JP2006218425A - 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 line speed or the like of a coating line 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. The visual characteristics including the color and quality feeling of the applied coating film are set to a target variable, and a coating condition and the factors related to the coating condition are set to an explanation variable with respect to predetermined compounded coating while multiple regression formula forming data is used to form a multiple regression formula. The relation between the target variable value and the explanation variable value in coating work is operated using the 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, and a building material, a coating control apparatus, and a coating facility. More specifically, the paint condition and the coating condition are controlled to control the coating color such as color and texture. The present invention relates to a coating method, a coating control device, and a coating facility capable of obtaining a coating film having stable visual characteristics.

  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 ratio of the solvent contained in the paint, the blending ratio of the solid content, the viscosity, etc. The paint conditions include the temperature, humidity and wind speed of the paint atmosphere in the case of the bell type coater described above. , Coating machine moving speed, coating object moving speed, distance between coating gun and coating object, applied voltage, paint discharge amount, bell cup rotation speed of bell type coating machine, shaping air temperature, shaping air humidity, Shaping air pressure, shaping air flow rate, etc. are included.

  As described above, the visual characteristics of the coating color such as the color and texture of the coating film are affected by various factors. 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 production lines for industrial products including painting lines, it is often necessary to adjust the production volume. In such a case, the line speed is also changed in the painting line. When the line speed changes, the coating film thickness changes accordingly. Therefore, in order to secure a predetermined film thickness, it is necessary to change the paint conditions and the coating conditions. When such a situation occurs, the amount of paint discharged is usually adjusted. In general, when the amount of paint discharged is adjusted, the target color, texture, and glitter of the coating film cannot be obtained unless other coating conditions or paint conditions are changed.

  In such a case, for example, it is necessary to change the coating conditions such as the bell cup rotation number in addition to the discharge amount so as to obtain a target brightness. Such a change in the coating conditions is not uniquely required, and the fact is that the knowledge, experience, and intuition of paint / painting engineers must be relied upon. In order to immediately cope with such a change in conditions, a high level of ability based on a wealth of knowledge and experience is required, so only a small number of engineers can respond. Therefore, in the case where there is no such engineer, not only can not be dealt with immediately, but even if it can be dealt with, the optimum operating condition may not be selected.

  In addition, the type of paint (especially resin composition, solvent composition, etc.) may be significantly changed for the purpose of improving the finished appearance of the coating film and improving the performance of the coating film. Even experienced paint engineers may not be able to deal with it. When such a situation occurs, it is not possible to select the most suitable paint conditions and coating conditions, which may not only lead to an increase in work man-hours and manufacturing costs and the occurrence of defective products, but in extreme cases, There is a possibility that the painting line must be stopped because the target color and texture cannot be obtained. 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 to express all factors 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. Then, a multiple regression equation with the film thickness as an objective variable is created, and a coating simulation is performed using the multiple regression equation to calculate and estimate the film thickness. 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-described problems, and stably maintains the visual characteristics such as the color and texture of the coating film even when the line speed of the coating line is changed. An object of the present invention is to provide a painting method, a painting control device, and a painting equipment that can be applied.

  A painting method (1) according to the present invention is 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, and having a predetermined composition. Using the data for creating multiple regression equations for each of the paints, with the visual characteristics of the paint color including the color and texture of the paint film applied as the objective variable and the paint conditions and the factors related to the paint conditions as explanatory variables By using the multiple regression equation obtained by performing multiple regression analysis, the relationship between the objective variable value and the explanatory variable value in the painting operation is calculated, and the painting operation is controlled and / or monitored based on the result. It is characterized by that.

  Further, in the coating method (2) according to the present invention, in the coating method (1), the factor relating to the paint condition is at least one of the viscosity of the paint, the blending ratio of the solid content, and the blending ratio of the dilution solvent. Including one, 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, the wind speed of the coating atmosphere, the moving speed of the automatic coating machine, the moving speed of the object to be coated, At least one of a distance between the coating gun and the object to be coated, applied voltage, bell cup rotation speed, atomizing air pressure, atomizing air flow rate, shaping air pressure, shaping air temperature, shaping air humidity, and shaping air flow rate. The visual characteristics of the paint color include Munsell color system chromaticity, L * a * b * color system chromaticity, L * C * h color system chromaticity, Hunter Lab table Color system chromaticity, XYZ color system color , Spectral reflectance, is characterized in that it comprises at least one of the IV value, SV value and the flip-flop value.

  A painting control apparatus (1) according to the present invention is a painting control apparatus used for controlling the painting method (1) or (2), and includes a multiple regression equation storage unit, a calculation / control unit, an input unit, and an output unit. A function for obtaining the explanatory variable value corresponding to the objective variable value and / or the description using a multiple regression equation stored in the multiple regression equation storage unit for each paint having a predetermined composition It has a function of obtaining the objective variable value based on the variable value.

  Moreover, the coating control apparatus (2) according to the present invention further includes a data storage unit for creating a multiple regression equation in the coating control apparatus (1), and is input for each of the paints having a predetermined composition. It has a function of creating a multiple regression equation using the visual characteristic value of the paint color as an objective variable value and data relating to the paint condition and the factors relating to the paint condition as explanatory variable values.

  A painting facility according to the present invention is an automatic painting facility that performs painting while moving a plurality of objects to be coated, and includes the painting control device (1) or (2) 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, the visual characteristic value of the coating color related to the objective variable value, the paint condition and / or the coating related to the explanatory variable value The value of the factor related to the paint condition and / or the coating condition is calculated so that the value of the factor related to the condition falls within an allowable range, and the painting operation is controlled and / or monitored based on the result. It is characterized by being composed.

  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 coating method (1), by using the multiple regression equation, the visual characteristic value of the coating color is maintained at a predetermined value even when the operating condition such as the line speed is changed in the coating line. Appropriate paint conditions and / or coating conditions can be determined. 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 respond immediately and reliably to changes in operating conditions without relying on some highly skilled painting engineers as in the past, and constantly monitor the operating state of painting. can do.

  In addition, according to the above-mentioned painting method (2), since multiple regression analysis is performed using factors related to many paint conditions and 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 (1), since it has a function capable of implementing either the coating method (1) or (2), it can be applied by any of the coating methods (1) to (4). The same effect as that obtained can be obtained.

  Moreover, according to the said coating control apparatus (2), since the function which produces a multiple regression equation is provided further, it is more practical.

  According to the coating facility, the coating control device (1) or (2) is provided and is configured to be able to perform either the coating method (1) or (2). An effect similar to the effect obtained by any one of (2) 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, for each paint of a predetermined composition, one of the visual characteristics including the color and texture of the painted film is an objective variable, and the factors related to the paint condition and the paint condition As an explanatory variable, a multiple regression equation is created in advance using the data for creating the multiple regression equation, and by using this multiple regression equation, the relationship between the objective variable and the explanatory variable in the painting operation, that is, the paint condition and the painting condition It is intended to calculate the relationship between the factor value and the visual characteristic value, and to control and / or monitor the painting operation based on the calculation result. That is, the coating method according to the embodiment can be obtained by promptly and accurately obtaining appropriate coating conditions and coating conditions according to changes in visual characteristic values in normal operation and reflecting them in the coating operation. It plays the role of controlling and monitoring the visual characteristic values.

  In the case of the multiple regression equation used in the painting method according to the embodiment, in order to control the visual characteristic value to a predetermined value or range according to changes in the painting conditions, etc. Appropriate conditions for at least one of the factors must be selected. Therefore, the multiple regression equation is an equation that includes at least one paint condition and / or a factor related to the coating condition that can control the visual characteristic value.

  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 the coating conditions include, for example, when a bell-type coating machine is used as an automatic coating machine, the amount of paint discharged, the temperature of the painting atmosphere, the humidity of the painting atmosphere, the wind speed of the painting atmosphere, the automatic painting machine Moving speed, moving speed of the object to be coated, distance between the coating gun and the object to be coated, applied voltage, bell cup rotation speed (hereinafter abbreviated as bell rotation speed), shaping air pressure, shaping air temperature, shaping Air humidity and shaping air flow rate are included. In addition, when an air atomizing type coating machine is used as the automatic coating machine, the atomizing air pressure and the atomizing air flow rate are included in the coating conditions instead of the bell rotation speed of the bell type coating gun.

  The objective variable Y is a visual characteristic. As described above, the visual characteristics of the paint color include 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.

  Hereinafter, the coating method according to the embodiment will be described more specifically with reference to the drawings. FIG. 1 is a schematic plan view showing a configuration of a main part of a generally used painting facility 10. 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 is provided with a bell type painting gun which is a rotary atomizer, and paints are applied to the article 11 from the bell type painting gun. 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 illustrating an example of a cross-sectional structure of a main part of a bell type coating machine 20 which is one of automatic coating machines and a control system thereof. 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 onto the article 11 to be coated. . The control system 25 includes an automatic coating machine control device 26, a shaping air regulator (pressure and flow rate regulator) 26a, a rotation speed regulator 26b of the bell cup 23, a paint supply amount regulator 26c, and an automatic coating machine controller. The input / output means 27 connected to 26 is provided.

The painting method according to the embodiment is a painting method using the painting equipment 10 and the automatic painting machine 13 (bell type painting machine 20) 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 the multiple regression equation is represented 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 conditions and the painting conditions already described, and all the factors are included in the multiple regression analysis. However, some factors that are strongly correlated with the objective variable have been clarified, and other factors with weak correlation need not be used, and can be changed from the viewpoint of the stability of the painting operation. 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 x _n used in the multiple regression analysis is a function of x _n and is basically represented by f (x _n ). Specifically, as the explanatory variable, the value of each factor is used as it is, square, cube, square root, reciprocal, logarithm, and the like. Since the optimum function shape can be made independent between the factors, it is preferable to select the optimum function shape theoretically, empirically, or experimentally for each factor.

When creating a multiple regression equation, basically, a multiple regression analysis is performed using all the factors relating to the 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 one form of the coating method according to the embodiment, when a paint film coated with a paint having a predetermined composition is used as an object and a characteristic value (objective variable value) of the paint film is expressed by an FF value, many paints are used. Among the factors relating to the conditions and the coating conditions, the influence of the paint discharge amount, the shaping air pressure and the bell rotation speed is strong. By using these three factors, the multiple correlation coefficient (R) and the explanation rate (R ² ) High multiple regression equation can be created. Therefore, in the case of the embodiment described later, when the objective variable value is the FF value, the values of the factors of the paint discharge amount, the shaping air pressure, and the bell rotation speed are mainly set as the explanatory variable values within a predetermined range. An example will be described in which multiple regression analysis is performed on the data changed in step 1 and other factors set to constant values.

  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. Therefore, it is preferable to select a factor that changes the value in each case as an explanatory variable. 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 painting method according to the embodiment and obtaining a visual characteristic value of the paint color based on the obtained multiple regression equation. The multiple regression equation is created according to the procedure of Step S1 to Step S3 shown in FIG. In step S1, a test panel is produced. The test panel is prepared by applying a top coating material having a predetermined composition to a base material subjected to, for example, undercoating and intermediate coating under predetermined coating conditions and coating conditions, and drying the coating film.

  The paint is usually a color pigment or glitter pigment as a colorant, a resin or a crosslinking material as a coating film component, a rheology control agent as an auxiliary component, a pigment dispersant, an anti-settling agent, a curing catalyst, an antifoaming agent, 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. There are limited factors that can change the paint conditions in order to fine-tune the visual characteristics such as texture under certain operating conditions. Additives such as mixing ratio of dilution solvent, rheology control agent, etc. There are factors related to the viscosity of the paint and the blending ratio of the solid content such as the blending ratio of

  In addition, there are many factors related to the coating conditions as described above. For example, the factors that have a large influence on the FF value are the amount of paint discharged, the case of using a bell type coating machine as an automatic coating machine. There are bell rotation speed and 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, as described above, depending on each visual characteristic such as color and texture as the objective variable, select a factor that has a strong correlation with the visual characteristic that is grasped in advance, and change the level of that factor Thus, it is preferable to efficiently create a multiple regression equation.

  Next, in step S2, for each test panel obtained in step S1, a visual characteristic value that is an objective variable in the multiple regression analysis is 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 the color and texture as numerical values, other values can be used, and the visual characteristic value is not limited to the above-described characteristic value examples.

  The paint conditions and coating conditions when the test panel is produced in step S1 and the measurement results of the coating film of the test panel obtained in step S2 are stored in a data storage unit provided in a simulator, a coating control device described later, or the like. It is preferable to store it as a database for creating multiple regression equations. Data relating to each factor and visual characteristics may be stored as numerical values, but the paint conditions and paint conditions are preferably stored in the form of a ratio to the reference value. Note that the data to be stored is not necessarily limited to the data obtained from the test panel. Even if the data is obtained from other than the test panel, the paint is in the prescribed composition, and the data of the visual characteristic value as the objective variable value, the data of the paint conditions and the factors related to the paint conditions are available Can be used as data for multiple regression analysis. The simulator referred to in this specification has a function of calculating a visual characteristic value that is an objective variable value by a multiple regression equation based on factor data relating to each input explanatory variable, and displaying the calculation result. This means an arithmetic device having the same.

  Next, in step S3, a multiple regression equation is obtained by performing multiple regression analysis. Specifically, the multiple regression analysis is performed using two or more factors selected from the paint conditions and the painting conditions as explanatory variables and one of visual characteristics representing color or texture as an objective variable. Since the basic form of the multiple regression equation and the multiple regression analysis method have already been described, redundant description will be omitted. For the multiple regression analysis, general-purpose software can be used. For example, Lotus 1-2-3 (registered trademark) manufactured by Lotus, Microsoft Excel series manufactured by Microsoft, and Japan Science and Technology, which is dedicated software for statistical calculation. JUSE-QCAS (registered trademark), etc. made by a training company can be used.

  In Steps S4 to S6, the estimation accuracy is confirmed for the multiple regression equations obtained in Steps S1 to S3. That is, it is a step of estimating visual characteristic values representing the color and texture of the coating film obtained by painting based on the paint conditions and the data of each factor relating to the painting conditions.

  In step S4, the multiple regression equation obtained in step S3 is stored in a storage unit such as a simulator or a coating control apparatus described later. This simulator may be the same as the device used in steps S1 to S3.

  In step S5, data on factors relating to the paint conditions and the paint conditions are input to the simulator. Specifically, in order to estimate a visual characteristic value obtained by painting, paint conditions for performing a simulation and data on factors relating to the painting conditions are input. As the input data, the value of each factor included in the multiple regression equation such as the ratio to the reference value is input as it is as the numerical value of each factor. The input device can be any device as long as it can input data to the simulator, such as a keyboard and a touch panel.

  In step S6, a visual characteristic value is calculated using a multiple regression equation on the basis of the input paint condition and the factor data relating to the paint condition in the simulator.

  In step S7, the visual characteristic value calculated in step S6 is displayed. When a computer in which the above-mentioned spreadsheet software is installed is used as the simulator, the factor related to the explanatory variable included in the multiple regression equation (usually the level in the multiple regression analysis in steps S1 to S3) When the data of the changed factor) is input, the computer automatically calculates the visual characteristic value, which is the objective variable, using the multiple regression equation (the multiple regression equation obtained in steps S1 to S3). The result is displayed.

  4A and 4B are flowcharts showing a procedure for estimating a paint condition for obtaining a target visual characteristic value and a factor related to the paint condition using a multiple regression equation used in the paint method according to the embodiment. Note that the multiple regression equation is obtained for each paint having a predetermined composition in the procedure corresponding to steps S1 to S3 above, and the flowcharts shown in FIGS. 4A and 4B are examples of cases that occur in actual painting operations. Assuming one example of The apparatus used to execute the following procedure is basically the apparatus shown in FIGS. 1 and 2 and the simulator described with reference to FIG.

  In a normal daily painting operation, the visual characteristic value of the paint color is appropriately measured, and it is monitored whether the color, texture, etc. satisfy a predetermined condition. If there is no abnormality in the paint condition and the paint condition, the visual characteristic value should not change greatly, but may change gradually. On the other hand, for reasons such as production adjustment, the painting conditions must be changed. Such painting operations are monitored, and measures are taken as necessary.

  In step S11 shown in FIG. 4A, it is determined whether or not there is a request for changing the operation condition of the painting line such as production amount adjustment. If it is determined that there is no such request, the process proceeds to step S12, and a visual characteristic value such as an FF value is measured. Next, the process proceeds to step S13, and it is determined whether or not the measurement result of the visual characteristic value is within an allowable range. If it is determined that the measurement result is within the allowable range, the process returns to step S11 to continue monitoring. On the other hand, if it is determined in step S13 that the measurement result exceeds the allowable range, the process proceeds to step S15 (FIG. 4B).

  If it is determined in step S11 that there has been a request to change the operating condition of the painting line, the process proceeds to step S14, and the factors relating to the specific explanatory variables that can cope with the change of the operating condition of the painting line, that is, the paint condition and the painting Among the factors related to the conditions, the target value of the corresponding factor is set. This factor is, for example, the moving speed of the object to be coated when it is necessary to increase the production speed. Thereafter, the process proceeds to step S15 (FIG. 4B).

In step S15 shown in FIG. 4B, the target value of the objective variable, that is, the target value of the visual characteristic value is set. Normally, it is set to approximately the median of the allowable range of visual characteristic values. This value is the most preferable value selected from the visual characteristic values obtained as actual results in the past for each paint having a predetermined composition. 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 S16, and among the factors relating to the paint conditions and the painting conditions, a factor _xn to be changed to obtain a target visual characteristic value is designated. For example, in the case where the moving speed of the object to be coated is set to be high in step S14, for example, a paint discharge amount is designated as a factor to be changed in order to ensure the thickness of the coating film.

In step S17, using the data of factors other than the target value of the visual characteristic value set in step S15 and the factor _{xn to be} changed, the explanatory variable f (x _n ) is calculated, and the value of the factor _xn is obtained. Although not shown in FIG. 4B, 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 regarding these factors may be stored in the simulator in advance, or may be input each time. After step S17, the process proceeds to step S18.

In step S18, it is determined whether or not the value of the factor _xn obtained in step S17 is within a range allowed as a constraint condition. If it is determined that the value of the calculated factor _xn exceeds the allowable range, the process proceeds to step S19, and the value of _xn is set to a value within the allowable range (for example, on the side exceeding the allowable range). Value). Next, it progresses to step S20, and after designating another factor to change, it returns to step S17 and repeats the procedure after step S17.

On the other hand, in step S18, 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, the target value of the visual characteristic values in painting work Since it should be satisfactory, it progresses to step S21 and determines all the paint conditions and coating conditions. 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, it progresses to step S22 and feeds forward the value determined by step S21 to painting operation. The painting operation is controlled by using the conditions fed forward in step S22.

  When the procedure up to step S22 is completed, the process returns to step S11, and the procedure after step S11 is repeated.

  The procedure described with reference to FIGS. 4A and 4B is an example showing that the painting method according to the present embodiment can be performed, and the painting operation can be controlled by using a multiple regression equation. If present, the order of the steps may be different, a specific step may be omitted, and another step 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 determining at least one appropriate paint condition and / or factors related to the paint conditions in response to changes in the paint operating conditions, the optimum paint conditions and paint conditions for one of the above visual characteristic values It is also possible to obtain a factor relating to the above and use the result. However, there is a possibility that the influence of the factors relating to the paint condition and the paint condition is different for each visual characteristic value. 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 is a block diagram showing the configuration of the coating control apparatus according to the embodiment of the present invention. The coating control apparatus 30 shown below is an example including a function as a simulator for creating a multiple regression equation described with reference to FIG. 3 and a function for executing the coating method described with reference to FIGS. 4A and 4B. is there. 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 visual characteristic values for creating multiple regression equations, paint conditions, data on factors related to painting conditions, data on visual characteristic values generated in actual operation, data on paint conditions, factors on painting conditions, The data are stored in the corresponding storage units via the input unit 34 and the calculation / control unit 33, respectively. The operation data storage unit 32a stores the visual characteristic values, the actual measurement values of the factors related to the paint conditions and the coating conditions, and the set values thereof. The constraint condition storage unit 32b stores at least a predetermined value. The permissible range and target value of the visual characteristic value set for each paint having the above composition are stored, and the permissible range and target value of the paint condition and coating condition are stored. Each data is stored in the multiple regression equation data storage unit 31 and the actual operation data storage unit 32 for each paint having a predetermined composition.

  When creating a multiple regression equation, the calculation / control unit 33 creates a multiple regression equation using the data stored in the data storage unit 31a for multiple regression analysis according to the procedure described with reference to FIG. Then, the obtained multiple regression equation is stored in the multiple regression equation storage unit 31b.

  The monitoring and control in the actual operation described with reference to FIGS. 4A and 4B are mainly performed using data stored in the operation data storage unit 32a and the constraint condition storage unit 32b of the actual operation data storage unit 32. It is executed by the calculation / control unit 33. The visual characteristic values and the factor values calculated by the calculation of the calculation / control unit 33 are output to the output unit 35 and, if necessary, the input / output means 27 of the control unit 25 of the automatic coating machine 20 directly. (Refer to FIG. 2) and used for control of 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 stored in the multiple regression equation storage unit 31b.

  The above functions included in the painting control apparatus 30 shown in FIG. 5 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 an automatic painting machine is shown in FIG. The painting facility 10 is an automatic painting facility 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. , Conveyor unit for transporting the object to be coated 11 at a constant speed, automatic coating machine 13 for spraying paint on the object to be coated 11, reciprocation for moving the automatic coating machine 13 to an appropriate position with respect to the object to be moved 11 A caterer or robot and an automatic painting control device 26 for controlling painting operations 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. Furthermore, the coating operation control described with reference to FIGS. 4A and 4B is executed by the coating 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 accuracy of the multiple regression equation used in the embodiment of the present invention was confirmed. 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.) Manufactured by: electrodeposition coating of epoxy resin, polyamine cationic resin and block polyisocyanate compound as curing agent) so that the coating thickness after curing is 20 μm, and heating at 170 ° C. for 20 minutes An electrodeposition coating film was formed by crosslinking and curing.

  In addition, on the surface of the electrodeposition coating, intermediate coating: Trade name "Lugabake Intermediate Coating Gray" (manufactured by Kansai Paint Co., Ltd .: coating containing polyester resin, melamine resin and organic solvent), coating thickness after curing Was applied by air spray so as to be 30 μm, and was heated at 140 ° C. for 30 minutes to be crosslinked and cured to form an intermediate coating film. 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.

  The top coating material to be applied to the substrate was prepared by the following method. Product name: Alpaste 7680NS (manufactured by Toyo Aluminum Co., Ltd., scaly aluminum flake pigment, solid per 100 parts by mass (solid content) of a hydroxyl group-containing acrylic resin (hydroxyl value 100, number average molecular weight 20000) and melamine resin An organic solvent-type paint containing about 25% by mass of solid was prepared by blending 20 parts by mass in terms of solid content, stirring and mixing, and diluting to a viscosity suitable for coating.

  Next, the prepared organic solvent-type paint was applied to the substrate using a bell-type coater. In painting, among the paint conditions and the factors related to the paint conditions, paint discharge amount, shaping air pressure (SA pressure) and bell rotation speed are set to 3 levels, and 7 conditions are selected by combining them. The substrate was painted with All other paint conditions and factors related to painting conditions were fixed. Seven test panels were produced by heating the coated substrate at a temperature of 140 ° C. for 30 minutes to cure the coating film.

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, trade name: ALCOPE (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).
FF value = 0.2 × (IV−SV) / (IV + SV) (1)
Table 1 summarizes the coating values (paint discharge amount, shaping air pressure, bell rotation speed) and the measured values of the FF values for the seven test panels.

Next, each explanatory variable related to each factor of paint discharge amount, shaping air pressure, and bell rotation speed is expressed as a function of each factor, so multiple regression analysis based on the value of each factor Explanatory variable values used in were obtained. The values of the above three factors (values shown in Table 1) can be used as they are as explanatory variable values. However, as described above, in the case of the painting method according to the present invention, in the multiple regression equation related to the FF value, the bell rotation number is a squared value, and the multiple correlation coefficient of the multiple regression equation is used. Since the present inventors have confirmed that the explanation rate can be improved, the bell rotation number is a square value, and the paint discharge amount and the shaping air pressure are first-order values. In the multiple regression analysis, each factor was used in the form of a ratio of an actual value (displayed with “actual”) to a reference value (displayed with “reference”). The standard values for each factor are as follows. Discharge amount: 160 cc / min, SA pressure: 2.45 × 10 ⁵ Pa, bell rotation speed: 25,000 rpm.

  Table 2 shows the explanatory variable values of each factor used in the multiple regression analysis.

The following equation (2) was obtained as a result of performing multiple regression analysis using the explanatory variable value corresponding to each factor shown in Table 2 and using the FF value obtained by actual measurement as the objective variable.
FF value = −0.300 × (actual discharge amount / reference discharge amount) + 0.125 × (actual SA pressure / reference SA pressure) + 0.130 × (actual bell rotation speed / reference bell rotation speed) ² +1.59 ( 2)
Next, a test for confirming the accuracy of the equation (2) was performed. Ten test panels were manufactured under the conditions shown in Table 3. 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 obtained by the equation (2).

  Table 3 summarizes the coating conditions, the actual measurement value and the calculated value (estimated value) of the FF value.

  As is clear from Table 3, the difference between the measured value and the calculated value of the FF value is extremely small, and it has been confirmed that the FF value can be estimated with high accuracy by the equation (2).

  In Example 2, a test panel was prepared using a top coating different from the case of Example 1, and a multiple regression equation was obtained, and the control accuracy of the FF value by using the obtained multiple regression equation was confirmed. In the top coat used for the preparation of the test panel, trade name: Alpaste 7620NS (manufactured by Toyo Aluminum Co., Ltd .: solid content 70% by mass) was blended as a scaly aluminum flake pigment. Other conditions are the same as those in the first embodiment. The measurement of the FF value is also the same as in the first embodiment.

  Table 4 summarizes the coating conditions (paint discharge amount, shaping air pressure, bell rotation speed) and the measured values of the FF values for the seven test panels.

The procedure for creating the multiple regression equation is the same as that in the case of the first embodiment, and thus a duplicate description is omitted. Further, the reference values of the paint discharge amount, the SA pressure, and the bell rotation speed are the same as those in the first embodiment. As a result of the multiple regression analysis, the following equation (3) was obtained.
FF value = −0.32 × (actual discharge amount / reference discharge amount) + 0.125 × (actual SA pressure / reference SA pressure) + 0.157 × (actual bell rotation number / reference bell rotation number) ² +1.69 ( 3)
Next, the control accuracy of the FF value by changing the coating conditions (paint discharge amount, shaping air pressure, bell rotation speed) was investigated. First, set the target value of the FF value so that the FF value is 1.65 or more, and use the above equation (3) to determine the coating conditions (paint discharge amount, shaping air pressure, and bell rotation speed factors). Appropriate combinations were sought.

  Table 5 shows the target values of the set FF values, the calculation results regarding the combination of the paint discharge amount, the shaping air pressure, and the bell rotation speed corresponding to each FF value, and the test panel obtained by painting under the conditions. Measured values of FF values are shown together.

As shown in Table 5, the paint discharge rate is 140-200 cc / min, the shaping air pressure is 1.47-2.94 × 10 ⁵ Pa, and the bell rotation speed is 22,000-35,000 rpm. Under the conditions changed to, coating was performed in search of appropriate combinations of the conditions. As a result, it was confirmed that the difference between the target value of the FF value and the actually measured value was within 0.01 and was extremely small.

  From the above results, with the change of the line speed in the painting line, for example, even when the discharge amount of the paint is changed, the multiple regression equation is used to obtain the appropriate value of the shaping air pressure or the bell rotation speed, By coating under the obtained conditions, it was confirmed that the FF value of the coating film can be controlled within a predetermined value, that is, within the range of constraint conditions.

  The coating method according to the present invention can be carried out by using the coating equipment and the coating control apparatus according to the present invention, and can be applied, for example, to the coating of industrial products such as automobile bodies with a paint containing a bright pigment. Thereby, the visual characteristic values such as the color and texture of the coating film are controlled and maintained with high accuracy.

It is a typical top view which shows the structure of the principal part of coating equipment. 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 | generates the multiple regression equation used with the coating method which concerns on embodiment of this invention, and calculates | requires the visual characteristic value of a coating color based on the obtained multiple regression equation. It is a flowchart which shows the procedure which estimates the factor which concerns on the coating condition and coating condition from which the visual characteristic value of the target coating color is obtained using the multiple regression equation used with the coating method which concerns on embodiment, and step S11- S14 is shown. It is a flowchart which shows the procedure which estimates the factor which concerns on the coating condition and coating condition from which the visual characteristic value of the target coating color is obtained using the multiple regression equation used with the coating method which concerns on embodiment, and step S15- S22 is shown. 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 Coating gun of bell type coating machine 22 Paint supply nozzle 23 Bell cup 24 Air outlet 25 Control system 26 Automatic coating machine control device 30 Coating control Device 31 Data storage unit for multiple regression equation 32 Data storage unit for actual operation 33 Calculation / control unit

Claims (5)

  In a coating method by spraying paint onto an object to be coated in the painting booth using an automatic painting machine arranged in the painting booth, the coating film applied to each of the paints of a predetermined composition Multiple regression obtained by performing multiple regression analysis using the data for creating multiple regression equations with the visual characteristics of paint color including color and texture as objective variables and factors related to paint conditions and paint conditions as explanatory variables A painting method characterized by calculating a relationship between an objective variable value and an explanatory variable value in a painting operation by using an equation, and controlling and / or monitoring a painting operation based on the result.   The factor relating to the paint condition includes at least one of the viscosity of the paint, the blending ratio of the solid content, and the blending ratio of the solvent for dilution, and the factors relating to the coating condition include the discharge amount of the paint and the coating atmosphere. The temperature of the coating atmosphere, 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 bell cup rotation speed, And at least one of atomizing air pressure, atomizing air flow rate, shaping air pressure, shaping air temperature, shaping air humidity, and shaping air flow rate, and the visual characteristic of the paint color is the chromaticity of the Munsell color system L * a * b * color system chromaticity, L * C * h color system chromaticity, Hunter Lab color system chromaticity, XYZ color system chromaticity, spectral reflectance, IV value, Small number of SV value and flip-flop value Both methods paint according to claim 1, characterized in that it comprises one.   A coating control apparatus used for controlling the coating method according to claim 1 or 2, comprising a multiple regression equation storage unit, a calculation / control unit, an input unit, and an output unit, each for a paint having a predetermined composition In addition, using the multiple regression equation stored in the multiple regression equation storage unit, the function for obtaining the explanatory variable value corresponding to the objective variable value and / or the objective variable value is obtained based on the explanatory variable value. A painting control device characterized by having a function.   Furthermore, a data storage unit for creating a multiple regression equation is provided, and for each of the paints of a predetermined composition, the input paint color visual characteristic value is an objective variable value, and the paint conditions and the factors relating to the paint conditions The coating control apparatus according to claim 3, further comprising a function of creating a multiple regression equation using the data relating to the data as explanatory variable values. An automatic painting facility that performs painting while moving a plurality of objects to be coated, comprising the painting control device according to claim 3 or 4, and using a multiple regression equation stored in the painting control device, The relationship between the objective variable value and the explanatory variable value is calculated, and the visual characteristic value of the paint color related to the objective variable value and the paint condition and / or the factor related to the paint condition related to the explanatory variable value are: It is configured to calculate the value of the paint condition and / or the factor related to the paint condition so as to fall within an allowable range, and to control and / or monitor the paint operation based on the result. Painting equipment.

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