JP2006218426A - Coating method, coating control unit and coating equipment - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide a coating method capable of stably keeping the visual characteristics such as a color, a quality feeling and the like of a coating film even in a case that the compounding condition or the like of coating is altered, a coating control unit and coating equipment. <P>SOLUTION: In this coating method, coating is sprayed on the article to be coated in a coating booth using the automatic coating machine arranged in the coating booth. When coating is applied to the article to be coated using newly compounded and planned coating, the visual characteristics including the color and quality feeling of the coating film of the newly compounded and planned coating are set to a target variable and the factor related to the compounding condition of the coating and at least one coating condition and/or the factor related to the coating condition are set to an explanation variable while the data housed in a data base is used to perform multiple regression analysis to form a multiple regression formula. The relation between the target variable and the explanation variable in coating work is operated using the obtained multiple regression formula and coating operation is controlled and/or monitored on the basis of the operation result. <P>COPYRIGHT: (C)2006,JPO&NCIPI

Description

  The present invention relates to a coating method for a vehicle such as an automobile, a home appliance, a building material, a coating control apparatus, and a coating facility. More specifically, the present invention seeks a coating condition and a coating condition corresponding to a change in a paint blending condition, and performs a coating operation. It is related with the coating method, the coating control apparatus, and coating equipment which can obtain the coating film with which visual characteristics, such as a color, a texture, and a glittering feeling, were stabilized by controlling.

  Paints are usually applied to the surface of vehicles such as passenger cars, household appliances such as refrigerators and washing machines, and building materials such as outer wall materials. This coating focuses on protecting the base steel plate and the like, and finishing it with an aesthetic appearance. Therefore, in the painting process in the production line, the coating film has bumps (projections on the surface of the coating film), different colors (difference between the target color and the coating color), sagging (locally thick part where the coating film dripped), In addition to preventing the occurrence of paint defects such as repellency (part of the paint surface with no dents or paint), armpits (pinholes), etc., especially in the overcoating stage, stabilizing the visual properties such as the color and texture of the paint film Great care is taken to make it easier.

  For example, in the case of top coat painting such as passenger cars, the object to be coated moves at a predetermined line speed in the top coat booth where temperature, humidity, etc. are controlled, and in the meantime, an automatic coating machine installed in the paint booth. It is painted by using. The automatic coating machine is equipped with, for example, a rotary atomizing electrostatic coating machine called a bell type coating machine, and by spraying the paint under a predetermined coating condition and coating condition using the bell type coating machine. Painting is done. The paint conditions include the proportion of the solvent contained in the paint, the proportion of the solid content, the viscosity, etc. In the case of the bell type coating machine, the painting conditions include the temperature and humidity of the painting atmosphere. Wind speed, coating machine moving speed, coating object moving speed, distance between coating machine coating gun and coating object, applied voltage, paint discharge rate, bell cup rotation speed of bell type coating machine, shaping air temperature, Shaping air humidity, shaping air pressure, shaping air flow rate and the like are included.

  The visual characteristics of the paint color such as color and texture are affected by various factors as described above. Therefore, the coating composition is ensured for the object to be coated so that the predetermined coating thickness can be secured and the target color and texture can be obtained within the constraint that the predetermined line speed is maintained. Accordingly, the coating is performed under finely controlled coating conditions and coating conditions.

  In recent years, in the automobile industry, various paint colors have been applied so that automobile users have a good impression of cars and can select a paint color according to their preference. It has been broken. In particular, a metallic color using a flaky metal pigment and a pearl color containing a pearl pigment coated with titanium dioxide on a flaky substrate have come to be used. In the case of these paint colors, the color and texture may change slightly even with slight changes or changes in the paint conditions and paint conditions described above. To obtain the target color and texture, Careful management and fine adjustments have been made.

  In the management and adjustment of the paint conditions and the paint conditions, if the target color, texture, etc. cannot be obtained, the composition of the paint is changed. The change in paint composition is, for example, the set paint composition conditions, that is, the type of resin as a solid content and its proportion, the type of colorant and its proportion, the type of glitter pigment and its proportion Etc., at least one condition change is included. When the composition of the paint is changed, the paint condition and painting condition must be newly set in accordance with the change of the composition.

  The above-described change in the blending condition of the paint and the new setting of the paint condition and the paint condition corresponding to the change in the blending condition are determined only after a skilled paint engineer, a paint engineer, etc. repeat trial and error. Therefore, a lot of time, man-hours and costs are required for newly setting the paint conditions and the paint conditions. In addition, if new conditions are not determined within the scheduled period, and if the target color and texture cannot be obtained under the newly set conditions, not only may defective products be generated, but If this is the case, it may happen that the painting line must be stopped. Losses for this purpose may be immeasurable, such as a decrease in production volume, or in some cases, payment of compensation to customers due to delays in delivery, or a decline in credit.

  In order to prevent the above situation from occurring, the paint conditions can be changed easily so that a certain level of finished skin can be obtained against fluctuations in the coating environment by simulation that predicts the finished skin of the paint film. A coating method that can be used has been proposed (for example, Patent Document 1). The method disclosed in Patent Document 1 is directed to a method of spraying an object to be coated conveyed continuously or in a tact manner with an automatic machine or a painting robot that drives an atomizing coating machine. Control coating conditions based on detection signals of atmospheric temperature and humidity, detection signals of finished skin of coating film, and pre-programmed paint conditions, painting conditions, painting environmental conditions, etc. and finished skin It is supposed to be.

  In the method disclosed in Patent Document 1, a relational expression is used to express the finished skin at the standard time and when the condition changes. W. The value is obtained and the L. W. The paint condition and the paint condition are obtained by simulation so that the value becomes the target value. The above relational expression indicates that the atomization characteristic values such as paint particles and the L.P. W. The empirical formula of the relationship with the value, paint conditions, paint conditions and L. W. It is configured based on the empirical formula of the relationship with the value. However, the latter empirical formula uses an exponential function, and all factors are expressed in the form of products of powers (powers). W. The degree of contribution of each factor to the value is not clear, it cannot be said that the accuracy is necessarily sufficient, and there is a problem that even the response to the change in line speed is not considered.

L. W. Although it is not intended for the finished skin of the paint film such as the value, a method has been proposed that uses the multiple regression equation to accurately estimate the thickness of the paint film to be painted with a bell-type painter ( For example, Patent Document 2). The method disclosed in Patent Document 2 is an explanatory variable that includes six variables: a moving speed of a coating machine, a distance between a coating gun and an object to be coated, an applied voltage, a discharge amount of paint, a shaping air pressure, and a bell cup rotation speed. The film thickness is calculated and estimated by creating a multiple regression equation with the film thickness as an objective variable and performing a coating simulation using the multiple regression equation. In this method, the thickness of the coating film can be estimated, but visual characteristic values such as the color and texture of the coating film cannot be estimated and controlled.
JP 2000-246167 A Japanese Patent Laid-Open No. 9-75839

  The present invention has been made to solve the above-mentioned problems, and even when a new paint blending design is performed and the paint blending conditions are changed, the color, texture, etc. of the coating film It is an object of the present invention to provide a painting method, a painting control device, and painting equipment that can stably maintain the visual characteristics of the painting.

  The painting method (1) according to the present invention has been newly designed in a painting method by spraying paint onto an object to be coated in the painting booth using an automatic painting machine arranged in the painting booth. Factors related to the paint blending conditions, with the visual characteristics of the paint color including the color and texture of the paint film newly designed and blended as the objective variable when coating the object with the paint By using a multiple regression equation obtained by performing multiple regression analysis using data stored in a database with at least one paint condition and / or factor relating to painting conditions as explanatory variables, painting is performed. The relationship between the objective variable and the explanatory variable in the operation is calculated, and the painting operation is controlled and / or monitored based on the result.

  In the painting method (2) according to the present invention, when performing the multiple regression analysis in the painting method (1), it is determined whether or not multiple regression analysis is possible based on the data stored in the database. When there is insufficient data, a test panel is prepared using the newly designed paint, and the multiple regression analysis is performed by supplementing the insufficient data.

  Further, in the coating method (3) according to the present invention, in the coating method (1) or (2), the factors relating to the blending conditions are the blending ratio of the resin component of the paint, the blending ratio of the coloring material, and the glitter. Including at least one of pigment blending ratios, and the factor relating to the paint conditions includes at least one of the viscosity of the paint, the blending ratio of solid content, and the blending ratio of the solvent for dilution, and the coating conditions The factors relating to the above are the discharge amount of the paint, the temperature of the paint atmosphere, the humidity of the paint atmosphere, the wind speed of the paint atmosphere, the moving speed of the automatic coating machine, the moving speed of the object to be coated, and between the paint gun and the object to be coated Including at least one of a distance, an applied voltage, a bell cup rotation speed, an atomizing air pressure, an atomizing air flow rate, a shaping air pressure, a shaping air temperature, a shaping air humidity, and a shaping air flow rate, Visual characteristics include Munsell color system chromaticity, L * a * b * color system chromaticity, L * C * h color system chromaticity, Hunter Lab color system chromaticity, XYZ color system It includes at least one of chromaticity, spectral reflectance, IV value, SV value, and flip-flop value of the system.

  A painting control apparatus according to the present invention is a painting control apparatus used for controlling any of the painting methods (1) to (3), and is a data storage unit for a multiple regression equation that serves as a database. , Equipped with a calculation / control unit, an input unit and an output unit, and for the newly designed paint, the visual characteristics of the paint color including the color and texture of the paint film are set as objective variables, and the paint composition conditions It was obtained by performing multiple regression analysis using the data stored in the multiple regression equation data storage unit, with the factor and the factor relating to at least one paint condition and / or coating condition as explanatory variables By using a multiple regression equation, a relationship between the objective variable and the explanatory variable in the painting operation is calculated, and a function of controlling and / or monitoring the painting operation based on the result is provided.

  A painting facility according to the present invention is an automatic painting facility that performs painting while moving a plurality of objects in a painting booth, and includes the above-described painting control device and is stored in the painting control device. Using a multiple regression equation, the relationship between the objective variable value and the explanatory variable value is calculated, and the paint color visual characteristic value related to the objective variable value and the paint condition and / or coating condition related to the explanatory variable value are calculated. The value of the factor relating to the paint condition and / or the coating condition is calculated so that the value of the factor concerned falls within an allowable range, and the painting operation is controlled and / or monitored based on the result. It is characterized by being.

  As used herein, the “visual characteristics of the paint color” means visual characteristics of the paint color that can be measured, such as the color of the coating film, the texture including glitter, and the spectral reflectance. In the following description, “visual characteristic of paint color” may be abbreviated as “visual characteristic”. Furthermore, the “predetermined paint composition” means a paint in which the components constituting the paint and the blending ratio thereof are defined by standards, specifications, and the like.

  According to the above-mentioned coating method (1), even when coating an object to be coated using a newly designed and designed paint, appropriate paint conditions and / or paint conditions that satisfy the visual characteristic value of the paint color Can be obtained accurately and promptly by using a multiple regression equation. In particular, since a multiple regression equation is used, a test using many test panels is not required, so that an excellent effect that an appropriate paint condition and / or paint condition can be obtained efficiently and economically is obtained. is there. Moreover, the relationship between the visual characteristic value of the coating film in the coating line and the coating operation conditions can be analyzed at all times. Therefore, it is possible to quickly and surely apply the newly formulated paint to the actual operation without relying on some paint engineers with high capacity as in the past. The operating status can be monitored constantly.

  Further, according to the painting method (2), since a multiple regression equation is created by supplementing the deficient data among the data accumulated in the database, a highly accurate multiple regression equation can be efficiently obtained. it can.

  In addition, according to the painting method (3), since the multiple regression analysis is performed using the factors related to the paint conditions and the painting conditions for each visual characteristic value of the paint color, among those factors, A factor having a strong correlation with the visual characteristic value can be obtained. Therefore, a multiple regression equation having a higher multiple correlation coefficient or explanation rate can be obtained.

  According to the coating control device, since it has a function capable of performing any of the coating methods (1) to (3), the effect obtained by any of the coating methods (1) to (3). The same effect can be obtained.

  According to the above-mentioned painting equipment, since it is provided with the above-mentioned painting control device and is configured to be able to carry out any of the above-mentioned painting methods (1) to (3), The same effect as that obtained can be obtained.

  First, the coating method which concerns on embodiment of this invention is demonstrated concretely. The painting method according to the embodiment is directed to a method of painting by spraying a paint on an object moving in the painting booth using an automatic painting machine arranged in the painting booth. Usually, the temperature in the painting booth is controlled to a predetermined condition, and when a water-based paint is used, the humidity is controlled in addition to the temperature. Under such conditions, the coating is performed while controlling the conditions so that a coating film satisfying a predetermined visual characteristic value can be obtained under predetermined coating conditions and coating conditions. In addition, a rotary atomizing electrostatic coating machine called a bell type coating machine is mainly used for spraying paint. In addition, the coating method which concerns on embodiment of this invention is applicable also to the coating in the coating booth where temperature and humidity are not controlled.

  In the case of the coating method according to the embodiment, when the blending conditions of the paint are changed in the actual painting operation as described above, the color and texture of the coating film obtained by painting the paint with the new blending The object is to determine the paint conditions and the paint conditions such that the visual characteristic values such as these become the target values in the painting work, and to control and monitor the painting operation based on the results. That is, the method according to the embodiment controls the visual characteristic value obtained by promptly and reliably obtaining and reflecting the paint condition and the paint condition corresponding to the change in the paint composition condition in the paint operation. And fulfill the role of monitoring.

  For this purpose, one of the visual characteristics including the color and texture of the coated film is set as the objective variable, and the factor related to the blending condition of the paint and the factor related to at least one paint condition and the coating condition as explanatory variables, By creating multiple regression equations in advance using the data stored in the database and using the obtained multiple regression equations, the relationship between objective variables and explanatory variables in actual operation, that is, visual characteristic values and paint Calculate the relationship between the blending conditions, paint conditions and the values of the factors related to the coating conditions, and based on the calculation results, at least one paint condition corresponding to the paint with the new blending conditions and the appropriate values of the factors related to the coating conditions By selecting, the painting operation can be controlled and / or monitored.

  In the case of the multiple regression equation used in the coating method according to the embodiment, at least one appropriate condition among the paint condition and the paint condition must be selected in accordance with the change in the paint blending condition. Therefore, the multiple regression equation includes a factor related to the blending condition of the paint to be changed, and the visual characteristic value can be controlled in response to the change in the blending condition of the paint. Or it is a formula that includes factors related to painting conditions.

  The main factors related to the blending conditions of the paint are the blending ratio of each resin contained as a solid content in the paint, the blending ratio of the coloring material (coloring pigment, dye, etc.), the blending ratio of the glitter pigment, and the additive. There are blending ratios. Further, the factors relating to the paint conditions include the viscosity of the paint, the blending ratio of the solid content of the paint, the blending ratio of the diluent solvent, and the like. Factors related to painting conditions include paint discharge rate, painting atmosphere temperature, painting atmosphere humidity, painting atmosphere wind speed, moving speed of automatic coating machine, moving speed of coated object, painting gun and coated object. Distance, applied voltage, bell cup rotation speed (hereinafter abbreviated as bell rotation speed), atomizing air pressure, atomizing air amount, shaping air pressure, shaping air temperature, shaping air humidity, shaping air flow rate, etc. It is. When an air atomizing type coating machine is used as the automatic coating machine, the atomizing air pressure or the atomizing air flow rate is included in the coating conditions instead of the bell rotation speed of the bell type coating machine.

  The objective variable Y is a visual characteristic, and as described above, the visual characteristic includes the color of the coating film, the texture of the paint color including glitter, the spectral reflectance, and the like. Among them, the color of the coating film is the Munsell color system, L * a * b * color system, L * C * h color system, Hunter Lab color system, and XYZ color system. It can be expressed using at least one. The texture of the paint color is expressed by, for example, glitter feeling. The glitter feeling is an IV value that represents the glitter feeling in the regular reflection direction of the coating film, an SV value that represents the glitter feeling in the watermark direction, and the relationship between the two. It can be represented by a flip-flop value (FF value) representing the orientation state of the conductive pigment. Furthermore, a value measured by a commercially available colorimeter or the like can be used as the chromaticity, and a value measured by a spectrophotometer can be used as the spectral reflectance.

  FIG. 1 is a schematic plan view showing a configuration of a main part of a painting facility 10 that is generally used. Hereinafter, the coating method according to the embodiment will be described more specifically with reference to the drawings. The article 11 moves in the direction of arrow A in the painting booth 12. An automatic painting machine 13 such as a bell type is arranged in the painting booth 12, and the automatic painting machine 13 shown in FIG. 1 includes a painting machine 13a for horizontal part painting and a painting machine 13b for vertical part painting. It consists of This automatic painting machine 13 may be a robot type automatic painting machine. The automatic coating machine 13 includes a bell-type coating machine that is a rotary atomizer, and paints the coating object 11 by spraying the coating material 11 from the bell-type coating machine. The coated object 11 after painting leaves the painting booth 12 and is sent to a drying furnace or the like.

  FIG. 2 is a diagram schematically showing an example of a cross-sectional structure of a main part of the bell type coating machine 20 and its control system. The coating gun 21 of the bell type coating machine 20 includes a coating material discharge port 22a of a coating material supply nozzle 22, a bell cup 23 that rotates at high speed, an air guide 24, an annular air outlet port 24a for shaping air, and the like. When the coating material is supplied from the coating material discharge port 22a, it is atomized by the centrifugal force of the rotating bell cup 23 and the shaping air sprayed from the air outlet port 24a, and the atomized coating material is sprayed on the article 11 to be coated. Painted. The control system 25 includes an automatic coating machine controller 26, a shaping air controller 26a (adjustment of pressure and flow rate), a rotation speed controller 26b of the bell cup 23, a paint supply amount controller 26c, and an automatic coating machine controller 26. Input / output means 27 connected to the.

The coating method according to the embodiment is a coating method using the coating equipment 10 and the automatic coating machine 13 as described above. In order to perform control and monitoring, a multiple regression analysis is performed on the relationship between the visual characteristics (objective variables) such as color and texture, and the factors related to paint conditions and paint conditions (explanatory variables), and a multiple regression equation is obtained. Based on the obtained multiple regression equation, the painting operation is basically controlled. The basic form of this multiple regression equation is expressed by the following equation (1).
_{Y = k 1 · f (x} 1) + k 2 · f (x 2) + ····· + k n · f (x n) + e (1)
(1) In the formula, Y is the objective _{variable, f (x 1) ~f (} x n) is an explanatory _variable, k 1 to k _n are regression coefficients, e is the residual. x _{1 to} x _n are the respective factors relating to the paint blending conditions, paint conditions, and coating conditions already described, and all the factors are included in the multiple regression analysis. However, some factors that have a strong correlation with the objective variable have been clarified, and when there is no need to use other factors with a weak correlation, the range that can be changed from the viewpoint of the stability of the painting operation, etc. If there are factors that are narrowly limited and weakly correlated with the objective variable, multiple regression analysis can be performed by excluding those factors from the explanatory variables.

The explanatory variable related to the factor _xn used in the multiple regression analysis is represented by the function form of _xn , that is, f ( _xn ). Specifically, as the explanatory variable, the value of each factor is used as it is, square, cube, square root, reciprocal, logarithm, or the like. Regarding the function, it is preferable to select a function form that is theoretically, empirically, or experimentally optimal for each factor. When each factor alone has a small correlation with the objective variable, and any of addition, subtraction, multiplication and division between the factors has a large correlation with the objective variable, a value obtained by combining the factors can be used as the explanatory variable.

When creating a multiple regression equation, basically, a multiple regression analysis is performed using all the factors relating to the paint blending conditions, paint conditions, and coating conditions as explanatory variables. However, as described above, when several factors having a strong correlation with the objective variable have been clarified, multiple regression analysis can be performed focusing on those factors. In the case of the coating method according to the present embodiment, factors relating to the blending conditions of the paint, for example, the bell rotation speed or the bell rotation speed and the shaping air pressure are used as explanatory variables, and visual characteristics are used as objective variables. By performing regression analysis, a multiple regression equation having a high multiple correlation coefficient (R) and high explanation rate (R ² ) can be created. Therefore, in the case of the embodiment described later, an example will be described in which multiple regression analysis is performed using the bell rotation speed or the bell rotation speed and the shaping air pressure as factors as the explanatory variable values in addition to the paint blending conditions.

  However, there are many combinations of the relationship between the objective variable and the explanatory variable that can provide a high multiple correlation coefficient, explanatory rate, etc., and the factors that have an important influence on the objective variable may differ in each case. is there. Therefore, it is preferable to select an appropriate factor as an explanatory variable in each case. Of course, if the factors that have a strong correlation with the objective variable are not clear, a multiple regression analysis is performed with all of the target factors as explanatory variables. In addition, in order to further improve the accuracy of the multiple regression equation, it is preferable to select an explanatory variable having a strong correlation with the objective variable and to perform multiple regression analysis.

  FIG. 3 is a flowchart showing a procedure for creating a multiple regression equation used in the coating method according to the embodiment. The creation of the multiple regression equation can be carried out using a device such as a personal computer that can perform multiple regression analysis (hereinafter referred to as a simulator) or a coating control device according to an embodiment of the present invention that will be described later. it can. Note that general-purpose software can be used for the multiple regression analysis. Examples of applicable software include Lotus 1-2-3 (registered trademark) manufactured by Lotus, Excel series manufactured by Microsoft, and statistical calculation. There is JUSE-QCAS (registered trademark) manufactured by Japan Science and Technology Institute, which is dedicated software.

  In step S1, a blending condition for a newly blended paint is input. As described above, as a blending condition of the paint, a target value and / or a range (for example, an allowable range) of a blending ratio of each resin, a coloring material, a bright pigment, an additive, and the like that are solid contents are input. In addition, data such as the blending ratio of the solvent is appropriately input as necessary.

  In step S2, a target value and / or a range (for example, an allowable range) of the visual characteristic value regarding the newly blended paint is input. As described above, the input visual characteristic values are FF value, Munsell color system, L * a * b * color system, L * C * h color system, Hunter Lab color system, XYZ color system. Is a value such as

  Next, the process proceeds to step S3, in which the factors essential for the multiple regression analysis among the factors relating to the paint conditions and the coating conditions are designated, and the range of the factor values is designated as necessary. The factors specified here are factors that need to be included in the multiple regression equation, and are effective for controlling the visual characteristic value, for example, the bell rotation speed, the shaping air pressure, and the like. If there is no essential factor in the multiple regression analysis or if it is unknown, step S3 is skipped and the process proceeds from step S2 to step S4.

  In step S4, when data necessary for multiple regression analysis is stored in advance as a database in a simulator or the like, it is determined whether or not multiple regression analysis is possible using the data stored in the database. The determination as to whether or not the data can be used for the multiple regression analysis includes, for example, the presence or absence of data within the range of the conditions provided in the data input in steps S1 and S2 or data having a value close to the range, and step S3. It is possible to make a judgment based on the presence or absence of data relating to essential factors among the paint conditions and painting conditions input in. If it is determined in step S4 that a multiple regression equation can be created using data existing in the database, the process proceeds to step S5.

  In step S5, a multiple regression analysis is performed using, for example, any of the above-described multiple regression analysis software to create a multiple regression equation. In determining the multiple regression equation, the factors relating to the blending conditions of the paint and the factors relating to at least one paint condition or paint condition having a strong correlation with the visual characteristic value are included. Choose a multiple regression equation with a high. The above-mentioned factors relating to paint conditions or painting conditions having a strong correlation with the visual characteristic values are factors necessary for controlling the visual characteristic values relating to the newly designed paint in a predetermined range.

  In step S6, the obtained multiple regression equation is stored in a storage unit such as a simulator. In the case of storing a multiple regression equation, it is preferable to store the data used to create the multiple regression equation in association with the obtained multiple regression equation.

  Next, it progresses to step S7 and it is judged whether simulation is performed. Although not shown, whether or not to perform the simulation is based on information about the necessity of simulation input in advance. If it is determined that the simulation is required, the process proceeds to step S8. In step S8, data such as paint blending conditions necessary for the simulation is input. Next, in step S9, a simulation is performed using the multiple regression equation obtained in step S5, the process proceeds to step S10, and a multiple regression equation is output as necessary as a result of the simulation. The accuracy of the obtained multiple regression equation is confirmed in advance by this simulation.

  If it is determined in step S7 that the simulation is not requested, the process proceeds to step S10, and if necessary, the multiple regression equation obtained in step S5 is output and the series of operations is terminated.

  Here, if it is determined in step S4 that the data existing in the database cannot create a multiple regression equation due to a lack of specific data, the process proceeds to step S11, and the missing data An item (at least one of factors relating to paint conditions and paint conditions) is extracted. The extraction of the missing data item may be the same as the determination in step S4, for example. In other words, the presence or absence of data within the range of conditions provided in the data input in steps S1 and S2 or data close to that range, and the essential factors among the paint conditions and coating conditions input in step S3 The data can be extracted based on the presence or absence of the data.

  If the deficient data item (factor) is extracted, the process proceeds to step S11 and the result is output. Thereafter, the process proceeds to step S21 shown in FIG. 4 in order to compensate for the missing data.

  FIG. 4 is a flowchart showing a procedure for supplementing data necessary for the multiple regression analysis. In order to make up for the missing data, a test panel was created by applying the paint with the newly formulated target paint under the specified paint conditions and paint conditions. Measure the characteristic value.

  First, a test panel is produced in step S21 shown in FIG. It is assumed that the newly designed paint is a top coating. In that case, a test panel is produced by, for example, applying a top coating material under predetermined coating conditions and coating conditions to a substrate on which undercoating and intermediate coating have been performed, and drying the coating film.

  Paints are usually pigments that are colorants, glitter pigments, resins and crosslinkers that are constituents of coatings, rheology control agents that are auxiliary components, pigment dispersants, antisettling agents, curing catalysts, antifoaming agents, It consists of various additives such as antioxidants and ultraviolet absorbers, extender pigments, and a solvent such as an organic solvent or water. When designing a paint, the constituent components and blending ratio of the paint are determined according to the required paint performance. In addition, in the operation conditions restricted in the actual operation, in order to fine-tune the visual characteristic values such as the texture of the coating film, the factors that can change the conditions are limited. For example, factors that have a large influence on the visual characteristic value include the amount of paint discharged, the number of bell rotations when using a bell-type coating machine as an automatic coating machine, and the shaping air pressure.

  The test panel is produced under a plurality of conditions by changing the conditions (levels) of some factors for each case, among the factors relating to the above-mentioned paint conditions and coating conditions, with respect to the paint having a predetermined composition. At that time, it is preferable to set a reference value for each factor to be changed, and to apply a coating by setting three or more levels with respect to the reference value to produce a test panel. However, the number of test panels to be manufactured increases remarkably if conditions of three levels or more are set for many factors. Therefore, for factors other than paint blending conditions, select factors that have a strong correlation with the visual characteristics that have been grasped in advance according to the visual characteristics such as color and texture as objective variables, as described above. It is preferable to efficiently create a multiple regression equation by changing the level of the factor. Regarding the blending conditions of the paint, it is preferable that the level of the factor to be changed is at least 3 levels.

  Next, in step S22, for each test panel obtained in step S21, visual characteristic values representing the color and texture of the coating film, which are objective variables in the multiple regression equation, are obtained by colorimetry. These visual characteristic values are as already described. However, as long as the visual characteristic value is a psychophysical quantity that can express a color or texture as a numerical value, other values can be used, and the visual characteristic value is not limited only to the above-described characteristic value.

  Next, proceeding to step S23, the paint blending conditions, the paint conditions and the coating conditions when the test panel was produced in step S21, and the measurement results of the coating film on the test panel obtained in step S22 will be described in the simulator and later. The data is stored in a multiple regression equation data storage unit provided in a painting control device or the like, and the missing data in the database is replenished. In addition, although the data regarding each factor and visual characteristics may store a numerical value as it is, it is preferable to preserve | save the paint conditions and the coating conditions in the form of ratio with respect to a reference value as needed. Note that the data to be stored is not necessarily limited to the data obtained from the test panel. Even if it is obtained from other than the test panel, such as data in actual operation, the data related to the blending conditions of the paint is reliable, the data of the visual characteristic value as the objective variable value, the factors related to the paint condition and the painting condition Can be used as data for multiple regression analysis.

  Since the data necessary for performing the multiple regression analysis is prepared by steps S21 to S23, the process returns to step S4 shown in FIG. 3, and the procedure after step S4 is executed.

  In the simulations in steps S8 and S9, based on the input factor data relating to the paint blending conditions, each paint condition, and the data relating to the paint conditions, the visual characteristic which is the objective variable value by the multiple regression equation. Calculate the value. Of course, the visual characteristic value is fixed, and the values of the factors relating to the paint condition and the painting condition corresponding to the characteristic value can also be calculated.

  FIG. 5 uses the multiple regression equation used in the painting method according to the embodiment to estimate the paint condition for obtaining the target visual characteristic value and the factor related to the paint condition for the paint newly designed. It is a flowchart which shows a procedure. Note that the multiple regression equation is obtained by the procedure shown in steps S1 to S12 and S21 to S23 described above, and the flowchart shown in FIG. 5 shows an example in the case of applying to an actual painting operation. Shall. An apparatus used for executing the following procedure is basically the automatic coating machine 20 shown in FIG. 2 and the above-described simulator or a coating control apparatus described later with reference to FIG.

  When a new paint blending design is performed, data on factors relating to the paint blending conditions are input in step S31. The factor data relating to the paint blending conditions is data corresponding to that described in relation to step S1 shown in FIG. Next, in step S32, the target value and / or range of the visual characteristic value related to the target paint is input. The target value or the range can be used because it may be possible to determine the range from the target value or the target value from the range. On the basis of the data relating to the input visual characteristic value, generally, the median value of the allowable range of the visual characteristic value is set as the visual characteristic value. However, a value close to the upper limit side or the lower limit side may be set as necessary.

Next, the process proceeds to step S33, and the factor _xn to be changed to obtain the target visual characteristic value is designated as the explanatory variable among the paint conditions and the factors related to the painting conditions. For example, when the set visual characteristic value as an objective variable is an FF value, and the most effective factor for controlling the FF value is empirically, experimentally or theoretically confirmed as the bell rotation speed Specify the number of bell rotations as a factor to change.

Next, in step S34, in order to obtain the value of the factor _xn to be changed, the target value of the visual characteristic value set based on the data input in step S32 and the data of factors other than the factor _{xn to be} changed Is used to calculate the explanatory variable f (x _n ) by the multiple regression equation, and further the value of the factor x _n is obtained. Although not shown in FIG. 5, the values of the factors related to the paint conditions and the coating conditions other than the factor _xn are set to fixed values. The fixed values of these factors mean values of factors that are predetermined in the painting operation, that is, values that are within the range that meets the constraints, and values that are within the limits of the set constraints. It can be selected appropriately. Further, data relating to these factors may be stored in advance in a simulator or the like, or may be input each time. After step S34, the process proceeds to step S35.

In step S35, it is determined whether or not the value of the factor _xn obtained in step S34 is within a range allowed as a constraint condition. If it is determined that the obtained factor _xn value exceeds the allowable range, the process proceeds to step S36, and the value of _xn is set to a value within the allowable range (for example, a value on the side exceeding the allowable range). Value). Next, it progresses to step S37, and after designating another factor to change, it returns to step S34 and repeats the procedure after step S34.

On the other hand, in step S35, the value of the factor obtained x _n is, when it is determined to be within the allowable range, by using the value of the factor x _n, visual characteristic values obtained in the actual operation, Since the target value or its range should be satisfied, the process proceeds to step S38, and all paint conditions and painting conditions are determined. The values of all the paint conditions and the painting conditions may be the values used for the calculation by the multiple regression equation. Next, the process proceeds to step S39, and the value determined in step S38 is fed forward to the painting operation. By using the conditions fed forward in step S39, the coating operation can be controlled and a coating film having a predetermined visual characteristic value can be obtained.

  In addition, the procedure demonstrated with reference to FIG. 5 is an example which shows that the coating method which concerns on this Embodiment can be implemented, If a painting operation can be controlled by using a multiple regression equation, The order of the steps may be different, specific steps may be omitted, and other steps may be included.

  The visual characteristic values include FF value, Munsell color system, L * a * b * color system, L * C * h color system, Hunter Lab color system, XYZ color system, etc. There is a value of When selecting factors related to paint conditions and painting conditions that satisfy the visual characteristic values for newly designed paints, obtain the optimum paint conditions and factors related to painting conditions for one visual characteristic value, and the result May be used. However, the influence of the factors relating to the paint conditions and the paint conditions on the respective visual characteristic values may be different. Therefore, using multiple regression equations for each visual characteristic value, determine the values of the factors related to the paint conditions and painting conditions that satisfy those visual characteristic values, and whether or not these visual characteristic values are satisfied. It is more preferable to check the above and select the most appropriate conditions.

  FIG. 5 shows an example in the case of controlling the painting operation, but the multiple regression equation is an equation representing the relationship between the visual characteristic value, the blending condition of the paint, the paint condition and / or the paint condition. It can also be used to monitor painting operations in actual operation. That is, when the visual characteristic value fluctuates, it is possible to estimate the factors affecting the visual characteristic value, such as fluctuations in paint blending conditions, paint conditions and / or painting conditions, and Useful for monitoring.

  FIG. 6 is a block diagram showing the configuration of the coating control apparatus according to the embodiment of the present invention. An example of the coating control apparatus 30 shown below includes a function as a simulator for creating a multiple regression equation described with reference to FIGS. 3 and 4 and a function for performing the coating method described with reference to FIG. 5. It is. The painting control device 30 includes a multiple regression equation data storage unit 31, an actual operation data storage unit 32, a calculation / control unit 33, an input unit 34, and an output unit 35. Further, the multiple regression equation data storage unit 31 and the calculation / control unit 33 and the actual operation data storage unit 32 and the calculation / control unit 33 are connected so as to be able to transmit and receive signals, and the calculation / control unit 33. And the input unit 34 and the output unit 35 are connected to be able to transmit and receive signals. Further, the multiple regression equation data storage unit 31 is provided with a multiple regression analysis data storage unit 31a and a multiple regression equation storage unit 31b, and the actual operation data storage unit 32 includes an operation data storage unit 32a and constraint conditions. A storage unit 32b is provided. The actual operation data storage unit 32 is provided as necessary, and for example, the necessary data may be stored in the multiple regression analysis data storage unit 31.

  Data on paint blending conditions and visual characteristic values for creating multiple regression equations, data on paint conditions, factors related to painting conditions, data on visual characteristic values generated during actual operation, paint conditions, factors relating to painting conditions The data regarding is stored in the corresponding storage units via the input unit 34 and the calculation / control unit 33. The multiple regression analysis data storage unit 31a mainly stores test results from the test panel, and the operation data storage unit 32a stores the visual characteristic values, paint conditions, and painting conditions obtained in actual operation. The actual measurement values of the factor data are stored, and at least the allowable range of the visual characteristic value and the target value, the coating condition, and the coating condition allowable range set for each paint having a predetermined composition are stored in the constraint condition storage unit 32b. And the target value is stored. The multiple regression analysis data storage unit 31a and the operation data storage unit 32a may be integrated without being separated. Further, each data may be stored for each paint having a predetermined composition.

  When creating a multiple regression equation, the calculation / control unit 33 uses the data stored in the multiple regression analysis data storage unit 31a according to the procedure described with reference to FIGS. An equation is created, and the obtained multiple regression equation is stored in the multiple regression equation storage unit 31b.

  The control of the painting operation in the actual operation related to the newly blended paint described with reference to FIG. 5 is the data stored in the operation data storage unit 32a and the constraint condition storage unit 32b of the actual operation data storage unit 32. Is executed by the arithmetic / control unit 33. The value of each factor that can be controlled to a predetermined visual characteristic value calculated by the calculation of the calculation / control unit 33 is output to the output unit 35 and, if necessary, directly from the control unit 25 of the automatic coating machine 20. It is transmitted to the input / output means 27 (see FIG. 2) and used for controlling the automatic coating machine 20.

  In the case of the coating control apparatus 30 according to the above-described embodiment, an example including the data storage unit 31a for multiple regression analysis, that is, an example having a function as a simulator is shown. However, in another embodiment, The data storage unit 31a for regression analysis may be omitted and the function as a simulator may not be provided. In that case, a multiple regression equation is created using another simulator, and the obtained multiple regression equation is configured to be stored in the multiple regression equation storage unit 51b.

  The above functions included in the painting control apparatus 30 shown in FIG. 6 can be realized by using a normal personal computer or the like.

  The painting facility according to the present embodiment is a facility whose basic overall configuration including the automatic painting machine 20 is shown in FIG. The painting facility 10 is an automatic painting facility 10 that performs painting while moving a plurality of objects 11 in a painting booth in which temperature and humidity are not controlled, or in a painting booth in which temperature or temperature and humidity are controlled. Usually, the conveyor part which conveys the to-be-coated object 11 at a fixed speed, the automatic coating machine 13 to spray paint on the to-be-coated object 11, and the automatic coating machine 13 are moved to an appropriate position with respect to the moving to-be-coated object 11. A reciprocator or robot and an automatic coating machine control device 26 for controlling the painting operation are provided. Further, one example of the automatic painting machine 13 included in the painting facility 10 is the bell type painting machine 20 shown in FIG. 2, and one example of the painting control apparatus has the configuration shown in FIG. Further, the painting operation control described with reference to FIG. 5 is executed by the painting control device 30. The painting facility 10 is basically intended for commercial-scale facilities, but may be configured as a small-scale facility for testing and research composed of an automatic coating machine 13 and a reciprocator. Good.

  In Example 1, the control accuracy of the visual characteristic value in the coating method using the multiple regression equation was confirmed on the premise that the blending condition of the metallic top coating was changed. Specifically, as an explanatory variable, create a multiple regression equation that includes factors related to the blending conditions of the metallic paint, and use the obtained multiple regression equation to determine the coating conditions that can achieve the target visual characteristic value. Select and estimate the visual characteristic value by the multiple regression equation using the selected condition, make a test panel painted under the selected condition, measure the visual characteristic value, The control accuracy was confirmed by comparing the visual characteristic values.

  First, a steel plate (material: JISG3141, size: length and width 400 mm x 300 mm, thickness 0.8 mm) subjected to degreasing and zinc phosphate treatment, cationic electrodeposition paint: trade name "ELECRON 9400HB" (Kansai Paint Co., Ltd.) Made of an epoxy resin, a polyamine cationic resin, and a coating containing a block polyisocyanate compound as a curing agent) are electrodeposited so that the coating thickness after curing is 20 μm, and heated at 170 ° C. for 20 minutes for crosslinking. An electrodeposition coating film was formed by curing.

  Furthermore, on the surface of the electrodeposition coating, an intermediate coating: the trade name “Lugabake Intermediate Coating Gray” (manufactured by Kansai Paint Co., Ltd., a coating containing a polyester / melamine resin and an organic solvent) has a coating thickness after curing. An intermediate coating film was formed by coating with air spray so as to have a thickness of 30 μm, followed by crosslinking and curing by heating at 140 ° C. for 30 minutes. By the above procedure, a steel plate having an electrodeposition coating film and an intermediate coating film formed on the surface was prepared and used as a substrate.

Table 1 summarizes the blending conditions of the top coating material applied to the substrate, the bell rotation number when applied using a bell-type coating machine, and the measurement results of the FF value of the obtained coating film. When preparing the paint, blend the hydroxyl group-containing acrylic resin, methylated melamine resin, and luster pigment in this order, stir and mix thoroughly, and then dilute to an appropriate viscosity for coating to obtain a solid content of about It was set as the water-based paint containing 25 mass%. As the paint, the blending ratio of each of the resins A, B, and C was set to 4 levels, the blending ratio of each of the luster pigments D and E was set to 3 levels, and 17 types of top coat paints were prepared by combining these blending ratios. In addition, the structure of resin A, B, C and the luster pigments D and E is as follows.
Resin (ratio by weight):
A hydroxyl group-containing acrylic resin / methylated melamine resin (solid content: 80% by mass): 8/2
B Hydroxyl group-containing acrylic resin / methylated melamine resin (solid content: 90% by mass): 8/2
C hydroxyl group-containing acrylic resin / methylated melamine resin (solid content: 100% by mass): 8/2
Bright pigment:
D scale-like aluminum flake pigment (solid content 65% by mass, average particle size 14.1 μm)
E scale-like aluminum flake pigment (solid content 70% by mass, average particle size 19.4 μm)
The hydroxyl group-containing acrylic resin has a solid content of 55% by mass, an acid value of 50, and a number average molecular weight of 50000.

  Next, the prepared water solvent type paint was applied to the substrate using a bell type coater. In the painting, the painting was performed under the condition that the bell rotation speed was set at 3 levels among the factors relating to the painting conditions. All other paint conditions and factors related to painting conditions were fixed. The coated substrate was heated at a temperature of 140 ° C. for 30 minutes to cure the coating film, thereby preparing 17 test panels having the conditions shown in Table 1.

About the obtained test panel, FF value which is a value showing a glitter feeling was measured as a visual characteristic value showing the color and texture of a coating film. For the measurement of the FF value, a metallic feeling measuring instrument, ALCOPE (trade name, manufactured by Kansai Paint Co., Ltd.) was used. ALCOPE is a laser-type metallic sensation measuring device that irradiates a near-infrared laser (wavelength 780 nm) sensitive to metal from an angle of 45 degrees with respect to the measurement surface and an angle of 45 degrees with respect to specular reflection light. This is a device having a function of detecting reflectance IV when receiving light and reflectance IV when receiving light at an angle of 10 degrees. The FF value was calculated from the following equation (1). The FF values are shown in Table 1.
FF value = 0.2 × (IV−SV) / (IV + SV) (1)

  Next, multiple regression analysis was performed using the blending ratios of the resins A, B, C, and the luster pigments D, E, and the bell rotation number as explanatory variables, and the measured FF values as objective variables. In the case of the coating method according to the present invention, in the multiple regression equation related to the FF value, the value obtained by squaring the bell rotation speed is used as an explanatory variable, thereby improving the multiple correlation coefficient and the explanation rate of the multiple regression equation. Since it has been confirmed by the present inventors that there is a case where it can be obtained, the bell rotation number was subjected to multiple regression analysis not only for the first power but also for the squared value. Also, for multiple regression analysis, the bell rotation speed is in the form of the ratio of the actual value (displayed with "actual") to the reference value (displayed with "reference") at 25,000 rpm. used.

As a result of the multiple regression analysis under the above conditions, the following equation (2) was obtained.
FF value = −0.20 × (resin A blending ratio / 100) + 0.08 × (resin B blending ratio / 100) −0.41 × (brilliant pigment D blending ratio / 20) + 0.225 × (actual bell) Rotation speed / reference bell rotation speed) +1.88 (2)
The multiple regression equation shown as the equation (2) does not include terms relating to the resin C and the luster pigment E. The reason is that the compounding of the resin was set to A + B + C = 100, and the compounding of the luster pigment was set to a constant value of D + C = 20. Further, regarding the bell rotation speed, in the case of the above condition, there was no clear difference between the case where the influence on the FF value is the first power and the second power, so the first power, that is, the first-order form is selected.

  Next, a test for confirming the accuracy of the equation (2) was performed. Under the conditions shown in Table 2, six test panels were produced. The method for producing the test panel is the same as the method for producing the test panel in order to obtain the above multiple regression equation. While measuring the FF value of the obtained test panel, the FF value was calculated by equation (2).

  Table 2 summarizes the blending ratio of each of the resin and the luster pigment, the bell rotation number, the actual measurement value and the calculated value (estimated value) of the FF value.

  As is clear from Table 2, the difference between the measured value and the calculated value of the FF value is extremely small, and the FF value can be estimated with high accuracy by the equation (2), and the blending conditions of the paint were changed. Even in this case, it was confirmed that the visual characteristic value can be controlled with high accuracy.

In Example 2, the control accuracy of the visual characteristic value in the coating method using the multiple regression equation was confirmed on the premise that the blending condition of the top coating material containing the color pigment was changed. Table 3 summarizes the blending ratio of resins A, B, and C and the blending ratios of color pigments F and G with respect to 19 types of prepared paints. As paints, 19 types of topcoat paints were prepared by combining the blending ratios of resins A, B, and C with 4 levels and blending ratios of color pigments F and G with 3 levels, respectively, and combining these blending ratios. Resins A, B, and C are the same as those used in Example 1. The color pigments F and G are as follows.
F: Shigetopyrrolopyrrole pigment (PR255)
G: Dimethylquinacridone pigment (PR209)
The test panel was prepared by changing the composition of the top coating as described above, and for some test panels, changing the shaping air pressure (SA pressure), and applying the color measurement method as follows. Except for the differences, the second embodiment is the same as the first embodiment, and a duplicate description is omitted. The number of bell rotation points and the shaping air pressure when the test panel was produced are as shown in Table 3. For color measurement, a colorimeter “SM color computer” (trade name, manufactured by Suga Test Instruments Co., Ltd.) was used, and measurement was performed under the conditions of visual field: 10 degrees, illumination: D65. The color value Δa in the L * a * b color system was calculated using 1 as a reference plate. The results are shown in Table 3.

  Next, a multiple regression analysis was performed using the blending ratios of the resins A, B, and C and the coloring pigments F and G, the bell rotation speed and the shaping air pressure as explanatory variables, and the color value Δa as an objective variable. In the case of the coating method according to the present invention, in the multiple regression equation related to the color value Δa, by using the values obtained by squaring the bell rotation speed and the shaping air pressure as the explanatory variables, the multiple correlation coefficient of the multiple regression equation, Since it has been confirmed by the present inventors that the explanation rate may be improved, multiple regression analysis is also performed for the bell rotation speed and the shaping air pressure for the squared value as well as the first power. went.

For the multiple regression analysis, the bell rotation speed and the shaping air pressure were used in the form of the ratio of the actual value (displayed with “real”) to the reference value (displayed with “reference”). The reference values were a bell rotation speed: 25000 rpm and a shaping air pressure: 1.96 × 10 ⁵ Pa.

As a result of the multiple regression analysis under the above conditions, the following equation (3) was obtained.
Color value Δa = 0.11 × (resin A blending ratio / 100) −0.440 × (resin B blending ratio / 100) + 1.90 × (pigment F blending ratio / 10) + 2.13 × (actual bell rotation speed) / standard bell rotational ^speed) 2 + 1.50 × (actual SA pressure / reference SA ^pressure) 2 -4.50 (3)
The multiple regression equation shown as the equation (3) does not include terms relating to the resin C and the color pigment G. The reason is that the formulation of the resin _{R A + R B + R C} = 100 ( provided _that, R A to R _C: blending ratio of the resin A through C), the formulation of the colored pigment is _R F _{+ R} G = 10 (however, _{R G} , R _F : blending ratio of the color pigments G and F) and a constant value. Regarding the bell rotation speed and the shaping air pressure, in the case of the above-described multiple regression analysis conditions, the influence on the color value Δa was stronger in the case of the square than the case of the first, so the square, that is, the quadratic form. Term.

  Next, a test for confirming the accuracy of the expression (3) was performed. Six test panels were manufactured under the conditions shown in Table 4. The method for producing the test panel is the same as the method for producing the test panel in order to obtain the above multiple regression equation. The color value Δa of the obtained test panel was measured, and the color value Δa was calculated by the equation (3).

  Table 4 summarizes the blending ratio of each of the resin and the color pigment, the bell rotation speed, the shaping air pressure, the actually measured value and the calculated value (estimated value) of the color value Δa.

  As is clear from Table 4, the blending ratios of resins A, B, and C are 0 to 50% by mass, 35 to 70% by mass, and 0 to 35% by mass, respectively, with respect to 100 parts by mass of the solid content of the resin. Even when the blending ratio of the pigments F and G is significantly changed to 1.75 to 6.5% by mass and 3.5 to 8.25% by mass with respect to 100 parts by mass of the solid content of the resin, Δa It was confirmed that the absolute value of the difference between the calculated value and the measured value was as extremely small as 0.01 to 0.17. That is, even when the blending ratio of the resin such as A, B, and C and the color pigment such as F and G is significantly changed, the target color value Δa is set and the appropriate value can be obtained by using the multiple regression equation. It was confirmed that the visual characteristic values such as the color value Δa obtained in actual operation can be controlled with high accuracy by selecting the coating conditions such as the bell rotation speed and the shaping air pressure.

  The painting method according to the present invention can be carried out by using the painting equipment and the painting control device according to the present invention. For example, when a paint used for painting on industrial products such as an automobile body is newly blended and designed. In addition, it is possible to easily obtain appropriate conditions for painting operation. Also, by operating under the conditions, visual characteristic values such as the color and texture of the coating film can be controlled and maintained with high accuracy.

It is a schematic plan view which shows the structure of the principal part of the coating equipment generally used. It is a figure which shows typically one example of the cross-section of the principal part of a bell type coating machine, and its control system. It is a flowchart which shows the procedure which produces the multiple regression equation used with the coating method which concerns on embodiment. It is a flowchart which shows the procedure for supplementing the data required for multiple regression analysis. Using the multiple regression equation used in the painting method according to the embodiment, the paint condition that can obtain the visual characteristic value of the target paint color and the factors related to the paint condition are estimated for the newly designed paint. It is a flowchart which shows the procedure to perform. It is a block diagram which shows the structure of the coating control apparatus which concerns on embodiment of this invention.

Explanation of symbols

DESCRIPTION OF SYMBOLS 10 Coating equipment 11 Coating object 12 Coating booth 13 Automatic coating machine 20 Bell type coating machine 21 Bell type coating machine coating gun 25 Control system 26 Automatic coating machine control device 30 Coating machine control device 31 Data storage unit 32 for multiple regression equation Data storage unit for actual operation 33 Calculation / control unit

Claims (5)

  In the painting method by spraying paint onto the object to be coated in the paint booth using an automatic painting machine arranged in the painting booth, the object to be coated is coated with the newly designed paint. In this case, the visual characteristics of the paint color including the color and texture relating to the coating film of the paint newly designed and blended are set as objective variables, the factors relating to the paint blending conditions, and at least one paint condition and / or paint By using the multiple regression equation obtained by performing multiple regression analysis using the data stored in the database, with the factors related to the conditions as explanatory variables, the objective variable and the explanatory variables in the painting work are A painting method characterized by calculating a relationship and controlling and / or monitoring a painting operation based on the result.   When performing the multiple regression analysis, it is determined whether multiple regression analysis is possible based on the data stored in the database, and if there is insufficient data, the newly formulated paint is added. The coating method according to claim 1, wherein a test panel is prepared, and a multiple regression analysis is performed by supplementing missing data.   The factor related to the blending condition includes at least one of the blending ratio of the resin component of the paint, the blending ratio of the colorant, and the blending ratio of the glitter pigment, and the factor related to the paint condition is the viscosity of the paint Including at least one of a blending ratio of a solid content and a blending ratio of a solvent for dilution, and the factors relating to the coating conditions are the discharge amount of the paint, the temperature of the coating atmosphere, the humidity of the coating atmosphere, and the wind speed of the coating atmosphere The moving speed of the automatic coating machine, the moving speed of the object to be coated, the distance between the coating gun and the object to be coated, the applied voltage, the rotation speed of the bell cup, the atomizing air pressure, the atomizing air flow rate, the shaping air Pressure, shaping air temperature, shaping air humidity, and shaping air flow rate, and the visual characteristics of the paint color are Munsell color system chromaticity, L * a * b * color system color Degree, L * C h color system chromaticity, Hunter Lab color system chromaticity, XYZ color system chromaticity, spectral reflectance, IV value, SV value, and flip-flop value. The coating method according to claim 1 or 2.   A coating control apparatus used for controlling the coating method according to any one of claims 1 to 3, wherein a data storage unit for a multiple regression equation serving as a database, a calculation / control unit, an input unit, and For paints that have an output section and are newly designed and designed, the visual characteristics of the paint color, including the color and texture of the paint film, are used as objective variables, the factors relating to the paint composition conditions, and at least one paint condition By using the multiple regression equation obtained by performing multiple regression analysis using the data stored in the data storage unit for multiple regression equation, with the factors relating to the coating conditions as explanatory variables, and painting, A painting control apparatus comprising a function of calculating a relationship between the objective variable and the explanatory variable in a work, and controlling and / or monitoring a painting operation based on the result.   An automatic painting facility for performing painting while moving a plurality of objects in a painting booth, comprising the painting control device according to claim 4 and using a multiple regression equation stored in the painting control device Calculating the relationship between the objective variable value and the explanatory variable value, the visual characteristic value of the coating color related to the objective variable value, the paint condition and / or the factor related to the coating condition related to the explanatory variable value, and Is configured to calculate the value of the factor relating to the paint condition and / or the paint condition so that the value falls within the allowable range, and to control and / or monitor the paint operation based on the result. Painting equipment.

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