AU Color a* Ｗａ（ｘ）－１Ｋａ（ｘ）－１ - Ｙａ（ｘ）－１Ｒａ（ｘ）－１Ｍａ（ｘ）－１ - Ｓａ（ｘ）－１Ｐａ（ｘ）－１Ｔａ（ｘ）－１

[0084] [Table 4]

13 Pre-adjustment paint 1 Color b* 36 Ｗｂ（ｘ）－１Ｋｂ（ｘ）－１ - Ｙｂ（ｘ）－１Ｒｂ（ｘ）－１Ｍｂ（ｘ）－１ - Ｓｂ（ｘ）－１Ｐｂ（ｘ）－１Ｔｂ（ｘ）－１ Gloss 10 Ｗｇ（ｘ）－１Ｋｇ（ｘ）－１ - Ｙｇ（ｘ）－１Ｒｇ（ｘ）－１Ｍｇ（ｘ）－１ - Ｓｇ（ｘ）－１Ｐｇ（ｘ）－１Ｔｇ（ｘ）－１ Viscosity 240 Ｗｖ（ｘ）－１Ｋｖ（ｘ）－１ - Ｙｖ（ｘ）－１Ｒｖ（ｘ）－１Ｍｖ（ｘ）－１ - Ｓｖ（ｘ）－１Ｐｖ（ｘ）－１Ｔｖ（ｘ）－１

Color L* 90 ＷＬ（ｘ）－２ＫＬ（ｘ）－２ - ＹＬ（ｘ）－２ＲＬ（ｘ）－２ - Ｍ２Ｌ（ｘ）－２ＳＬ（ｘ）－２ＰＬ（ｘ）－２ＴＬ（ｘ）－２ Color a* -1 Ｗａ（ｘ）－２Ｋａ（ｘ）－２ - Ｙａ（ｘ）－２Ｒａ（ｘ）－２ - Ｍ２ａ（ｘ）－２Ｓａ（ｘ）－２Ｐａ（ｘ）－２Ｔａ（ｘ）－２ Pre-adjustment paint 2 Color b* 7 Ｗｂ（ｘ）－２Ｋｂ（ｘ）－２ - Ｙｂ（ｘ）－２Ｒｂ（ｘ）－２ - Ｍ２ｂ（ｘ）－２Ｓｂ（ｘ）－２Ｐｂ（ｘ）－２Ｔｂ（ｘ）－２ Gloss 29 Ｗｇ（ｘ）－２Ｋｇ（ｘ）－２ - Ｙｇ（ｘ）－２Ｒｇ（ｘ）－２ - Ｍ２ｇ（ｘ）－２Ｓｇ（ｘ）－２Ｐｇ（ｘ）－２Ｔｇ（ｘ）－２

Viscosity 230 Ｗｖ（ｘ）－２Ｋｖ（ｘ）－２ - Ｙｖ（ｘ）－２Ｒｖ（ｘ）－２ - Ｍ２ｖ（ｘ）－２Ｓｖ（ｘ）－２ - -

Color L* 59 ＷＬ（ｘ）－３ - Ｋ２Ｌ（ｘ）－３ＹＬ（ｘ）－３ＲＬ（ｘ）－３ＭＬ（ｘ）－３ - ＳＬ（ｘ）－３ＰＬ（ｘ）－３ＴＬ（ｘ）－３ - 39 -

Color a* 4 Ｗａ（ｘ）－３ - Ｋ２ａ（ｘ）－３Ｙａ（ｘ）－３Ｒａ（ｘ）－３Ｍａ（ｘ）－３ - Ｓａ（ｘ）－３Ｐａ（ｘ）－３Ｔａ（ｘ）－３ Pre-adjustment paint 3 Color b* 13 Ｗｂ（ｘ）－３ - Ｋ２ｂ（ｘ）－３Ｙｂ（ｘ）－３Ｒｂ（ｘ）－３Ｍｂ（ｘ）－３ - Ｓｂ（ｘ）－３Ｐｂ（ｘ）－３Ｔｂ（ｘ）－３ Gloss 7 Ｗｇ（ｘ）－３ - Ｋ２ｇ（ｘ）－３Ｙｇ（ｘ）－３Ｒｇ（ｘ）－３Ｍｇ（ｘ）－３ - Ｓｇ（ｘ）－３Ｐｇ（ｘ）－３Ｔｇ（ｘ）－３

Viscosity 260 Ｗｖ（ｘ）－３ - Ｋ２ｖ（ｘ）－３Ｙｖ（ｘ）－３Ｒｖ（ｘ）－３Ｍｖ（ｘ）－３ - Ｓｖ（ｘ）－３ - -

Color L* 29 ＷＬ（ｘ）－４ - Ｋ２Ｌ（ｘ）－４ＹＬ（ｘ）－４ＲＬ（ｘ）－４ - Ｍ２Ｌ（ｘ）－４ＳＬ（ｘ）－４ＰＬ（ｘ）－４ＴＬ（ｘ）－４ Color a* 3 Ｗａ（ｘ）－４ - Ｋ２ａ（ｘ）－４Ｙａ（ｘ）－４Ｒａ（ｘ）－４ - Ｍ２ａ（ｘ）－４Ｓａ（ｘ）－４Ｐａ（ｘ）－４Ｔａ（ｘ）－４ Pre-adjustment paint 4 Color b* 2 Ｗｂ（ｘ）－４ - Ｋ２ｂ（ｘ）－４Ｙｂ（ｘ）－４Ｒｂ（ｘ）－４ - Ｍ２ｂ（ｘ）－４Ｓｂ（ｘ）－４Ｐｂ（ｘ）－４Ｔｂ（ｘ）－４ Gloss 7 Ｗｇ（ｘ）－４ - Ｋ２ｇ（ｘ）－４Ｙｇ（ｘ）－４Ｒｇ（ｘ）－４ - Ｍ２ｇ（ｘ）－４Ｓｇ（ｘ）－４Ｐｇ（ｘ）－４Ｔｇ（ｘ）－４ Viscosity 240 Ｗｖ（ｘ）－４ - Ｋ２ｖ（ｘ）－４Ｙｖ（ｘ）－４Ｒｖ（ｘ）－４ - Ｍ２ｖ（ｘ）－４Ｓｖ（ｘ）－４ - -

[Table 5] Change amount response curve Paint property adjustment material Coating conditions Paint Pre-change Pre-adjustment paint Yellow Viscosity Maximum arrival property paint property White colorant Black colorant 1 Black colorant 2 Red colorant Gloss modifier 1 Gloss modifier 2 Nip pressure colorant modifier temperature Color L* 60 ＷＬ（ｘ）－１ｃＫＬ（ｘ）－１ｃ - ＹＬ（ｘ）－１ｃＲＬ（ｘ）－１ｃＭＬ（ｘ）－１ｃ - ＳＬ（ｘ）－１ｃＰＬ（ｘ）－１ｃＴＬ（ｘ）－１ｃ

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[0085] [Table 5]

Color a* 13 Ｗａ（ｘ）－１ｃＫａ（ｘ）－１ｃ - Ｙａ（ｘ）－１ｃＲａ（ｘ）－１ｃＭａ（ｘ）－１ｃ - Ｓａ（ｘ）－１ｃＰａ（ｘ）－１ｃＴａ（ｘ）－１ｃ

Pre-adjustment paint 1 Color b* 36 Ｗｂ（ｘ）－１ｃＫｂ（ｘ）－１ｃ - Ｙｂ（ｘ）－１ｃＲｂ（ｘ）－１ｃＭｂ（ｘ）－１ｃ - Ｓｂ（ｘ）－１ｃＰｂ（ｘ）－１ｃＴｂ（ｘ）－１ｃ

Gloss 10 Ｗｇ（ｘ）－１ｃＫｇ（ｘ）－１ｃ - Ｙｇ（ｘ）－１ｃＲｇ（ｘ）－１ｃＭｇ（ｘ）－１ｃ - Ｓｇ（ｘ）－１ｃＰｇ（ｘ）－１ｃＴｇ（ｘ）－１ｃ

Viscosity 240 Ｗｖ（ｘ）－１ｃＫｖ（ｘ）－１ｃ - Ｙｖ（ｘ）－１ｃＲｖ（ｘ）－１ｃＭｖ（ｘ）－１ｃ - Ｓｖ（ｘ）－１ｃ - -

Color L* 90 ＷＬ（ｘ）－２ｃＫＬ（ｘ）－２ｃ - ＹＬ（ｘ）－２ｃＲＬ（ｘ）－２ｃ - Ｍ２Ｌ（ｘ）－２ｃＳＬ（ｘ）－２ｃＰＬ（ｘ）－２ｃＴＬ（ｘ）－２ｃ

Color a* -1 Ｗａ（ｘ）－２ｃＫａ（ｘ）－２ｃ - Ｙａ（ｘ）－２ｃＲａ（ｘ）－２ｃ - Ｍ２ａ（ｘ）－２ｃＳａ（ｘ）－２ｃＰａ（ｘ）－２ｃＴａ（ｘ）－２ｃ

Pre-adjustment paint 2 Color b* 7 Ｗｂ（ｘ）－２ｃＫｂ（ｘ）－２ｃ - Ｙｂ（ｘ）－２ｃＲｂ（ｘ）－２ｃ - Ｍ２ｂ（ｘ）－２ｃＳｂ（ｘ）－２ｃＰｂ（ｘ）－２ｃＴｂ（ｘ）－２ｃ

Gloss 29 Ｗｇ（ｘ）－２ｃＫｇ（ｘ）－２ｃ - Ｙｇ（ｘ）－２ｃＲｇ（ｘ）－２ｃ - Ｍ２ｇ（ｘ）－２ｃＳｇ（ｘ）－２ｃＰｇ（ｘ）－２ｃｖｇ（ｘ）－２ｃ

Viscosity 230 Ｗｖ（ｘ）－２ｃＫｖ（ｘ）－２ｃ - Ｙｖ（ｘ）－２ｃＲｖ（ｘ）－２ｃ - Ｍ２ｖ（ｘ）－２ｃＳｖ（ｘ）－２ｃ - - - 40 -

Color L* 59 ＷＬ（ｘ）－３ｃ - Ｋ２Ｌ（ｘ）－３ｃＹＬ（ｘ）－３ｃＲＬ（ｘ）－３ｃＭＬ（ｘ）－３ｃ - ＳＬ（ｘ）－３ｃＰＬ（ｘ）－３ｃＴＬ（ｘ）－３ｃ

Color a* 4 Ｗａ（ｘ）－３ｃ - Ｋ２ａ（ｘ）－３ｃＹａ（ｘ）－３ｃＲａ（ｘ）－３ｃＭａ（ｘ）－３ｃ - Ｓａ（ｘ）－３ｃＰａ（ｘ）－３ｃＴａ（ｘ）－３ｃ

Pre-adjustment paint 3 Color b* 13 Ｗｂ（ｘ）－３ｃ - Ｋ２ｂ（ｘ）－３ｃＹｂ（ｘ）－３ｃＲｂ（ｘ）－３ｃＭｂ（ｘ）－３ｃ - Ｓｂ（ｘ）－３ｃＰｂ（ｘ）－３ｃＴｂ（ｘ）－３ｃ

Gloss 7 Ｗｇ（ｘ）－３ｃ - Ｋ２ｇ（ｘ）－３ｃＹｇ（ｘ）－３ｃＲｇ（ｘ）－３ｃＭｇ（ｘ）－３ｃ - Ｓｇ（ｘ）－３ｃＰｇ（ｘ）－３ｃＴｇ（ｘ）－３ｃ

Viscosity 260 Ｗｖ（ｘ）－３ｃ - Ｋ２ｖ（ｘ）－３ｃＹｖ（ｘ）－３ｃＲｖ（ｘ）－３ｃＭｖ（ｘ）－３ｃ - Ｓｖ（ｘ）－３ｃ - -

Color L* 29 ＷＬ（ｘ）－４ｃ - Ｋ２Ｌ（ｘ）－４ｃＹＬ（ｘ）－４ｃＲＬ（ｘ）－４ｃ - Ｍ２Ｌ（ｘ）－４ｃＳＬ（ｘ）－４ｃＰＬ（ｘ）－４ｃＴＬ（ｘ）－４ｃ

Color a* 3 Ｗａ（ｘ）－４ｃ - Ｋ２ａ（ｘ）－４ｃＹａ（ｘ）－４ｃＲａ（ｘ）－４ｃ - Ｍ２ａ（ｘ）－４ｃＳａ（ｘ）－４ｃＰａ（ｘ）－４ｃＴａ（ｘ）－４ｃ

Pre-adjustment paint 4 Color b* 2 Ｗｂ（ｘ）－４ｃ - Ｋ２ｂ（ｘ）－４ｃＹｂ（ｘ）－４ｃＲｂ（ｘ）－４ｃ - Ｍ２ｂ（ｘ）－４ｃＳｂ（ｘ）－４ｃＰｂ（ｘ）－４ｃＴｂ（ｘ）－４ｃ

Gloss 7 Ｗｇ（ｘ）－４ｃ - Ｋ２ｇ（ｘ）－４ｃＹｇ（ｘ）－４ｃＲｇ（ｘ）－４ｃ - Ｍ２ｇ（ｘ）－４ｃＳｇ（ｘ）－４ｃＰｇ（ｘ）－４ｃＴｇ（ｘ）－４ｃ

Viscosity 240 Ｗｖ（ｘ）－４ｃ - Ｋ２ｖ（ｘ）－４ｃＹｖ（ｘ）－４ｃＲｖ（ｘ）－４ｃ - Ｍ２ｖ（ｘ）－４ｃＳｖ（ｘ）－４ｃ - -

[Table 6] Example, Comparative Example Example 1 Example 2 Example 3 Comparative Example 1 Comparative Example 2 Calculation method Change amount response curve Change amount response curve Change amount response curve Theoretical formula calculation Machine learning Change amount response Experiment Calculation Calculation - -

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[0086] [Table 6]

curve creation method Blending amount calculation Brute-force search Brute-force search Mathematical optimization Blending ratio difference correction Brute-force search Color Adjustable Adjustable Adjustable Adjustable Adjustable Property adjustability Gloss Adjustable Adjustable Adjustable Not adjustable Adjustable Viscosity Adjustable Adjustable Adjustable Not adjustable Adjustable Number of adjustments 2.5 2.8 2.3 Not adjustable 5.2 Limit adjustment color difference 0.05 0.05 0.05 0.3 0.1 - 41 -

Production volume rate () 101 101 105 - 104 Required number of sets of data 224 224 224 24 6,000 Required number of coatings 224 48 48 24 6,000

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[0087] As shown in Table 6, in Examples 1 to 3, extremely high-accuracy toning was possible with a limit adjustment color difference of 0.05. Moreover, in Examples 1 to 3, the number of adjustments was less than 3, and thus adjustment was possible with a small number of steps. Furthermore, in 5 Examples 1 to 3, a large number of sets of data were not required, and the number of steps was significantly reduced. In Comparative Example 1 using theoretical formula calculation, high- 2023290761

accuracy toning was not possible with a limit adjustment color difference of 0.3. In addition, due to the lack of an established theoretical adjustment method 10 of gloss and viscosity for paint compositions, the pass criteria could not be met. In Comparative Example 2 using artificial intelligence based on machine learning, a certain level of high-accuracy toning was possible with a limit adjustment color difference of 0.1, but the number of adjustments was large, i.e. 5.2 times, and also the required number of sets of data was very large, i.e. 15 6,000, requiring a large number of steps.

REFERENCE SIGNS LIST

[0088] 10 automatic adjustment system 11 computer 20 12 acquisition unit 13 calculation unit

[0089] It is to be understood that, if any prior art publication (or information derived from it), or any matter which is known, is referred to herein, such 25 reference does not constitute an admission that the publication (or information derived from it) or known matter forms a part of the common general knowledge in the art, in Australia or any other country.

[0090] In the claims which follow and in the preceding description, except 30 where the context requires otherwise due to express language or necessary implication, the word “comprise” or variations such as “comprises” or “comprising” is used in an inclusive sense, i.e. to specify the presence of the stated features but not to preclude the presence or addition of further features in various embodiments of the invention. 35

22220763_1 (GHMatters) P124802.AU

Claims

26 Feb 2026

THE CLAIMS DEFINING THE INVENTION ARE AS FOLLOWS:

5 1. An automatic adjustment method for a paint composition of determining, by calculation by a calculation unit of a computer, a suitable change amount in an addition ratio of a paint property adjustment material to 2023290761

a pre-adjustment paint composition and/or a suitable change amount in a production condition for obtaining a target paint property when adjusting a 10 paint composition under a predetermined production condition , the paint property adjustment material including at least one from among a plurality of types of colorants, one or more types of gloss modifiers, and one or more types of viscosity modifiers, and the target paint property including at least one of a target color, a target gloss, and a target viscosity, the automatic adjustment 15 method comprising: a change amount response curve data acquisition step of , based on a pre-change paint composition, obtaining in advance information of a paint property when only one parameter from among an addition ratio of one or more types of colorants of the plurality of types of colorants, an addition ratio of the 20 one or more types of gloss modifiers, an addition ratio of the one or more types of viscosity modifiers, and the production condition is varied, for each parameter, and acquiring change amount response curve data indicating a relationship between a change amount in each parameter and a change amount in the information of the paint property; and 25 a calculation step of calculating, by the calculation unit of the computer, the suitable change amount in the addition ratio of the paint property adjustment material to the pre-adjustment paint composition and/or the suitable change amount in the production condition, using target data including the at least one of the target color, the target gloss, and the target viscosity and the 30 change amount response curve data acquired in the change amount response curve data acquisition step, wherein in the calculation step, the suitable change amount in the addition ratio of the paint property adjustment material to the pre-adjustment paint composition and/or the suitable change amount in the production 35 condition is calculated using a brute-force search technique.

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2. An automatic adjustment method for a paint composition of determining, by calculation by a calculation unit of a computer, a suitable change amount in an addition ratio of a paint property adjustment material to a pre-adjustment paint composition and/or a suitable change amount in a 5 production condition for obtaining a target paint property when adjusting a paint composition under a predetermined production condition , the paint property adjustment material including at least one from among a plurality of 2023290761

types of colorants, one or more types of gloss modifiers, and one or more types of viscosity modifiers, and the target paint property including at least one of a 10 target color, a target gloss, and a target viscosity, the automatic adjustment method comprising: a change amount response curve data acquisition step of, based on a pre-change paint composition, obtaining in advance information of a paint property when only one parameter from among an addition ratio of one or more 15 types of colorants of the plurality of types of colorants, an addition ratio of the one or more types of gloss modifiers, an addition ratio of the one or more types of viscosity modifiers, and the production condition is varied, for each parameter, and acquiring change amount response curve data indicating a relationship between a change amount in each parameter and a change amount 20 in the information of the paint property; and a calculation step of calculating, by the calculation unit of the computer, the suitable change amount in the addition ratio of the paint property adjustment material to the pre-adjustment paint composition and/or the suitable change amount in the production condition, using target data including the at 25 least one of the target color, the target gloss, and the target viscosity and the change amount response curve data acquired in the change amount response curve data acquisition step, wherein in the calculation step, the suitable change amount in the addition ratio of the paint property adjustment material to the pre -adjustment 30 paint composition and/or the suitable change amount in the production condition is calculated using a mathematical optimization technique.
3. The automatic adjustment method according to claim 1 or 2, wherein in the calculation step: 35 a change amount in at least one of color, gloss, and viscosity when at least one from among addition ratios of the plurality of types of colorants, the

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26 Feb 2026

addition ratio of the one or more types of gloss modifiers, the addition ratio of the one or more types of viscosity modifiers, and the production condition is changed is calculated using the change amount response curve data, and a change amount in the at least one from among the addition ratios of 5 the plurality of types of colorants, the addition ratio of the one or more types of gloss modifiers, the addition ratio of the one or more types of viscosity modifiers, and the production condition that reduces a difference between the 2023290761

at least one of color, gloss, and viscosity changed by the calculated change amount in the at least one of color, gloss, and viscosity and the at least one of 10 the target color, the target gloss, and the target viscosity is calculated.
4. The automatic adjustment method according to claim 1 or 2, wherein prior to the calculation step, data of a change amount in at least one of color, gloss, and viscosity when at least one from among addition ratios of the 15 plurality of types of colorants, the addition ratio of the one or more types of gloss modifiers, the addition ratio of the one or more types of viscosity modifiers, and the production condition is changed is obtained in advance, using the change amount response curve data, and in the calculation step, a change amount in the at least one from among 20 the addition ratios of the plurality of types of colorants, the addition ratio of the one or more types of gloss modifiers, the addition ratio of the one or more types of viscosity modifiers, and the production condition that reduces a difference between the at least one of color, gloss, and viscosity changed by the change amount in the at least one of color, gloss, and viscosity obtained in 25 advance and the at least one of the target color, the target gloss, and the target viscosity is calculated.
5. The automatic adjustment method according to any one of claims 1 to 4, wherein the calculation step includes: 30 a first calculation substep of calculating a suitable change amount in an addition ratio of a gloss modifier and/or a viscosity modifier, using data of the target gloss and/or the target viscosity and the change amount response curve data acquired in the change amount response curve data acquisition step ; a second calculation substep of, using the suitable change amount in 35 the addition ratio of the gloss modifier and/or the viscosity modifier obtained in the first calculation substep and the change amount response curve data,

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calculating a change amount in color resulting from adding the gloss modifier and/or the viscosity modifier by the suitable change amount in the addition ratio obtained in the first calculation substep; and a third calculation substep of calculating a suitable change amount in 5 an addition ratio of a colorant, using the change amount in color obtained in the second calculation substep and the change amount response curve data. 2023290761
6. The automatic adjustment method according to claim 3, further comprising: 10 a step of setting a numerical value generation range for a change amount in at least one of the addition ratio of each colorant, the addition ratio of each gloss modifier, the addition ratio of each viscosity modifier, and the production condition; and a step of preparing a data group of change amounts in the addition ratio 15 of the paint property adjustment material to the pre-adjustment paint composition and/or change amounts in the production condition, by combining change amounts in at least one of the addition ratio of the colorant, the addition ratio of the gloss modifier, the addition ratio of the viscosity modifier, and the production condition generated within the set numerical value generation range, 20 wherein in the calculation step: the change amount in at least one of color, gloss, and viscosity when the addition ratio of the paint property adjustment material to the pre- adjustment paint composition and/or the production condition is changed by each numerical value of the prepared data group of the change amounts in the 25 addition ratio of the paint property adjustment material to the pre -adjustment paint composition and/or the change amounts in the production condition is calculated using the change amount response curve data, and the change amount in the at least one from among the addition ratios of the plurality of types of colorants, the addition ratio of the one or more types 30 of gloss modifiers, the addition ratio of the one or more types of viscosity modifiers, and the production condition that reduces the difference between the at least one of color, gloss, and viscosity changed by the calculated change amount in the at least one of color, gloss, and viscosity and the at least one of the target color, the target gloss, and the target viscosity is calculated. 35
7. The automatic adjustment method according to claim 2, wherein a

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convex optimization technique is used as the mathematical optimization technique.
8. The automatic adjustment method according to claim 2, wherein a 5 quadratic programming technique is used as the mathematical optimization technique. 2023290761
9. The automatic adjustment method according to claim 2, wherein a gradient descent technique is used as the mathematical optimization technique. 10
10. The automatic adjustment method according to any one of claims 1 to 9, wherein the pre-adjustment paint composition includes two or more of (A1) to (A3): (A1) the one or more types of colorants, (A2) the one or more types of gloss modifiers, and (A3) the one or more types of viscosity modifiers. 15
11. The automatic adjustment method according to any one of claims 1 to 10, wherein the production condition includes one or more of (a) to (d): (a) one or more of viscosity and heating residue of paint, (b) one or more of roll peripheral speed, spray discharge amount, 20 electrodeposition coating voltage, coating pressure , and paint flow rate in a step of applying the paint composition to a coated matter, (c) one or more of maximum arrival temperature of the coated matter, baking temperature, and baking time in a baking step, and (d) one or more of environmental temperature and humidity of a 25 production line and temperature of the paint.
12. The automatic adjustment method according to any one of claims 1 to 11, wherein the paint property adjustment material includes the plurality of types of colorants, 30 the target paint property includes the target color, the pre-adjustment paint composition includes the one or more types of colorants, the change amount response curve data acquisition step includes obtaining colors in advance by varying an addition ratio of one type of colorant 35 and acquiring the change amount response curve data indicating a relationship between a change amount in the addition ratio of the one type of colorant and

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a change amount in color, and the calculation step includes calculating a suitable change amount in the addition ratio of the colorant, using the target color and the change amount response curve data acquired in the change amount response curve data 5 acquisition step.
13. An automatic adjustment system for a paint composition configured to 2023290761

determine, by calculation by a calculation unit of a computer, a suitable change amount in an addition ratio of a paint property adjustment material to a pre - 10 adjustment paint composition and/or a suitable change amount in a production condition for obtaining a target paint property when adjusting a paint composition under a predetermined production condition , the paint property adjustment material including at least one from among a plurality of types of colorants, one or more types of gloss modifiers, and one or more types of 15 viscosity modifiers, and the target paint property including at least one of a target color, a target gloss, and a target viscosity, the automatic adjustment system further comprising an acquisition unit configured to, based on a pre-change paint composition, obtain in advance information of a paint property when only one 20 parameter from among an addition ratio of one or more types of colorants of the plurality of types of colorants, an addition ratio of the one or more types of gloss modifiers, an addition ratio of the one or more types of viscosity modifiers, and the production condition is varied, for each parameter, and acquire change amount response curve data indicating a relationship between 25 a change amount in each parameter and a change amount in the information of the paint property, wherein the calculation unit is configured to calculate the suitable change amount in the addition ratio of the paint property adjustment material to the pre-adjustment paint composition and/or the suitable change amount in 30 the production condition, using target data including the at least one of the target color, the target gloss, and the target viscosity and the acquired change amount response curve data, and the calculation unit is configured to calculate the suitable change amount in the addition ratio of the paint property adjustment material to the 35 pre-adjustment paint composition and/or the suitable change amount in the production condition, using a brute-force search technique.

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14. An automatic adjustment system for a paint composition configured to determine, by calculation by a calculation unit of a computer, a suitable change amount in an addition ratio of a paint property adjustment material to a pre - 5 adjustment paint composition and/or a suitable change amount in a production condition for obtaining a target paint property when adjusting a paint composition under a predetermined production condition , the paint property 2023290761

adjustment material including at least one from among a plurality of types of colorants, one or more types of gloss modifiers, and one or more types of 10 viscosity modifiers, and the target paint property including at least one of a target color, a target gloss, and a target viscosity, the automatic adjustment system further comprising an acquisition unit configured to, based on a pre-change paint composition, obtain in advance information of a paint property when only one 15 parameter from among an addition ratio of one or more types of colorants of the plurality of types of colorants, an addition ratio of the one or more types of gloss modifiers, an addition ratio of the one or more types of viscosity modifiers, and the production condition is varied, for each parameter, and acquire change amount response curve data indicating a relationship between 20 a change amount in each parameter and a change amount in the information of the paint property, wherein the calculation unit is configured to calculate the suitable change amount in the addition ratio of the paint property adjustment material to the pre-adjustment paint composition and/or the suitable change amount in 25 the production condition, using target data including the at least one of the target color, the target gloss, and the target viscosity and the acquired change amount response curve data, and the calculation unit is configured to calculate the suitable change amount in the addition ratio of the paint property adjustment material to the 30 pre-adjustment paint composition and/or the suitable change amount in the production condition, using a mathematical optimization technique.

22220763_1 (GHMatters) P124802.AU