JP7703900B2 - Coating quality prediction method - Google Patents

Description

This disclosure relates to a method for predicting coating quality.

Conventionally, the general method for evaluating coating quality is to actually prepare test pieces for each expected substrate/color/painting process and conduct durability tests simulating the market. However, a more convenient and reliable method for evaluating coating quality has been proposed, for example, using a rigid pendulum type viscoelasticity measuring device (FDOM) (see, for example, Patent Documents 1 and 2).

Patent Document 1 describes a method for evaluating the base hiding ability of a paint. In this method, a sample having a coating film before cure shrinkage treatment is prepared, and while the sample is subjected to cure shrinkage treatment, a process for measuring the cure progress of the coating film over time and a process for measuring the shrinkage progress of the coating film over time are simultaneously carried out. Then, from the change in the cure progress over time and the change in the shrinkage progress over time, an index of the effect of the unevenness of the base on the unevenness that appears on the coating film surface after cure shrinkage treatment is calculated. For example, the method of measuring the cure progress of the coating film is described as using a pendulum-type viscoelasticity measuring device.

Patent Document 2 also describes a method for measuring the viscoelasticity of paint using a rigid pendulum-type viscoelasticity measuring device, in which the viscoelastic behavior of only a clear coating film applied over a base coating film is measured. Specifically, in this method, the measurement edge of a rigid pendulum is brought into contact with the surface of a sample application plate on which a base coating film and a clear coating film have been applied over the base coating film, and while the measurement edge is finely moved up and down relative to the sample application plate, a current is passed between the measurement edge and the sample application plate, and the current value is measured. Then, the finely moved up and down of the rigid pendulum is stopped at the position where the current value changes suddenly, and the viscosity of only the clear coating film is measured.

JP 2006-038533 A Japanese Patent Application Publication No. 05-296912

However, the methods of Patent Documents 1 and 2 require the preparation of test specimens having the coating film to be evaluated for each test, which makes it difficult to deal with the increase in evaluation labor hours that accompanies the use of multi-material materials. There is also a demand for further improvement in the reliability of the tests.

Therefore, this disclosure provides a coating quality prediction method that requires less evaluation effort and is highly reliable.

In order to solve the above problems, the coating quality prediction method disclosed herein is a method for predicting the quality of a coating film after curing in a coating material comprising a substrate and a coating film provided on the surface of the substrate, the method comprising the steps of: preparing a test piece comprising a test substrate and a test coating film before curing provided on the surface of the test substrate; performing a rigid pendulum type viscoelastic measurement on the test piece to determine the degree of bridging of the test coating film when the test piece is heated and the test coating film is cured; determining conditions of a baking temperature and baking time for the test coating film that bring the degree of bridging into a predetermined range based on the heating temperature and heating time of the test piece and the degree of bridging; and predicting the quality of the coating film after curing based on the conditions, the method further comprising a step of calculating temperature information for each part of the coating material when the entire coating material is heated, and the prediction step further predicts the quality of the coating film after curing for each part of the coating material based on the temperature information .

The thermosetting resin, which is the main component of the coating, hardens when the temperature of the resin rises, and chemical crosslinking occurs due to a chemical reaction between the resin molecules, and physical crosslinking occurs due to the physical entanglement of the resin molecules, simultaneously progressing, forming a three-dimensional network structure of the resin.

In general, the degree of chemical crosslinking in a thermosetting resin can be analyzed by spectroscopic techniques such as infrared spectroscopy. On the other hand, the degree of physical crosslinking in a thermosetting resin is difficult to directly observe by spectroscopic techniques and can be analyzed by computational chemistry techniques such as rheology simulation and first-principles molecular dynamics calculation. However, it is difficult to combine the results of the analysis of the degree of chemical crosslinking by spectroscopic techniques with the results of the analysis of the degree of physical crosslinking by computational chemistry techniques to analyze the degree of formation of a comprehensive three-dimensional network structure by chemical crosslinking and physical crosslinking in a thermosetting resin (also referred to as the "degree of crosslinking" in this specification).

In rigid pendulum viscoelasticity measurements, the measurement edge of a rigid pendulum is placed in contact with the surface of a test substrate on which an uncured test coating is applied, and the test piece is heated while the rigid pendulum is oscillated to measure changes over time in the period of the oscillating motion, logarithmic reduction rate, etc. The period of the oscillating motion primarily reflects the elasticity of the resin, and the logarithmic reduction rate reflects the viscosity of the resin.

For example, the period of the oscillation motion, which reflects the elasticity of the resin, begins to decrease as crosslinking of the resin begins. The period then continues to decrease as crosslinking progresses, and when sufficient crosslinking is formed, the rate of decrease slows and eventually becomes almost constant. In other words, the change over time in the period of the oscillation motion reflects the change over time in the overall degree of crosslinking of the test coating film. In other words, by measuring the change over time in the period of the oscillation motion, it is possible to accurately analyze the starting point of crosslinking of the resin, the rate of crosslinking of the resin, the progress of crosslinking in the resin, the activation energy of crosslinking, the starting temperature of crosslinking, etc.

In this configuration, the conditions of the baking temperature and baking time of the test coating film that bring the degree of cross-linking into a predetermined range are determined based on the information on the heating temperature and heating time of the test piece in the rigid pendulum type viscoelasticity measurement and the information on the degree of cross-linking. This makes it possible to express the relationship between the quality of the test coating film and the baking temperature and baking time of the test coating film simply, in detail, and with high accuracy.

Then, the quality of the coating film after hardening is predicted based on the above conditions. Specifically, when the test piece has the same specifications as the coating material to be predicted, the above conditions correspond to the baking temperature and baking time conditions that bring about a predetermined range of bridging degree in the coating film to be predicted. Therefore, since the quality of the coating film after hardening can be predicted theoretically based on the above conditions, it is possible to realize a highly reliable coating quality prediction while reducing the number of evaluation items. In addition, the degree of effect on the coating film quality when the baking temperature and baking time of the coating film are changed can be predicted simply and accurately.

Furthermore, when considering changes to the paint composition, it is conceivable that the above conditions will not be determined for test pieces with the same specifications as the coating material to be predicted. Even in such cases, the above conditions for the coating film to be predicted can be roughly calculated based on the above conditions determined in advance for various test pieces. In this way, the quality of the coating film to be predicted can be predicted based on the calculated above conditions, so the degree of impact that changes in the paint composition, etc., will have on the coating film quality can be predicted simply and accurately on paper. It is also possible to predict the coating film quality of new paints based on the above conditions of test coatings for various existing paints, making it possible to efficiently develop new paints.

Preferably, in the prediction process, the quality of the coating film after curing is predicted based on the set values of the baking temperature and baking time for the coating film.

As described above, the above conditions simply and precisely represent the relationship between the quality of the test coating film and the baking temperature and baking time of the test coating film. Therefore, particularly when the test piece has the same specifications as the coating material to be predicted, by comparing the above conditions with the set values of the baking temperature and baking time for the coating film to be predicted, the post-hardening quality of the coating film to be predicted can be predicted simply and precisely on paper. In addition, the degree of effect on the coating film quality when the baking temperature and baking time of the coating film are changed can be predicted simply and precisely on paper.

Preferably, the method further includes a step of calculating the amount of thermal energy applied to the test piece in the rigid pendulum type viscoelasticity measurement based on the heating temperature and heating time of the test piece and the material properties of the test substrate, and in the prediction step, the quality of the coating film after curing is predicted based on the amount of thermal energy.

In this configuration, the measurement principle of rigid pendulum type viscoelasticity measurement is utilized to calculate the amount of heat energy required for hardening the test coating, i.e., for the formation of crosslinks, taking into consideration information such as the type and size of the test substrate. By comparing the above conditions with the amount of heat energy, it is possible to visualize the influence of material properties such as the type and size of the substrate, in addition to the composition of the paint, on the degree of crosslink formation of the coating. Then, by predicting the quality of the hardened coating to be predicted based on the above conditions and the amount of heat energy, it is possible to make a highly accurate prediction that takes into account the combination of the paint and the substrate, thereby improving the reliability of the test. In addition, when considering the adoption of a new substrate, the influence of the new substrate on the quality of the hardened coating can be confirmed easily and accurately.

This configuration further includes a step of calculating temperature information for each part of the coating material when the entire coating material is heated, and in the prediction step, the quality of the coating film after hardening for each part of the coating material is predicted based on the temperature information.

This configuration makes it possible to clarify the relationship between the design factors of the coating material (material properties of the substrate and design values of the structural surface, etc.) and the coating film quality. In addition, the coating film quality for each part of the coating material, which is brought about by the design factors of the coating material, the baking temperature, and the baking time, can be predicted on paper, which greatly improves development efficiency.

Preferably, the rigid pendulum type viscoelasticity measurement involves heating the test piece while swinging the rigid pendulum with the measuring edge of the rigid pendulum in contact with the surface of the test substrate, and measuring the change over time in the period of the swinging motion of the rigid pendulum, and the degree of bridging of the test coating is calculated based on the change over time in the period of the swinging motion.

As described above, the change over time in the period of the oscillating motion accurately reflects the change over time in the overall degree of cross-linking due to both chemical and physical cross-linking in the coating film. Therefore, by calculating the degree of cross-linking of the coating film based on the change over time in the period of the oscillating motion, it is possible to achieve a highly reliable prediction of the quality of the coating film.

The specified range of the degree of bridging is the range that provides an acceptable range of durability quality for the test coating film after curing.

This allows for highly reliable quality predictions that ensure excellent durability of the coating.

Preferably, the coating material is the body of a vehicle.

This configuration makes it possible to easily and accurately predict the quality of the coating film applied to the vehicle body.

Preferably, the substrate is made of at least one material selected from the group consisting of steel, aluminum, and polypropylene resin.

This disclosure can be applied to a variety of substrates and can also accommodate multi-material applications.

As described above, according to the present disclosure, the relationship between the quality of a test coating film and the baking temperature and baking time of the test coating film can be expressed simply, in detail, and with high accuracy. Furthermore, since the post-curing quality of the coating film to be predicted can be predicted theoretically, it is possible to realize a highly reliable prediction of the quality of the coating film while reducing the number of evaluation items.

FIG. 2 is a diagram for explaining the relationship between the hardening of a coating film and the quality of the coating film. 1 is a flowchart showing the steps of a coating quality prediction method according to the present disclosure. FIG. 2 is a diagram for explaining a measurement method for rigid pendulum type viscoelasticity measurement. 1 is a graph showing an example of a temperature profile of a test piece. 6 is a graph showing the change over time in the period of the swinging motion of a rigid pendulum at various baking temperatures. 1 is a graph showing the relationship between heating time and degree of cross-linking. Baking window map for clear coating. Baking window map for low-temperature curing clear coating. Thermal energy amount map when steel plate is used as the substrate. Heat energy amount map when aluminum is used as the base material. Thermal energy map when polypropylene is used as the base material. FIG. 11 is a diagram showing the results of a vehicle body seizure simulation.

Embodiments of the present disclosure will now be described in detail with reference to the accompanying drawings. The following description of the preferred embodiments is merely exemplary in nature and is in no way intended to limit the present disclosure, its applications, or its uses.

(Embodiment 1)
<Painting materials>
The coating quality prediction method disclosed herein is a method for predicting the quality of a coating film after curing in a coating material including a substrate and a coating film formed on the surface of the substrate and made of a paint containing a thermosetting resin as a main ingredient.

The uses of the coating materials are not particularly limited, but specific examples include uses on vehicle bodies and other parts, home appliances, building materials, etc.

The substrate of the coating material, the coating film, and the coating film forming method are described below. Note that the following description of the substrate of the coating material, the coating film, and the coating film forming method also applies to the test substrate 11, the test coating film 12, and the method of forming the test coating film 12 of the test piece 1 described later.

[Base material]
The substrate is a metal material, a resin material, or a composite material thereof.

Specific examples of metal materials include iron, steel, copper, aluminum, tin, zinc, and alloys thereof. The metal material is preferably a steel plate such as cold-rolled steel sheet (SPC), galvannealed steel sheet (GA), high-tensile steel sheet or hot-stamped material, or a light alloy material such as aluminum. The substrate may have a chemical conversion coating (phosphate coating (e.g., zinc phosphate coating), chromate coating, etc.) formed on the surface.

Specific examples of resin materials include polypropylene resin (PP), polycarbonate resin, urethane resin, polyester resin, polystyrene resin, ABS resin, polyvinyl chloride resin, polyamide resin, etc.

The substrate is preferably made of at least one material selected from the group consisting of steel, aluminum, and polypropylene resin. When the coating to be predicted is a coating applied to the surface of a member that constitutes the body of a vehicle, these materials may be selected as the material of the body, which is the substrate.

[Coating film]
The coating film is not particularly limited as long as it is a coating film containing a thermosetting resin as a main component.

Specific examples of thermosetting resins that are the main components of the coating film include urethane resins such as polyurethane resins and urethane acrylate resins, epoxy resins, acrylic resins, vinyl ester resins, phenolic resins, polyimide resins, urea resins, melamine resins, bismaleimide resins, and unsaturated polyester resins. The thermosetting resin may be a single resin material, a copolymer of a resin material with another resin material, a modified resin, or a resin material that is a blend of two or more types. The thermosetting resin is preferably at least one selected from the group consisting of urethane resins, epoxy resins, and acrylic resins. The paint that is the raw material of the coating film may be a one-component curing type or a two-component curing type.

Specific examples of coating films include urethane resin-based clear coating films and low-temperature curing clear coating films used as topcoat coating films, and epoxy resin-based and acrylic resin-based cationic electrocoating coating films used as base coating films. The coating film may also be a multilayer coating film in which a topcoat coating film is superimposed on a primer coating film, or a multilayer coating film in which an intermediate coating film and a topcoat coating film are superimposed on an electrocoating coating film.

[Coating film formation method]
A coating material is applied to the surface of a substrate by spraying, electrodeposition, brushing, or the like to form a coating film before curing, and then the coating film is cured by baking.

Figure 1 shows the relationship between the hardening of the coating film and the quality of the coating film. When the baking temperature and baking time are appropriate, the initial coating film immediately after baking has a sufficient three-dimensional network structure formed by crosslinking due to the formation of chemical bonds between resin molecules (chemical crosslinking) and crosslinking due to physical entanglement between resin molecules (physical crosslinking) (sufficient degree of bridging). In this way, even if an external force is applied to the surface of the coating material due to contact with a stone or the like, the coating film will fully absorb the impact energy through elastic deformation, and destruction of the coating film will be suppressed due to shear strength, etc., and it will exhibit excellent chipping resistance to the substrate.

On the other hand, if the baking temperature is low and/or the baking time is short, the formation of a three-dimensional network structure through chemical and physical cross-linking in the initial coating film will be insufficient (the degree of cross-linking will be low). If this happens, when an external force is applied to the surface of the coating material due to contact with a stone or the like, the coating film will not be able to absorb the impact energy sufficiently, and the coating film will be destroyed, for example, from weak points where bonds are insufficiently formed.

<Coating quality prediction method>
As shown in FIG. 2, the coating quality prediction method according to this embodiment includes a preparation step S1, a viscoelasticity measurement step S2, a baking window map creation step S3, an arbitrary heat energy amount calculation step S4, an arbitrary temperature information calculation step S5, and a prediction step S6.

Note that cases in which the thermal energy amount calculation process S4 and/or the temperature information calculation process S5 are included will be described in embodiments 2 to 4 below.

[Preparation process]
3, in a preparation step S1, a test piece 1 is prepared, which includes a test substrate 11 and a test coating film 12 before curing provided on the surface of the test substrate 11. Specifically, for example, a paint, which is a raw material of the test coating film, is applied to the surface of the test substrate 11 by a spray or the like to form the test coating film 12.

The test substrate 11 may be of the same specifications as the substrate of the coating material to be predicted, or may be of different specifications, but from the viewpoint of improving prediction accuracy, it is preferable that the test substrate 11 has the same specifications as the substrate of the coating material to be predicted or similar specifications.

[Viscoelasticity measurement process]
Next, in a viscoelasticity measurement step S3, a rigid pendulum type viscoelasticity measurement is performed on the test piece 1 using a rigid pendulum type viscoelasticity measuring device 2. Then, the test piece 1 is heated to harden the test coating film 12, and the degree of cross-linking of the test coating film 12 is determined.

Specifically, for example, as shown in FIG. 3, the measurement edge 21a of the rigid pendulum 21 is brought into contact with the surface of the test substrate 11 on which the uncured test coating film 12 is provided.

Then, with the measuring edge 21a in contact with the surface of the test substrate 11, the rigid pendulum 21 is swung as shown by the dashed line and arrow A2 in Figure 3.

Furthermore, while the rigid pendulum 21 is oscillating, the test piece 1 is heated from the test substrate 11 side by a cooling/heating block 23 arranged on the back side of the test substrate 11, and thermal energy is applied to the test piece 1 as shown by the arrow A1. Then, while the hardening of the test coating film 12 progresses, the change over time in the period of the oscillating motion of the rigid pendulum 21 is measured. Then, the degree of bridging of the test coating film 12 is calculated based on the change over time in the period of the oscillating motion.

FIG. 4 shows an example of the temperature profile of the test piece 1. As shown in FIG. 4, the temperature of the test piece 1 starts to rise from the ambient temperature T ₀ at a constant rate of temperature rise at time t ₀ , and reaches the target temperature T ₁ at time t ₁ (heating process). Then, the temperature of the test piece 1 is maintained at the target temperature T ₁ from time t ₁ to time t ₂ (heating process). Then, heating of the test piece 1 is terminated at time t ₂ , and the temperature of the test piece 1 returns to the ambient temperature at time t ₃ by cooling and/or cooling (temperature decreasing process). In this specification, the temperature T of the test piece 1 from the start of the heating process to the end of the heat-keeping process may be referred to as the "heating temperature", and the time t elapsed from the start of the heating process may be referred to as the "heating time" of the test piece 1. In addition, the definition of the baking time of the coating film may take into account the time of only the heat-keeping process, or may take into account the time of the heating process and the heat-keeping process. For the sake of convenience, the time required for the temperature increase and temperature maintenance steps, i.e., the time from time _t0 when the temperature increase starts to time _t2 when the temperature maintenance ends, is referred to as the "baking time." Also, the target temperature _T1 is referred to as the "baking temperature."

As described above, the change over time in the period of the oscillating motion of the rigid pendulum 21 reflects the change over time in the overall degree of bridging of the test coating film 12.

Specifically, Figure 5 is a graph showing the change over time in the period of the swinging motion of the rigid pendulum 21 at various baking temperatures when a clear coating is used as the test coating 12. The test piece 1 used in the test in Figure 5 is a test piece formed by spraying a urethane resin-based two-component curing clear paint as the test coating 12 onto the surface of a steel plate (20 mm x 50 mm x 0.3 mm) as the test substrate 11 so that the thickness before curing is approximately 100 μm.

5, the temperature of the test piece 1 started to be increased at time 0 minute (= _t0 ). Then, at time 5 minutes (= _t1 ), the temperature of the test piece 1 reached the target temperature _T1 (80°C, 90°C, 100°C, 130°C, 140°C, 170°C), and was maintained at the target temperature _T1 thereafter.

The larger the period number, the less cross-linking of the resin will progress, and the lower the elasticity of the test coating film 12 will be. The smaller the period number, the more cross-linking of the resin will progress, and the higher the elasticity of the test coating film 12 will be.

The period of the oscillation motion, which was about 0.72 to about 0.76 at the start of the temperature rise, began to decrease about 8 minutes to about 13 minutes after the start of the temperature rise at all target temperatures _T1 . The point at which the period began to decrease is considered to be the starting point of crosslinking of the resin.

When the target temperature _T1 is 130°C or higher, the cycle becomes 0.10 or less about 13 to 16 minutes after the start of the temperature rise, and then the cycle becomes almost constant. As described above, the change in the cycle over time reflects the speed of crosslinking of the resin and the degree of progress of the crosslinking. Therefore, when the target temperature _T1 is 130°C or higher, the crosslinking of the resin progresses quickly after the start of the crosslinking of the resin, and it is considered that the cycle becomes almost constant when the crosslinking of the resin eventually becomes saturated.

When the target temperature _T1 was 100° C. or lower, the rate of decrease in the cycle was slower and the width of decrease in the cycle was smaller than when the target temperature _T1 was 130° C. or higher. This means that the target temperature _T1 was insufficient to sufficiently promote the crosslinking of the thermosetting resin, and the progress of the crosslinking was slow.

Based on the data on the change over time in the cycle shown in Figure 5, the degree of bridging (%) of the test coating film 12, indicated by the open double-headed arrow in Figure 5, was calculated using the following formula (1).

Degree of bridge formation (%) = [(P ₀ - _{P t} )/P ₀ ]×100 (1)
In the above formula (1), P ₀ is the period at the start of printing (5 minutes=t ₀ ), and P _t is the period at time t.

Fig. 6 is a graph plotting the degree of bridging calculated by the above formula (1) against time, and shows an enlarged portion of the portion with a degree of bridging of 80% to 100% and a time of 10 minutes to 25 minutes. As shown in Fig. 6, it was found that the degree of bridging was 89.3% when the baking temperature of the clear paint used and the target temperature _T1 , which is the lower limit of the baking temperature, were 130°C and the time was 20 minutes. In addition, when the target temperatures _T1 were 170°C and 140°C, which are baking temperatures higher than 130°C, the time at which the degree of bridging reached 89.3% was about 15.5 minutes and about 17 minutes, respectively.

[Baking window map creation process]
Next, in the baking window map creation process S3, the conditions for the baking temperature and baking time of the test piece 1, particularly the baking temperature (= target temperature _T1 ) and baking time of the test coating film 12, which result in a bridge formation degree within a specified range, are determined based on the bridge formation degree calculated by the above formula (1).

Specifically, for example, based on the information on the degree of bridging obtained from the experiments in Figures 5 and 6, the combinations of baking temperature and baking time that result in the same degree of bridging are plotted as shown in Figure 7, with the baking temperature and baking time on the horizontal and vertical axes, respectively. Then, a regression curve is obtained for each degree of bridging.

The baking conditions that yielded the lower limit, standard value, and upper limit of the durability quality of the clear coating (after curing) used in the experiment were previously considered to be, for example, baking temperature 130°C x baking time 20 minutes, baking temperature 140°C x baking time 25 minutes, and baking temperature 170°C x baking time 30 minutes, respectively.

As shown by the circles in FIG. 7, the baking conditions that result in the above-mentioned lower limit, standard value, and upper limit are the baking conditions that result in bridging degrees of 89.3%, 90.3%, and 91.2%, respectively. Therefore, it can be seen that the regression curves of bridging degrees of 89.3%, 90.3%, and 91.2% are lines that result in the lower limit, standard value, and upper limit of the durability quality of the cured film of the above-mentioned clear paint. The hatched area in FIG. 7, that is, the area sandwiched between the regression curves of bridging degrees of 89.3% and 91.2%, can be said to be the allowable range of the durability quality of the clear coating film (after curing) used in the experiment (in this specification, the allowable range of the durability quality of the coating film after curing or the test coating film 12 is called the "baking window").

In this way, in the baking window map creation step S3, a map showing the relationship between the baking temperature and baking time of the test coating film 12 and the degree of bridging, as shown in FIG. 7, is created (in this specification, a map showing the relationship between the baking temperature and baking time of the cured coating film or the test coating film 12 and the degree of bridging is referred to as a "baking window map"). The baking window map can easily and precisely show the relationship between the baking temperature and baking time of the test coating film 12 and the quality of the test coating film 12. By creating a baking window map, the baking conditions of the coating film, which could only be grasped at points in the past, can be grasped as an area. In addition, for example, if a baking window map is created for a new paint, the baking window of the new paint becomes clear, making it easier to set the baking conditions.

Next, the clear paint on test piece 1 was replaced with a urethane resin-based two-component curing low-temperature curing clear paint, and an experiment similar to the one that gave the results in Figures 5 and 6 was conducted. The baking window map shown in Figure 8 was obtained. In Figure 8, the baking window of the clear coating in Figure 7 is shown by a dashed line.

In Figure 8, the regression curves for bridging degrees of 82.2%, 86.5% and 91.1% are lines that respectively provide the lower limit, standard value and upper limit of the durability quality of the low-temperature curing clear coating after curing. It can be seen that the area sandwiched between the regression curves for bridging degrees of 82.2% and 91.1% is the baking window of the low-temperature curing clear coating.

As shown in Figure 8, the baking window of low-temperature curing clear coatings is shifted toward the lower temperature and shorter time side compared to the baking window of clear coatings. In this way, it can be seen that the baking window map accurately shows the different baking windows depending on the type of coating.

It is preferable that the predetermined range of the degree of bridging is a range that brings about a baking window of the test coating film 12. In the examples of Figures 7 and 8, the predetermined range of the degree of bridging can be, for example, 80% or more and 100% or less, more specifically, 82.2% or more and 91.2% or less. The baking temperature and baking time conditions of the test coating film 12 that bring the degree of bridging into the predetermined range can be a combination of baking temperature and baking time included in the baking window.

In addition, from the baking window maps of Figures 7 and 8, for the clear coating film and low-temperature curing type clear coating film used in the experiments of Figures 5 to 8, the baking temperature can be, for example, 70°C or higher and 180°C or lower, and the baking time can be 10 minutes or higher and 55 minutes or lower.
[Prediction process]
The prediction step S6 is a step of predicting the post-curing quality of the coating film to be predicted based on the above conditions, i.e., the combination of baking temperature and baking time included in the baking window of the baking window map.

Specifically, when the test piece 1 has the same specifications as the coating material to be predicted, the above conditions correspond to the baking temperature and baking time that will bring about a predetermined range of bridging degree in the coating film to be predicted. Therefore, for example, by comparing the baking window map with the set values of the baking temperature and baking time in the coating film to be predicted, the quality of the coating film to be predicted after hardening can be predicted simply and accurately on paper. In this way, a highly reliable quality prediction of the coating film can be achieved while reducing the number of evaluation items. In addition, the degree of impact on the coating film quality when the baking temperature and baking time of the coating film are changed can also be predicted simply and accurately.

Furthermore, baking window maps may be created in advance for test pieces 1 equipped with various test coatings 12, for example, with different types of paint, base/hardener ratios, types/amounts of additives such as colorants, etc., and stored in a database. For example, when considering changes in the composition of a paint, it is possible to assume that baking window maps have not been created for test pieces with specifications similar to the paint material to be predicted. Even in such cases, if there is a database of baking window maps, the above conditions for the coating film to be predicted can be roughly calculated by combining multiple baking window maps. Then, the quality of the coating film to be predicted can be predicted based on the calculated conditions, so that the degree of impact of changes in the composition of the paint on the coating film quality can be predicted easily and accurately on a desk. In addition, it is also possible to predict the coating film quality of a new paint based on the above conditions of the test coatings for various existing paints, making it possible to efficiently develop new paints.

(Embodiment 2)
Other embodiments according to the present disclosure will be described in detail below. In the description of these embodiments, the same parts as those in the other embodiments will be denoted by the same reference numerals and detailed description thereof will be omitted.

<Coating quality prediction method>
As shown in FIG. 2, the coating quality prediction method of the present disclosure may include a thermal energy amount calculation step S4 prior to the prediction step S6.

[Heat energy amount calculation process]
The thermal energy amount calculation step S4 is a step of calculating the amount of thermal energy applied to the test piece 1 in the rigid pendulum viscoelasticity measurement, based on the heating temperature and heating time of the test piece 1 and the material property values of the test substrate 11. That is, in this step, the measurement principle of the rigid pendulum viscoelasticity measurement is utilized to calculate the amount of thermal energy required for curing the test coating film 12, i.e., for crosslinking, taking into account information such as the type and size of the test substrate 11.

Specifically, as shown in Figures 3 and 4, in the heating and heat-retaining steps of the viscoelasticity measurement process S2, thermal energy is applied to the test piece 1 from the cooling/heating block 23.

For example, if the time from the start of temperature rise (heating time) is t, the amount of thermal energy given to the test piece 1 in the temperature rise process (t≦t ₁ ) and the heat retention process (t>t ₁ ) can be calculated by the following formulas (2) and (3), respectively.

However, the explanation of each parameter in equations (2) and (3) is shown in Table 1.

Note that equation (2) for the temperature increase process simply takes into account only the heating of the cooling block 23. On the other hand, equation (3) for the heat retention process assumes that the amount of heat dissipated from the test piece 1 is replenished by the heating of the cooling block 23.

Of the parameters in equations (2) and (3), c, ρ, and ε are physical property values of the substrate. Furthermore, V and S are values related to the size of the test piece 1.

For the test piece 1 used in the tests of Figures 5 to 7, the amount of thermal energy given to the test piece 1 in the temperature-raising step and the heat-retaining step was calculated using the formulas (2) and (3) with the atmospheric temperature _T0 before the temperature-raising step being 301.15 K (= 28 ° C.). The results are shown in Figure 9.

Figure 9 shows the distribution of the amount of thermal energy applied to the test piece 1, with the horizontal and vertical axes representing the baking temperature and baking time, and can be considered a "thermal energy amount map." Note that Figure 9 also shows the baking window map from Figure 7 superimposed on it.

As shown in FIG. 9, the amount of thermal energy imparted to the test piece 1 during the heating process and the heat retention process generally increases as the baking temperature increases and/or the baking time increases.

When the test substrate 11 of the test piece 1 is changed from a steel plate to an aluminum plate or a PP plate, the heat energy amount map calculated by formulas (2) and (3) is as shown in Figures 10 and 11. The material property values of the test substrate 11 used in the calculations are as shown in Table 2. The baking window map of Figure 7 is also superimposed on Figures 10 and 11.

As shown in Figures 10 and 11, the amount of thermal energy given to the test piece 1 during the heating process and the heat retention process generally increases as the baking temperature increases and/or the baking time increases.

For example, when comparing the amounts of thermal energy at the positions circled with solid lines in Figures 9 to 11 where the baking temperature is 110°C and the baking time is 45 minutes, it can be seen that the amount of thermal energy imparted to the test piece 1 is lower when the test substrate 11 is an aluminum plate compared to when the test substrate 11 is a steel plate. It can also be seen that the amount of thermal energy imparted to the test piece 1 is higher when the test substrate 11 is a PP plate compared to when the test substrate 11 is a steel plate.

When the test substrate 11 is a PP plate, it will soften if the baking temperature exceeds 110°C, so it is clear that the baking temperature that creates the baking window is at least 110°C or less. In this way, for example, from Figure 11, the boundary of the baking window based on the material properties of the substrate can also be grasped.

[Prediction process]
In this embodiment, in the prediction step S6, the quality after curing of the coating film to be predicted is predicted based on the above-mentioned conditions and the amount of thermal energy calculated in the thermal energy amount calculation step S4.

Specifically, for example, as shown in Figures 9 to 11, the baking window map and the thermal energy amount map are superimposed. This makes it possible to visualize the influence of material properties such as the type and size of the substrate, in addition to the composition of the paint, on the degree of bridging of the coating film. Then, by predicting the quality of the coating film after hardening based on the above conditions and the above thermal energy amount, highly accurate prediction is possible taking into account the combination of the coating and the substrate. This improves the reliability of the test. In addition, even when considering the adoption of a new substrate from the viewpoint of lowering the baking temperature for the purpose of reducing _CO2 emissions, for example, the influence of the new substrate on the quality of the coating film after hardening can be easily and accurately confirmed.

(Embodiment 3)
As shown in FIG. 2, the coating quality prediction method of the present disclosure may include a temperature information calculation step S5 prior to the prediction step S6.

[Temperature information calculation process]
The temperature information calculation step S5 is a step of calculating temperature information for each part of the coating material when the entire coating material to be predicted is heated. Specifically, for example, a computational chemistry method such as a baking simulation can be used as a method for calculating the temperature information.

As a specific example, consider the case where the paint material is the body of a vehicle. Figure 12 shows temperature information for each part of the body when the entire body of an automobile (vehicle) is heated during the baking process after painting, calculated using a baking simulation.

For example, baking of a car body is performed by introducing the entire car body into a furnace. In such a case, even if the entire car body is heated to a constant temperature by setting the temperature on the furnace side, as shown in FIG. 12, it can be seen that the actual surface temperature of the car body varies from part to part. Such variation in surface temperature from part to part of the car body causes variation in the quality of the paint film from part to part of the car body.

[Prediction process]
In this embodiment, in the prediction step S6, the quality of the coating film after hardening for each portion of the coating material is predicted based on the above conditions and the above temperature information.

As mentioned above, the surface temperature of the coating material can vary from part to part. This can lead to variations in the quality of the coating film from part to part.

According to this configuration, by comparing the baking window maps as shown in Figures 7 and 8 with the temperature information for each part of the coating material as shown in Figure 12, the coating film quality for each part of the coating material can be predicted easily and accurately. This makes it possible to effectively adjust the set values of the baking temperature and baking time for the entire coating material, adjust the design factors of the coating material (material property values of the substrate and design values of the structural surface, etc.), etc.

(Embodiment 4)
As shown in Fig. 2, the coating property prediction method of the present disclosure may include both a thermal energy amount calculation step S4 and a temperature information calculation step S5 before the prediction step S6. Although the thermal energy amount calculation step S4 and the temperature information calculation step S5 are described in this order in Fig. 2, the order is not important. The temperature information calculation step S5 may be performed before the thermal energy amount calculation step S4.

By comparing the temperature information shown in Figure 12 with the thermal energy amount maps shown in Figures 9 to 11, the amount of thermal energy applied to each part of the coating material when it is heated can be determined. Then, by comparing it with the baking window maps shown in Figures 7 and 8, the relationship between the design factors of the coating material and the coating film quality can be clarified. This makes it possible to more accurately predict the quality of the coating film after hardening for each part of the coating material. Furthermore, since the coating film quality for each part of the coating material brought about by the design factors of the coating material, baking temperature, and baking time can be predicted on paper, the efficiency of coating material development is greatly improved.

This disclosure is extremely useful because it provides a highly reliable method for predicting coating quality with fewer evaluation steps.

REFERENCE SIGNS LIST 1 Test piece 11 Test substrate 12 Test coating 2 Rigid pendulum type viscoelasticity measuring device 21 Rigid pendulum 21a Measurement edge 23 Cooling and heating block S1 Preparation step S2 Viscoelasticity measuring step S3 Baking window map creation step S4 Heat energy amount calculation step S5 Temperature information calculation step S6 Prediction step

Claims (7)

A method for predicting a quality of a coating film after curing in a coating material having a substrate and a coating film provided on a surface of the substrate, comprising:
A step of preparing a test piece including a test substrate and a test coating film before curing provided on a surface of the test substrate;
a step of subjecting the test piece to a rigid pendulum type viscoelastic measurement, and determining a degree of crosslinking of the test coating film when the test piece is heated to cure the test coating film;
determining conditions of a baking temperature and a baking time of the test coating film that bring the degree of crosslinking into a predetermined range based on the heating temperature and the heating time of the test piece and the degree of crosslinking;
and predicting the quality of the coating film after curing based on the conditions .
The coating material may further include a step of calculating temperature information for each portion of the coating material when the entire coating material is heated.
In the prediction step, the quality of the coating film after hardening for each part of the coating material is predicted based on the temperature information.
A coating quality prediction method comprising: In claim 1,
A coating quality prediction method, characterized in that in the predicting step, the quality of the coating after curing is predicted based on set values of baking temperature and baking time for the coating. In claim 1,
The method further includes a step of calculating an amount of thermal energy applied to the test piece in the rigid pendulum type viscoelasticity measurement based on a heating temperature and a heating time of the test piece and material property values of the test substrate,
A coating quality prediction method, characterized in that in the predicting step, the quality of the coating after curing is predicted based on the amount of thermal energy. In any one of claims 1 to 3 ,
The rigid pendulum type viscoelasticity measurement is a method for measuring a change over time in a period of the oscillation motion of a rigid pendulum by heating the test piece while oscillating the rigid pendulum in a state where a measuring edge of the rigid pendulum is brought into contact with the surface of the test substrate,
A coating quality prediction method, characterized in that the degree of bridging of the test coating is calculated based on the change over time in the period of the rocking motion. In any one of claims 1 to 4 ,
A coating quality prediction method, characterized in that the predetermined range of the degree of crosslinking is a range that provides an acceptable range of durability quality of the test coating after curing. In any one of claims 1 to 5 ,
The coating quality prediction method, wherein the coating material is a vehicle body. In any one of claims 1 to 6 ,
The method for predicting coating quality, wherein the substrate is made of at least one material selected from the group consisting of steel, aluminum, and polypropylene resin.

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