Method for estimating stress characteristics of strengthened glass and method for manufacturing model for estimating stress characteristics

Abstract

A stress characteristic estimation method of strengthened glass estimates other stress characteristics among a plurality of stress characteristics in a compressive stress layer (2) formed by a plurality of ion exchange treatments, based on a part of the stress characteristics. The stress characteristic estimation method includes a sampling process (S4), a prediction model creation process (S5), a measurement process (S7), and an estimation process (S8). The other stress characteristics include a depth (DOC) of the compressive stress layer (2).

Description

Technical Field

[0001] This invention relates to a method for estimating the stress characteristics of reinforced glass with a compressive stress layer, and a method for preparing a model for estimating stress characteristics. Background Technology

[0002] Mobile phones (especially smartphones), tablets, digital cameras, automotive dashboard components, touch panel displays, and contactless power supply devices are becoming increasingly popular. These electronic devices utilize ion-exchange treated tempered glass. Furthermore, in recent years, the use of tempered glass in the exterior components of digital signage, directional devices, and smartphones has been steadily increasing.

[0003] Tempered glass achieves high strength by incorporating a compressive stress layer formed through ion exchange treatment on its surface, which inhibits the formation and propagation of surface cracks. The strength of tempered glass can be further enhanced by adjusting the formation method of this compressive stress layer. Therefore, high-precision measurement of the stress characteristics of the compressive stress layer is essential for the quality management and development of tempered glass.

[0004] Patent Document 1 discloses a surface stress measuring device that utilizes the optical waveguide effect of a compressive stress layer to determine the stress and depth of the compressive stress layer. This surface stress measuring device comprises: a light supply component that directs monochromatic light into the surface layer of tempered glass; a light extraction component that ejects light propagating within the surface layer of the glass outwards; and a light conversion component that separates the light emitted from the light extraction component into two light components that vibrate parallel and perpendicular to the interface between the glass and the light extraction component, respectively, and converts these light components into bright line arrays (see the claims of that document).

[0005] Using this surface stress measuring device, the difference in position of the bright line columns involving the two light components extracted from the glass can be determined. From this difference in position of the bright line columns, the difference in the refractive index of the two light components relative to the surface of the glass can be calculated. Then, the compressive stress on the surface of the glass can be measured from this difference in surface refractive index. In addition, the depth (thickness) of the compressive stress layer can be measured from the number of bright line columns (see column 4 on page 2 and column 5 on page 3 of this document).

[0006] Patent Document 2 discloses a stress measuring device that uses scattered light from a laser to determine the stress distribution of tempered glass. This device allows for changing the polarization phase difference of the laser relative to its wavelength by more than one wavelength using a polarization phase-variable component. The device then captures multiple images of the scattered light emitted from the tempered glass by the altered laser beam incident on it. Furthermore, a calculation unit uses these multiple images to determine the periodic brightness changes of the scattered light, calculates the phase change of the brightness changes, and calculates the stress distribution along the depth direction from the surface of the tempered glass based on the phase change (see claim 1 of this document). This stress measuring device can measure the stress within chemically tempered glass regardless of the refractive index distribution.

[0007] Existing technical documents

[0008] Patent documents

[0009] Patent Document 1: Japanese Patent Application Publication No. 53-136886

[0010] Patent Document 2: International Publication No. 2018 / 056121 Summary of the Invention

[0011] The problem the invention aims to solve

[0012] In recent years, lithium aluminum silicate (LAS) based tempered glass has attracted attention due to its high surface stress value and ability to deepen the stress layer.

[0013] In the manufacture of this strengthened glass, for example, the strengthening glass is immersed in a molten salt containing NaNO3 at high temperature to perform a first chemical strengthening treatment. This causes ion exchange between Li ions in the strengthening glass and Na ions in the molten salt. Na ions readily diffuse within the strengthened glass and are thus introduced into regions deeper than the surface of the strengthened glass.

[0014] Subsequently, the strengthening glass is immersed in a molten salt containing KNO3 to perform a second chemical strengthening treatment. This process involves ion exchange between K ions and Li or Na ions contained in the strengthening glass. Consequently, a compressive stress layer with high compressive stress, originating from K ions, is formed in a surface region that is shallower than the compressive stress layer caused by Na ions formed in the first ion exchange.

[0015] If Li ions in the glass are exchanged for Na ions in the molten salt, the refractive index of the glass decreases. Conversely, if Na and Li ions in the glass are exchanged for K ions in the molten salt, the refractive index of the glass increases. That is, in the region on the glass surface where K ions have been exchanged, the refractive index is higher than in the unexchanged portions of the glass. On the other hand, in the deeper regions where Na ions have been exchanged, the refractive index is lower than in the unexchanged portions of the glass, resulting in a state where the refractive index is disproportionate to the stress.

[0016] Therefore, although the stress measuring device utilizing the surface optical waveguide effect disclosed in Patent Document 1 can measure the stress value and stress distribution of the compressive stress layer caused by K ions, it cannot measure the stress characteristics in the deeper compressive stress region caused by Na ions.

[0017] On the other hand, the stress measuring device disclosed in Patent Document 2 can measure the stress characteristics of the stress layer at a deeper range. However, in this stress measuring device, the diameter of the laser beam becomes the resolution in the depth direction, which is, for example, about 10 μm. Therefore, the stress value cannot be measured with high precision in the shallow region from the surface of the glass to the interior (e.g., the region within 10 μm from the surface).

[0018] Therefore, in order to measure the stress characteristics from the surface to a deep interior region in lithium aluminum silicate (LAS)-based tempered glass where ion exchange between Li and Na ions and between Na and K ions have been performed, it is necessary to use both the stress measuring apparatus of Patent Document 1 and the stress measuring apparatus of Patent Document 2. Consequently, measuring the stress characteristics of a large quantity of tempered glass requires considerable time during quality management and development. Furthermore, the need to prepare multiple measuring devices during the manufacturing process increases equipment costs.

[0019] The present invention was made in view of the above circumstances, and its technical objective is to efficiently obtain the stress characteristics of tempered glass.

[0020] means for solving problems

[0021] The present invention addresses the aforementioned problems and is characterized by a method for estimating the stress characteristics of tempered glass, which involves estimating other stress characteristics based on a subset of stress characteristics within a compressive stress layer formed through multiple ion exchange treatments. The method comprises the following steps: a sampling step of obtaining the aforementioned multiple stress characteristics of a sample tempered glass having the aforementioned compressive stress layer as training data; a prediction model creation step of creating a prediction model representing the relationship between the aforementioned subset of stress characteristics and the aforementioned other stress characteristics using a computational processing device based on the aforementioned training data; a measurement step of obtaining the aforementioned subset of stress characteristics of the tempered glass having the aforementioned compressive stress layer as input data for the aforementioned prediction model; and an estimation step of inputting the input data obtained through the measurement step into the aforementioned prediction model and obtaining output data related to the aforementioned other stress characteristics, including the depth of compressive stress layer (DOC), using the computational processing device.

[0022] Based on the above structure, among the multiple stress characteristics involved in the tempered glass of the estimated object obtained through the measurement process, input data of a portion of the stress characteristics are fed into the prediction model, thereby enabling high-precision estimation of the depth of the compressive stress layer, which is a component of other stress characteristics. This significantly reduces the operation time when measuring the stress characteristics of a large number of tempered glasses. Therefore, it allows for efficient strength checks and strength analysis of a large number of tempered glasses.

[0023] In this method, the tempered glass of the presumed object and the tempered glass of the sample are plate-shaped or sheet-shaped with a surface, and the stress characteristics mentioned above may include the diffusion depth (DOL) of K ions introduced through the ion exchange treatment from the surface.

[0024] In addition, the aforementioned tempered glass has a tensile stress layer at the central position in the thickness direction of the tempered glass, and the aforementioned stress characteristics include the maximum compressive stress value (CS) in the aforementioned compressive stress layer, and the aforementioned other stress characteristics may include the maximum value of tensile stress (CT) in the aforementioned tensile stress layer.

[0025] The sampling process includes: a first sampling process for obtaining the multiple stress characteristics of the sample glass after the first ion exchange treatment in the multiple ion exchange treatments as first training data; and a final sampling process for obtaining the multiple stress characteristics of the sample glass after the last ion exchange treatment in the multiple ion exchange treatments as final training data. In the prediction model making process, the prediction model is made based on the first training data and the final training data. The measurement process includes: a first measurement process for obtaining a portion of the stress characteristics of the presumed object glass after the first ion exchange treatment in the multiple ion exchange treatments as first input data to the prediction model; and a final measurement process for obtaining a portion of the stress characteristics of the presumed object glass after the last ion exchange treatment in the multiple ion exchange treatments as final input data to the prediction model. In the presumption process, the first input data and the final input data obtained through the measurement process are input into the prediction model to obtain output data related to the other stress characteristics.

[0026] In this method, the above-mentioned multiple ion exchange treatments can be two ion exchange treatments.

[0027] In this method, during the above estimation process, by using some of the stress characteristics as explanatory variables and the other stress characteristics as target variables in regression analysis, the regression equation and its constants for the above prediction model can be obtained.

[0028] In this method, the regression equation can be a linear equation. In this case, when the maximum compressive stress value (CS) in the compressive stress layer and the diffusion depth (DOL) of K ions introduced through the ion exchange treatment from the surface are set as the explanatory variables, and the depth (DOC) of the compressive stress layer is set as the target variable, the regression equation can include the following equation (1).

[0029] DOC=aCS+bDOL+c···(1)

[0030] Here, a to c are constants.

[0031] In addition, when the maximum compressive stress value (CS) in the above-mentioned compressive stress layer and the diffusion depth (DOL) of K ions introduced through the above-mentioned ion exchange treatment from the above-mentioned surface are set as the above-mentioned explanatory variables, and the maximum value of the above-mentioned tensile stress (CT) is set as the above-mentioned target variable, the above-mentioned regression equation may include the following equation (2).

[0032] CT=dCS+eDOL+f···(2)

[0033] Here, d ~ f are constants.

[0034] In this method, the stress characteristics mentioned above include the thickness (T) of the tempered glass. When the maximum compressive stress value (CS) in the compressive stress layer, the diffusion depth (DOL) of K ions introduced through the ion exchange treatment from the surface, and the thickness (T) of the tempered glass are set as the explanatory variables, and the depth (DOC) of the compressive stress layer is set as the target variable, the regression equation may include the following equation (4).

[0035] DOC=aT+bCS+cDOL+d···(4)

[0036] Here, a to d are constants.

[0037] In this method, the aforementioned stress characteristics include the thickness (T) of the tempered glass. When the maximum compressive stress value (CS) in the compressive stress layer, the diffusion depth (DOL) of K ions introduced through the ion exchange treatment from the surface, and the thickness (T) of the tempered glass are set as explanatory variables, and the maximum value (CT) of the tensile stress is set as the target variable, the regression equation may include the following equation (5).

[0038] CT=eT+fCS+gDOL+h···(5)

[0039] Here, e ~ h are constants.

[0040] In this method, the aforementioned multiple ion exchange treatments are considered as two ion exchange treatments. In these two ion exchange treatments, the maximum compressive stress value (CS) in the compressive stress layer of the strengthened glass, which is located between the first ion exchange treatment and the last ion exchange treatment (i.e., before the second ion exchange treatment), is used. 1st ) and the diffusion depth (DOL) of K ions introduced through the above-mentioned first ion exchange treatment from the above-mentioned surface. 1st Let ) be the explanatory variable mentioned above, and let the maximum compressive stress value (CS) in the compressive stress layer of the strengthened glass after the last, i.e., the second, ion exchange treatment be the variable. 2nd The diffusion depth (DOL) of K ions introduced through the last, i.e., the second, ion exchange treatment from the aforementioned surface. 2nd When the depth of the compressive stress layer (DOC) of the tempered glass after the last ion exchange treatment (i.e., the second ion exchange treatment) is set as the explanatory variable, the regression equation can include the following equation (7).

[0041] DOC = aCS 1st +bDOL 1st +cCS2nd +dDOL 2nd +e

[0042] ···(7)

[0043] Here, a to e are constants.

[0044] In this method, the aforementioned multiple ion exchange treatments are considered as two ion exchange treatments. In these two ion exchange treatments, the maximum compressive stress value (CS) in the compressive stress layer of the strengthened glass, which is located between the first ion exchange treatment and the last ion exchange treatment (i.e., before the second ion exchange treatment), is used. 1st ) and the diffusion depth (DOL) of K ions introduced through the above-mentioned first ion exchange treatment from the above-mentioned surface. 1st Let ) be the explanatory variable mentioned above, and let the maximum compressive stress value (CS) in the compressive stress layer of the strengthened glass after the last, i.e., the second, ion exchange treatment be the variable. 2nd The diffusion depth (DOL) of K ions introduced through the last, i.e., the second, ion exchange treatment from the aforementioned surface. 2nd When the above explanatory variable is set as the above explanatory variable, and the maximum value of the tensile stress (CT) of the above-mentioned tempered glass after the last, i.e. the second ion exchange treatment is set as the above target variable, the above regression equation may include the following equation (8).

[0045] CT = fCS 1st +gDOL 1st +hCS 2nd +iDOL 2nd +j

[0046] ···(8)

[0047] Here, f~j is a constant.

[0048] In this method, the aforementioned stress characteristics include the thickness (T) of the tempered glass, the aforementioned multiple ion exchange treatments are two ion exchange treatments, and in the two ion exchange treatments, the maximum compressive stress value (CS) in the compressive stress layer of the tempered glass involved in the first ion exchange treatment and the last ion exchange treatment before the second ion exchange treatment is selected. 1st ) and the diffusion depth (DOL) of K ions introduced through the above-mentioned first ion exchange treatment from the above-mentioned surface. 1st Let ) be the explanatory variable mentioned above, and let the maximum compressive stress value (CS) in the compressive stress layer of the strengthened glass after the last, i.e., the second, ion exchange treatment be the variable. 2nd The diffusion depth (DOL) of K ions introduced through the last, i.e., the second, ion exchange treatment from the aforementioned surface. 2ndWhen the above explanatory variable is set as the above explanatory variable, the thickness (T) of the above tempered glass is set as the above explanatory variable, and the depth (DOC) of the above tempered glass after the last, i.e. the second ion exchange treatment is set as the above target variable, the above regression equation may include the following equation (10).

[0049] DOC = aT + bCS 1st +cDOL 1st +dCS 2nd +eDOL 2nd +f

[0050] ···(10)

[0051] Here, a to f are constants.

[0052] In this method, the aforementioned stress characteristics include the thickness (T) of the tempered glass, the aforementioned multiple ion exchange treatments are two ion exchange treatments, and in the two ion exchange treatments, the maximum compressive stress value (CS) in the compressive stress layer of the tempered glass involved in the first ion exchange treatment and the last ion exchange treatment before the second ion exchange treatment is selected. 1st ) and the diffusion depth (DOL) of K ions introduced through the above-mentioned first ion exchange treatment from the above-mentioned surface. 1st Let ) be the explanatory variable mentioned above, and let the maximum compressive stress value (CS) in the compressive stress layer of the strengthened glass after the last, i.e., the second, ion exchange treatment be the variable. 2nd The diffusion depth (DOL) of K ions introduced through the last, i.e., the second, ion exchange treatment from the aforementioned surface. 2nd When the above explanatory variable is set as the above explanatory variable, the thickness (T) of the above tempered glass is set as the above explanatory variable, and the maximum value (CT) of the above tempered glass after the last, i.e. the second ion exchange treatment is set as the above target variable, the above regression equation may include the following equation (11).

[0053] CT = gT + hCS 1st +iDOL 1st +jCS 2nd +kDOL 2nd +l

[0054] ···(11)

[0055] Here, g ~ l is a constant.

[0056] The regression equation described above can be a polynomial equation. In this case, when the maximum compressive stress value (CS) in the compressive stress layer and the diffusion depth (DOL) of the K ions introduced through the ion exchange treatment from the surface are set as the explanatory variables, and the depth (DOC) of the compressive stress layer is set as the target variable, the regression equation can include the following equation (13).

[0057] DOC = a(CS + b) 2 +c(DOL+d) 2 +e ···(13)

[0058] Here, a to e are constants.

[0059] In this method, when the maximum compressive stress value (CS) in the compressive stress layer and the diffusion depth (DOL) of K ions introduced through the ion exchange treatment from the surface are set as the explanatory variables, and the maximum value of the tensile stress (CT) is set as the target variable, the regression equation may include the following equation (14).

[0060] CT = f(CS + g) 2 +h(DOL+i) 2 +j ···(14)

[0061] Here, f~j is a constant.

[0062] In this method, the aforementioned stress characteristics include the thickness (T) of the tempered glass, the aforementioned multiple ion exchange treatments are two ion exchange treatments, and in the two ion exchange treatments, the maximum compressive stress value (CS) in the compressive stress layer of the tempered glass involved in the first ion exchange treatment and the last ion exchange treatment before the second ion exchange treatment is selected. 1st The diffusion depth (DOL) of K ions introduced through the first ion exchange treatment from the surface described above. 1st Let ) be the explanatory variable mentioned above, and let the maximum compressive stress value (CS) in the compressive stress layer of the strengthened glass after the last, i.e., the second, ion exchange treatment be the variable. 2nd The diffusion depth (DOL) of K ions introduced through the last, i.e., the second, ion exchange treatment from the aforementioned surface. 2nd When the above explanatory variable is set as the above explanatory variable, the thickness (T) of the above tempered glass is set as the above explanatory variable, and the depth (DOC) of the above tempered glass after the last, i.e. the second ion exchange treatment is set as the above target variable, the above regression equation may include the following equation (16).

[0063] DOC = a(T + b) 2 +c(CS) 1st +d)2 +e (DOL) 1st +f) 2

[0064] +g(CS) 2nd +h) 2 +i(DOL) 2nd +j) 2 +k ···(16)

[0065] Here, a~k are constants.

[0066] In this method, the aforementioned stress characteristics include the thickness (T) of the tempered glass, the aforementioned multiple ion exchange treatments are two ion exchange treatments, and in the two ion exchange treatments, the maximum compressive stress value (CS) in the compressive stress layer of the tempered glass involved in the first ion exchange treatment and the last ion exchange treatment before the second ion exchange treatment is selected. 1st ) and the diffusion depth (DOL) of K ions introduced through the above-mentioned first ion exchange treatment from the above-mentioned surface. 1st Let ) be the explanatory variable mentioned above, and let the maximum compressive stress value (CS) in the compressive stress layer of the strengthened glass after the last, i.e., the second, ion exchange treatment be the variable. 2nd The diffusion depth (DOL) of K ions introduced through the last, i.e., the second, ion exchange treatment from the aforementioned surface. 2nd When the above explanatory variable is set as the above explanatory variable, the thickness (T) of the above tempered glass is set as the above explanatory variable, and the maximum value (CT) of the above tempered glass after the last, i.e. the second ion exchange treatment is set as the above target variable, the above regression equation may include the following equation (17).

[0067] CT = l(T + m) 2 +n(CS) 1st +o) 2 +p(DOL) 1st +q) 2

[0068] +r(CS) 2nd +s) 2 +t(DOL) 2nd +u) 2 +v ···(17)

[0069] Here, l to v are constants.

[0070] It should be noted that the constants (a to v) contained in the above equations (1) to (17) sometimes use the same notation repeatedly in individual equations, but each one represents an independent and individual constant value for each equation. The same constant notation does not represent the same value.

[0071] In this method, the regression equation may include the product of the maximum compressive stress value (CS) in the compressive stress layer and the diffusion depth (DOL) of the K ions introduced through the ion exchange treatment from the surface (CS×DOL) as the explanatory variable.

[0072] In this method, the reinforced glass of the presumed object contains Na2O and Li2O as glass components, and the compressive stress layer includes a compressive stress layer caused by K ions introduced through the ion exchange treatment and a compressive stress layer caused by Na ions introduced through the ion exchange treatment. In the sampling process, some of the stress characteristics can be measured by a surface stress meter using the optical waveguide effect, and other stress characteristics can be measured by a scattered light photoelastic stress meter.

[0073] The present invention addresses the aforementioned problems and is characterized by a method for fabricating a stress characteristic estimation model for reinforced glass, which is used to create a predictive model for estimating stress characteristics in a compressive stress layer formed through multiple ion exchange treatments. The predictive model is used to estimate other stress characteristics based on a subset of stress characteristics in the compressive stress layer. The method for fabricating the stress characteristic estimation model comprises: a sampling step of obtaining the plurality of stress characteristics in a sample reinforced glass having the compressive stress layer as training data; and a predictive model fabrication step of fabricating a predictive model representing the relationship between the subset of stress characteristics and the other stress characteristics using a computational processing device based on the training data.

[0074] Furthermore, the present invention is characterized by a stress characteristic estimation method that uses a pre-prepared prediction model to estimate the stress characteristics of tempered glass using the aforementioned stress characteristic estimation model making method. This method comprises: a measurement step of obtaining a portion of the stress characteristics of the tempered glass having the aforementioned compressive stress layer as input data to the prediction model; and an estimation step of inputting the input data obtained through the measurement step into the prediction model to obtain output data related to other stress characteristics, including the depth of compressive stress layer (DOC).

[0075] The present invention addresses the aforementioned problems and is characterized by a method for estimating the stress characteristics of tempered glass, which derives other stress characteristics from a subset of stress characteristics in a compressive stress layer formed through multiple ion exchange treatments. The method comprises: an estimation step that derives the other stress characteristics using a calculation processing apparatus capable of performing calculations based on a prediction model representing the relationship between the subset of stress characteristics and the other stress characteristics; and a measurement step that obtains the subset of stress characteristics in the tempered glass having the aforementioned compressive stress layer as input data to the prediction model, wherein the other stress characteristics include the depth of compressive stress (DOC) of the aforementioned compressive stress layer. In the estimation step, the input data obtained in the measurement step is input into the prediction model, and the calculation processing apparatus obtains output data relating to the depth of compressive stress (DOC) of the other stress characteristics.

[0076] Invention Effects

[0077] According to the present invention, the stress characteristics of tempered glass can be obtained efficiently. Attached Figure Description

[0078] Figure 1 This is a schematic diagram showing the cross-section of tempered glass.

[0079] Figure 2 It is a graph showing the stress distribution along the thickness direction of tempered glass.

[0080] Figure 3 This is a flowchart illustrating the manufacturing process of tempered glass.

[0081] Figure 4 This is a flowchart illustrating the method for estimating the stress characteristics of tempered glass.

[0082] Explanation of reference numerals in the attached figures

[0083] 1. Tempered glass

[0084] 1a Main surface of tempered glass

[0085] 1b End face of tempered glass

[0086] 2. Compressive stress layer

[0087] 3 Tensile stress layer

[0088] Maximum compressive stress value of CS compressive stress layer

[0089] Maximum tensile stress in CT

[0090] Depth of DOC compressive stress layer

[0091] S4 Sampling Process

[0092] S5 Predictive Model Production Process

[0093] S7 Measurement Procedure

[0094] S8 Estimated Process

[0095] T refers to the thickness of the tempered glass. Detailed Implementation

[0096] The following description of this specific embodiment will be based on the accompanying drawings. Figures 1 to 4 This invention relates to one embodiment of the method for estimating the stress characteristics of tempered glass.

[0097] Tempered glass 1 is an example of glass that is the object of estimation in the method for estimating the stress characteristics of tempered glass according to the present invention. For example... Figure 1 As shown, the tempered glass 1 is a plate- or sheet-like chemically strengthened glass obtained through ion exchange. The tempered glass 1 has a surface, a compressive stress layer 2, and a tensile stress layer 3.

[0098] The thickness T of the tempered glass 1 can be set arbitrarily, preferably less than 2.0 mm, more preferably less than 1.8 mm, less than 1.6 mm, less than 1.4 mm, less than 1.2 mm, less than 1.0 mm, less than 0.9 mm, less than 0.85 mm, even more preferably less than 0.8 mm, preferably more than 0.03 mm, more than 0.05 mm, more than 0.1 mm, more than 0.15 mm, more than 0.2 mm, more than 0.25 mm, more than 0.3 mm, more than 0.35 mm, more than 0.4 mm, more than 0.45 mm, more than 0.5 mm, more than 0.6 mm, and even more preferably more than 0.65 mm.

[0099] The surface of the tempered glass 1 includes a main surface 1a serving as the front and back, and an end face 1b. A compressive stress layer 2 is formed on the surface portion of the tempered glass 1, including the main surface 1a and the end face 1b. The compressive stress layer 2 includes a compressive stress layer caused by K ions introduced through ion exchange treatment, and a compressive stress layer caused by Na ions introduced through ion exchange treatment. The compressive stress layer caused by K ions is formed at a shallower location on and near the surface of the tempered glass 1. The compressive stress layer caused by Na ions is formed at a deeper location than the compressive stress layer caused by K ions. A tensile stress layer 3 is formed at a deeper location than the compressive stress layer 2.

[0100] The stress profile of the tempered glass 1 is obtained by measuring the stress along the depth direction (orthogonal to the main surface 1a) from the main surface 1a side, with compressive stress as positive and tensile stress as negative, using compressive stress as positive and tensile stress as negative. The stress profile of the tempered glass 1 thus obtained is as follows: Figure 2 As shown. Figure 2In the chart, the vertical axis represents stress, and the horizontal axis represents the position (depth) in the thickness direction relative to a main surface 1a. Figure 2 In the chart, positive stress values ​​represent compressive stress, and negative stress values ​​represent tensile stress. That is, Figure 2 In the chart, a larger absolute value of the stress indicates a greater stress. It should be noted that... Figure 2 This is an exaggerated diagram for the purpose of understanding; the stress distribution of the reinforced glass 1 is not limited to this scheme.

[0101] The stress distribution of the tempered glass 1, along the depth direction (orthogonal to the main surface 1a), has a first peak P1, a first valley B1, a second peak P2, and a second valley B2.

[0102] The first peak P1 is the location where the maximum compressive stress is found on the main surface 1a. The compressive stress CS of the first peak P1 is 500 MPa or more, preferably 700 MPa to 900 MPa, and more preferably 750 MPa to 850 MPa.

[0103] The stress decreases along the depth direction from the first peak P1, reaching a minimum at the first valley B1. The stress CSb at the first valley B1 is... Figure 2 The example shows the case of compressive stress (positive value), but there are also cases where tensile stress (negative value) is taken. The lower the stress CSb of valley 1 B1, the lower the tensile stress CT of valley 2 B2, which slows down the failure process.

[0104] The stress CSb at the first valley B1 is preferably +100 MPa or less, more preferably +90 MPa or less, +80 MPa or less, +70 MPa or less, or +60 MPa or less. However, if the stress CSb at the first valley B1 is too low, surface cracks will form during the strengthening process, resulting in decreased visibility. The stress CSb at the first valley B1 is preferably -50 MPa or more, more preferably -45 MPa or more, -40 MPa or more, -35 MPa or more, or -30 MPa or more. The stress CSb at the first valley B1 can be 0 MPa or more and +65 MPa or less, or -30 MPa or more and less than 0 MPa. The depth DOLb of the first valley B1 is preferably 0.5% to 12% of the thickness T, more preferably 1% to 7% of the thickness T. The depth DOLb of Valley 1 B1 is approximately the same as, or slightly deeper than, the depth of the compressive stress layer 2 caused by K ions, i.e., the diffusion depth of K ions introduced through ion exchange, DOL. More specifically, DOLb lies within ±10 μm of DOL.

[0105] The stress increases along the depth direction from the first valley B1, reaching its maximum value at the second peak P2. The stress CSp at the second peak P2 is the compressive stress. The compressive stress CSp at the second peak P2 is 15MPa to 250MPa, preferably 15MPa to 240MPa, 15MPa to 230MPa, 15MPa to 220MPa, 15MPa to 210MPa, 15MPa to 200MPa, 15MPa to 190MPa, 15MPa to 180MPa, 15MPa to 175MPa, 15MPa to 170MPa, 15MPa to 165MPa, 15MPa to 160MPa, 18MPa to 100MPa, and more preferably 20MPa to 80MPa.

[0106] The depth DOLp of the second peak P2 is 4% to 20% of the thickness T, preferably 4% to 19%, 4% to 18.5%, 4% to 18%, 4% to 17.5%, or 4% to 17% of the thickness T, and more preferably 4.5% to 17%, 5% to 17%, 6% to 17%, 7.3% to 17%, or 8% to 15% of the thickness T.

[0107] The distance in the depth direction from the first valley B1 to the second peak P2, i.e., DOLp-DOLb, is 3% or more of the thickness T, preferably 4% or more of the thickness T, and more preferably 5% to 13% of the thickness T.

[0108] The stress decreases from the second peak P2 along the depth direction, and the minimum tensile stress (the absolute value is the maximum value) is reached at the second valley B2. The absolute value (maximum value) of the tensile stress CT at the second valley B2 at the central position in the thickness direction of the tempered glass 1 is 70 MPa or less, preferably 65 MPa or less, 60 MPa or less, and more preferably 40 MPa to 55 MPa.

[0109] The product of the tensile stress CT and the thickness T of the second valley B2 is preferably -70 MPa·mm or more, more preferably -65 MPa·mm or more, -60 MPa·mm or more, or -55 MPa·mm or more. Furthermore, the product of the tensile stress CT and the thickness T of the second valley B2 is preferably -5 MPa·mm or less, -10 MPa·mm or less, -15 MPa·mm or less, -20 MPa·mm or less, -25 MPa·mm or less, or -30 MPa·mm or less.

[0110] Between the second peak P2 and the second valley B2, there is a stress zero point Z where the stress is zero. Typically, the depth of the stress zero point Z, i.e., the depth DOC of the compressive stress layer 2, is unlikely to exceed 20% of the thickness T, and physically around 22% is also a limit. However, in this embodiment, a DOC exceeding this limit value can be obtained.

[0111] The greater the depth DOC of the zero stress point Z, the higher the strength to withstand protrusion penetration. Preferably, it is 10% or more, 10.5% or more, 11% or more, 11.5% or more, 12% or more, 12.5% ​​or more, 13% or more, 13.5% or more, 14% or more, 14.5% or more, 15% or more, 15.5% or more, 16% or more, 16.5% or more, 17% or more, 17.5% or more, 18% or more, more preferably 18.5% or more, 19% or more, 19.5% or more, 20% or more, 20.5% or more, 21% or more, 21.5% or more, 22.0% or more, 22.5% or more, 23% or more, 23.5% or more, and most preferably 24% or more.

[0112] However, if the depth DOC of the zero stress point Z becomes excessively large, excessive tensile stress may be generated in the first valley B1 and the second valley B2. Therefore, the depth DOC of the zero stress point Z is preferably 35% or less, 34.5% or less, 34% or less, 33.5% or less, 33% or less, 32.5% or less, 32% or less, 31.5% or less, 31% or less, 30.5% or less, 30% or less, 29.5% or less, 29% or less, 28.5% or less, or 28% or less of the thickness T, more preferably 27% or less.

[0113] In this embodiment, the tempered glass 1 also has the same stress distribution on the end face 1b. Specifically, the stress distribution of the tempered glass 1 includes: a first peak where the compressive stress is at its maximum value at the end face 1b; a first valley where the stress decreases along the depth direction from the first peak to a minimum value; a second peak where the compressive stress increases along the depth direction from the first valley to a maximum value; and a second valley where the tensile stress decreases along the depth direction from the second peak to a minimum value. The compressive stress at the first peak is 500 MPa or more, and the compressive stress at the second peak is 15 MPa to 250 MPa. The second peak exists at a depth of 4% to 20% of the thickness T. Furthermore, the preferred range of the stress distribution related to the end face 1b can also be applied in the same way to the preferred range of the stress distribution related to the main surface 1a.

[0114] It should be noted that the stress and its distribution of the reinforced glass 1 can be measured and synthesized using, for example, a surface stress gauge (FSM-6000LE) and a diffused light photoelastic stress gauge (SLP-1000) manufactured by Orihara Manufacturing Co., Ltd.

[0115] The tempered glass 1 constructed in the above manner is manufactured by the following method: preparing a plate-shaped glass (hereinafter referred to as tempered glass) containing alkali metal oxides as its composition, and subjecting the tempered glass to a tempering treatment.

[0116] The glass for strengthening is preferably composed of, by mass percent, 40%–70% SiO2, 10%–30% Al2O3, 0%–3% B2O3, 5%–25% Na2O, 0%–5.5% K2O, 0.1%–10% Li2O, 0%–6% MgO and 0%–15% P2O5.

[0117] It should be noted that the composition of the strengthening glass described above is an example. If chemical strengthening based on ion exchange can be achieved, strengthening glass with a known composition can be used. Furthermore, the strengthening glass obtained by ion-exchange treatment of the above-mentioned strengthening glass has the same composition as the strengthening glass before ion-exchange treatment.

[0118] The method for manufacturing the tempered glass 1 (tempered glass sheet) with the above-described structure will be described below.

[0119] like Figure 3 As shown, this method includes a preparation step S1, a first ion exchange step S21, and a second ion exchange step S22.

[0120] Preparation step S1 is the process of preparing glass for strengthening. In preparation step S1, glass raw materials that are blended in the manner described above are put into a continuous melting furnace, heated and melted at 1500°C to 1600°C, clarified, and then fed to a forming device to be formed into a plate or the like, and then annealed, thereby producing glass for strengthening.

[0121] As a method for forming glass sheets, the overflow pull-down method is preferred. The overflow pull-down method is capable of producing high-quality glass sheets in large quantities and can also easily produce large glass sheets, while minimizing surface damage to the glass sheets. It should be noted that, in the overflow pull-down method, alumina and zircon are used as constituent materials of the formed body. The strengthening glass of this invention exhibits good compatibility with alumina and zircon, especially with alumina (the components of the molten glass are unlikely to react with the components of the formed body, making it difficult to generate bubbles, pitting, etc.).

[0122] Besides the overflow pull-down method, various other forming methods can be used. For example, forming methods such as float forming, pull-down forming (slit pull-down forming, re-pulling forming, etc.), roll forming, and extrusion forming can be used.

[0123] After the glass is formed and strengthened, or simultaneously with the forming process, it can be bent as needed. Additionally, it can be cut, drilled, surface ground, chamfered, end-face ground, etched, and other processes can be performed as required.

[0124] The dimensions of the reinforced glass can be set arbitrarily, but the thickness T is preferably 2.0 mm or less, more preferably 0.05 to 1.0 mm, and even more preferably 0.1 mm to 0.9 mm, 0.3 mm to 0.85 mm, or 0.5 mm to 0.8 mm.

[0125] In the first ion exchange step S21, the strengthening glass is immersed (contacted) in a treatment tank filled with a first molten salt containing Na ions and held at a specified temperature for a specified time, thereby performing ion exchange treatment on the surface of the strengthening glass. This process involves the exchange of Li ions in the strengthening glass with Na ions in the first molten salt, introducing Na ions into the vicinity of the surface (main surface and end face) of the strengthening glass. Furthermore, the Na ions in the strengthening glass are exchanged with K ions in the first molten salt. As a result, a compressive stress layer 2 is formed on the surface of the strengthening glass, thus strengthening the glass.

[0126] In the first ion exchange step S21, the region where Na ions are introduced into the strengthening glass is preferably the region of the strengthening glass extending from the surface to a depth of 10% or more of the thickness T, and more preferably the region of the strengthening glass extending from the surface to a depth of 12% or more, 14% or more, 15% or more, or 15% or more and 40% or less of the thickness T.

[0127] The first molten salt used in the first ion exchange step S21 is preferably a mixture of NaNO3 and KNO3. If the first molten salt contains K ions, the compressive stress and its distribution on the surface of the strengthened glass can be easily measured after the first ion exchange step S21, thus facilitating quality management of the obtained strengthened glass. The concentration of NaNO3 in the first molten salt is preferably higher than the concentration of KNO3 in the first molten salt, but this relationship is not limited to. Preferably, the concentration of NaNO3 in the first molten salt is 50% or more by mass, and the concentration of KNO3 in the first molten salt is less than 50% by mass. However, it is not limited to this; preferably, the concentration of NaNO3 in the first molten salt is 100–20%, 100–30%, 100–40%, 100–50%, or 100–60% by mass, with the balance being KNO3. When the first molten salt is a mixture of NaNO3 and KNO3, Na ions diffuse more easily in the tempered glass than K ions, and are therefore introduced into regions deeper than the surface of the tempered glass. It should be noted that the first molten salt can be configured to contain only NaNO3 and no KNO3. Alternatively, the first molten salt can contain LiNO3.

[0128] The ion exchange treatment temperature of the first ion exchange step S21 is preferably 350–480°C, more preferably 360–430°C, and even more preferably 370–400°C or 370–390°C. The ion exchange treatment time of the first ion exchange step S21 is preferably 1–20 hours, more preferably 1.5–15 hours, and even more preferably 2–10 hours.

[0129] In the second ion exchange step S22, the strengthening glass is immersed in a treatment tank filled with a second molten salt containing K ions and Li ions, and held at a specified temperature for a specified time, thereby performing ion exchange treatment on the surface of the strengthening glass.

[0130] Therefore, Li ions in the second molten salt undergo a reverse ion exchange with Na ions in the strengthening glass, causing at least a portion of the Na ions to detach from the strengthening glass. Simultaneously, K ions undergo an ion exchange with either Li or Na ions contained in the strengthening glass, introducing K ions into the strengthening glass from the surface down to a region shallower than 7% of its thickness T. In other words, the compressive stress formed in the surface portion of the strengthening glass is mitigated through reverse ion exchange, and the strengthening glass is strengthened through ion exchange, with high compressive stress only forming near the surface in the surface portion.

[0131] In the second ion exchange step S22, the region where Na ions are removed from the strengthening glass is preferably a region extending from the surface of the strengthening glass to a depth of 15% or less of its thickness T, more preferably a region extending from the surface of the strengthening glass to a depth of 14% or less, 13% or less, 12% or less, 11% or less, 10% or less, 1% or more and 10% or less, 2% or more and 10% or less, 3% or more and 10% or less, 4% or more and 10% or less, or 5% or more and 10% or less of its thickness T. Furthermore, in the second ion exchange step S22, the region where K ions are introduced into the strengthening glass is preferably a region extending from the surface of the strengthening glass to a depth of 7% or less of its thickness T, more preferably a region extending from the surface of the strengthening glass to a depth of 6.5% or less, 6% or less, 5.5% or less, or 5% or less of its thickness T.

[0132] The second molten salt used in the second ion exchange step S22 is preferably a mixed salt of LiNO3 and KNO3. The concentration of LiNO3 in the second molten salt is preferably lower than the concentration of KNO3. Specifically, the concentration of LiNO3 in the second molten salt, in mass %, is preferably 0.1–5%, 0.2–5%, 0.3–5%, 0.4–5%, 0.5–5%, 0.5–4%, 0.5–3%, 0.5–2.5%, 0.5–2%, or 1–2%. The concentration of KNO3 in the second molten salt, in mass %, is preferably 95–99.5%, 96–99.5%, 97–99.5%, 98–99.5%, 98–99.4%, 98–99.3%, 98–99.2%, 98–99.1%, or 98–99%.

[0133] Furthermore, the concentration of Li ions in the second molten salt is preferably 100 ppm by mass or more. In this case, the concentration of Li ions in the second molten salt is obtained by multiplying the LiNO3 expressed as % by 0.101.

[0134] The ion exchange treatment temperature in the second ion exchange step S22 is preferably 350–480°C, more preferably 360–430°C, and even more preferably 370–400°C or 370–390°C. The ion exchange treatment time in the second ion exchange step S22 is preferably shorter than the ion exchange treatment time in the first ion exchange step S21. The ion exchange treatment time in the second ion exchange step S22 is preferably 0.2 hours or more, more preferably 0.3–2 hours or 0.4–1.5 hours, and even more preferably 0.5–1 hour.

[0135] The strengthening glass impregnated with molten salt in each ion exchange process S21 and S22 can be preheated to the temperature of the molten salt in the ion exchange process S21 and S22, or it can be impregnated with each molten salt at room temperature (e.g., 1℃ to 40℃).

[0136] Preferably, a cleaning step for cleaning the strengthening glass extracted from the molten salt is provided between the first ion exchange step S21 and the second ion exchange step S22. By cleaning, the deposits adhering to the strengthening glass are easily removed, and the ion exchange treatment can be performed more uniformly in the second ion exchange step S22.

[0137] Next, the method for estimating the stress characteristics of the tempered glass 1 will be described. The method for estimating the stress characteristics of tempered glass according to the present invention can estimate other stress characteristics based on a prediction model from among the multiple stress characteristics of tempered glass 1 having a compressive stress layer 2 on the surface through multiple (two times in the above example) ion exchange treatments.

[0138] like Figure 4 As shown, this method is broadly divided into a model generation stage and a model utilization stage. For the model generation stage, once the predictive model is obtained, it can be performed only when updates are needed, such as when manufacturing conditions like glass composition or ion exchange conditions change. On the other hand, the model utilization stage can be performed repeatedly for quality management purposes, such as in the manufacturing process of tempered glass products.

[0139] In the model generation stage, a sample reinforced glass is produced by performing ion exchange treatment under the same ion exchange conditions as the reinforced glass that is the presumed object, using the same size, shape, and composition of the reinforced glass.

[0140] The model generation stage includes sample glass preparation step S3, sampling step S4, and prediction model fabrication step S5.

[0141] In the sample glass preparation process S3, multiple strengthening glasses are prepared for making sample strengthening glass.

[0142] Sampling procedure S4 includes multiple (N times: N is an integer greater than 2) ion exchange procedures S20-1 to S20-N for strengthening glass, and the first sampling procedure S4-1 to the final sampling procedure S4-N for measuring the stress characteristics of the sample strengthened glass after each ion exchange procedure S20-1 to S20-N.

[0143] In each sampling step S4-1 to S4-N, after each ion exchange step S20-1 to S20-N, multiple stress characteristics of the sample tempered glass are obtained as training data. That is, multiple stress characteristics of the sample tempered glass after the first ion exchange step S20-1 are obtained through the first sampling step S4-1 as the first training data. Further, after performing the second ion exchange step S20-2 on the sample tempered glass, its stress characteristics are obtained through the second sampling step S4-2 as the second training data. This sampling is repeated, and the stress characteristics of the sample tempered glass after the final, i.e., the Nth, ion exchange step S20-N are obtained through the final sampling step S4-N as the final training data.

[0144] The number of ion exchange processes and sampling times in sampling step S4 is set to the same number of ion exchange processes used in the utilization stage to produce the tempered glass for the presumed object. That is, if the tempered glass for the presumed object is produced by two ion exchange processes, the sample tempered glass is also produced by two ion exchange processes (first ion exchange process S20-1 and second ion exchange process S20-2) in sampling step S4. In this case, two sampling processes (first sampling process S4-1 and second sampling process S4-2) are performed in a manner corresponding to each ion exchange process to obtain the first training data and the final training data, i.e., the second training data.

[0145] Examples of stress characteristics included in the training data include CS, DOL, DOC, CT, CS80, and the thickness T of the tempered glass. Here, CS80 is the compressive stress value at a depth of 80 μm from the main surface of the tempered glass sample. It should be noted that the training data is preferably used after pre-conversion of the same physical quantities in a common unit manner. For example, data regarding length (depth), such as T, DOL, and DOC, are preferably converted to μm before use.

[0146] Of these stress characteristics, CS and DOL were measured using, for example, a surface stress gauge (FSM-6000LE) manufactured by Orihara Corporation. The FSM-6000LE can measure these stress characteristics using the optical waveguide effect. Additionally, DOC, CT, and CS80 were measured using, for example, a light-scattering photoelastic stress gauge (SLP-1000) manufactured by Orihara Corporation. Thickness T can be measured after the final ion exchange process using, for example, a micrometer, a laser displacement gauge, or other measuring devices.

[0147] The measured training data is recorded on a recording medium or stored in a computational processing device capable of performing the predictive model creation step S5.

[0148] In the prediction model creation step S5, a prediction model for predicting stress characteristics is created using a computational processing device. This prediction model predicts stress characteristics based on training data obtained through the sampling step S4. In the prediction model creation step S5, some or all of the training data obtained through the sampling step S4 is used. If only a portion of the training data is used, for example, first training data and final training data can be used. Alternatively, only the final training data can be used. It is not limited to this; other training data can also be added to the first and final training data to create the prediction model.

[0149] Commercially available computers can be used as the computational processing device. The computational processing device contains statistical analysis software. The device can generate regression equations as predictive models through regression analysis using the statistical analysis software. Suitable statistical analysis software includes, for example, JMP (registered trademark) manufactured by SAS Institute Inc.

[0150] In the predictive model creation step S5, among the multiple stress characteristics included in the training data related to stress characteristics, some stress characteristics are used as explanatory variables, while others are used as target variables. Specifically, CS, DOL, and / or T can be used as explanatory variables, while DOC, CT, and CS80 can be used as target variables.

[0151] The regression equation for the prediction model is, for example, expressed by least squares as a first-order function (first-order equation) based on the variables mentioned above. For example, the regression equation made solely based on the final training data is represented by the following (1) to (3).

[0152] DOC=aCS+bDOL+c···(1)

[0153] CT=dCS+eDOL+f···(2)

[0154] CS80=gCS+hDOL+i···(3)

[0155] Here, a to i are positive or negative constants (the same applies below).

[0156] As another implementation method, the regression equation can be represented by the following equations (4) to (6).

[0157] DOC=aT+bCS+cDOL+d···(4)

[0158] CT=eT+fCS+gDOL+h···(5)

[0159] CS80=iT+jCS+kDOL+l···(6)

[0160] Here, j~l are positive or negative constants (the same applies below).

[0161] As another implementation, for example, in the case of two ion exchange treatments, the regression equation based on the first training data and the final training data (the second training data) is represented by, for example, the following equations (7) to (9).

[0162] DOC = aCS 1st +bDOL 1st +cCS 2nd +dDOL 2nd +e

[0163] ···(7)

[0164] CT = fCS 1st +gDOL 1st +hCS 2nd +iDOL 2nd +j

[0165] ···(8)

[0166] CS80 = kCS 1st +lDOL 1st +mCS 2nd +nDOL 2nd +o

[0167] ···(9)

[0168] Here, m~o is a positive or negative constant (the same applies below).

[0169] In equations (7) to (9) above, CS 1st CS is obtained after the first ion exchange treatment (first ion exchange step S20-1). 2nd The CS (same below) was measured after the final ion exchange treatment (second ion exchange step). DOL 1st DOL was measured after the first ion exchange treatment (first ion exchange step S20-1). 2nd DOL was measured after the final ion exchange treatment (second ion exchange step) (the same applies below).

[0170] In other implementations, the regression equation can be represented by the following equations (10) to (12).

[0171] DOC = aT + bCS 1st +cDOL 1st +dCS 2nd +eDOL 2nd +f

[0172] ···(10)

[0173] CT = gT + hCS 1st +iDOL 1st +jCS 2nd +kDOL 2nd +l

[0174] ···(11)

[0175] CS80 = mT + nCS 1st +oDOL 1st +pCS 2nd +qDOL2nd +r

[0176] ···(12)

[0177] Here, p ~ r are positive or negative constants (the same applies below).

[0178] In other implementations, the regression equation can be represented as a multinomial function (multinomial equation). For example, a quadratic regression equation based solely on the final training data is represented by the following equations (13) to (15).

[0179] DOC = a(CS + b) 2 +c(DOL+d) 2 +e ···(13)

[0180] CT = f(CS + g) 2 +h(DOL+i) 2 +j ···(14)

[0181] CS80 = k(CS + l) 2 +m(DOL+n) 2 +o ···(15)

[0182] In other implementations, the regression equation (quadratic equation) can be represented by the following equations (16) to (18).

[0183] DOC = a(T + b) 2 +c(CS) 1st +d) 2 +e (DOL) 1st +f) 2

[0184] +g(CS) 2nd +h) 2 +i(DOL) 2nd +j) 2 +k ···(16)

[0185] CT = l(T + m) 2 +n(CS) 1st +o) 2 +p(DOL) 1st +q) 2

[0186] +r(CS) 2nd +s) 2 +t(DOL) 2nd +u) 2 +v ···(17)

[0187] CS80 = w(T + x) 2 +y(CS)1st +z) 2 +α(DOL) 1st +β) 2

[0188] +γ(CS) 2nd +δ) 2 +ε(DOL) 2nd +ζ) 2 +η ···(18)

[0189] Here, s~z and α~η are positive or negative constants.

[0190] It should be noted that the constants (a~z, α~η) contained in the above equations (1) to (18) sometimes use the same notation repeatedly in individual equations, but they all represent individual constant values ​​obtained independently according to each equation. The same constant notation does not represent the same value.

[0191] Besides the examples above, the regression equations involved in predictive models can be quadratic equations (multiplication equations) that include product terms of variables related to stress characteristics as explanatory variables. For example, a product term could be T×CS. 1st T×DOL 1st T×CS 2nd T×DOL 2nd CS 1st ×DOL 1st CS 1st ×CS 2nd CS 1st ×DOL 2nd DOL 1st ×CS 2nd DOL 1st ×DOL 2nd CS 2nd ×DOL 2nd .

[0192] In the prediction model creation process S5, the appropriateness of the prediction model created by the calculation and processing device is verified (verification process). Specifically, the DOC (DOC) measured in the sampling process S4 is verified. 1st DOC 2nd ), CS (CS) 1st CS 2nd ), CS80 (CS80) 1st CS80 2nd The data involved is compared with the data calculated through the prediction model. In the verification process, the coefficient of determination (R²) is used... 2The root mean square error (RMSE) verifies the suitability of the predictive model. Here, the coefficient of determination represents the proportion of the total variation in the target variable that can be explained by all explanatory variables; it indicates the goodness of fit between the regression equation and the training data. A coefficient of determination closer to 1 is better.

[0193] In the model utilization phase, the glass to be strengthened is subjected to multiple ion exchange treatments to produce strengthened glass that serves as the presupposition. In this case, after each ion exchange treatment, a portion of the stress characteristics of the strengthened glass is measured, and based on the prediction model produced in the prediction model production step S5, other stress characteristics are inferred from a portion of its stress characteristics.

[0194] like Figure 4 As shown, the model utilization stage includes the glass preparation process S6, the measurement process S7, and the estimation process S8.

[0195] In the glass preparation process S6 for the presumed object, multiple strengthening glasses are prepared for making the strengthening glass for the presumed object.

[0196] Measurement step S7 includes multiple (N times: N is an integer greater than or equal to 2) ion exchange steps S200-1 to S200-N, and multiple (N times) measurement steps S7-1 to S7-N performed after each ion exchange step S200-1 to S200-N. In measurement step S7, after each ion exchange step S200-1 to S200-N, a portion of the stress characteristics involved in the tempered glass is measured, and the measured stress characteristics are used as input data to the prediction model. For example, a portion of the stress characteristics involved in the tempered glass after the first ion exchange step S200-1 is measured through the first measurement step S7-1. The data related to the portion of stress characteristics measured in the first measurement step S7-1 becomes the first input data to the prediction model. In the case of the second ion exchange step S200-2, a portion of the stress characteristics involved in the subsequent tempered glass is measured through the second measurement step S7-2 to obtain the second input data. This measurement was repeated, and a portion of the stress characteristics of the strengthened glass after the final ion exchange process S200-N was measured through the final measurement process S7-N to obtain the final input data.

[0197] The following description will explain the measurement process S7 and the estimation process S8 when the strengthened glass, which is the presumed object, is produced through two ion exchange processes. In this case, the second measurement process becomes the final measurement process.

[0198] In the first measurement step S7-1, after the first ion exchange treatment, i.e., the first ion exchange step S200-1 (and before the second ion exchange step), the surface stress (CS) of the tempered glass of the presumed object is measured using a surface stress meter (FSM-6000LE) manufactured by, for example, Orihara Corporation. 1st DOL 1st This serves as the first input data for the prediction model.

[0199] In the final measurement process, after the last ion exchange treatment, i.e., the second ion exchange process, the surface stress (CS) of the tempered glass of the presumed object is measured using a surface stress meter (FSM-6000LE) manufactured by, for example, Orihara Corporation. 2nd DOOL 2nd As the final input data for the prediction model.

[0200] When T is used as a variable in the prediction model, the thickness of the tempered glass, which is the object of estimation, is measured after the second ion exchange process (the final ion exchange process) using measuring devices such as micrometers, laser displacement meters, or other measuring instruments. The measured data is sent or input to a calculation processing device capable of performing the estimation process S8.

[0201] In the estimation step S8, the input data related to the stress characteristics measured in the measurement step S7 are imported into the prediction model. As the calculation processing device for performing the estimation step S8, a computer with the aforementioned prediction model pre-installed and capable of performing regression equation-based calculations is used. That is, as the calculation processing device, the prediction model can be installed and used on a different computer than the computer that performed the prediction model creation step S5. Alternatively, the computer that performed the prediction model creation step S5 can be used as the calculation processing device. The calculation processing device processes the first input data (CS) measured in the measurement step S7. 1st DOL 1st ) and final input data (CS) 2nd DOL 2nd Based on the T input prediction model determined by the situation, the output data (DOS, CT, CS80) involved in other stress characteristics are calculated.

[0202] According to the stress characteristic estimation method for tempered glass described above in this embodiment, among the multiple stress characteristics (CS, DOL, DOC, CT, CS80, T) involved in the tempered glass to be estimated, a portion of the stress characteristics (CS, DOL, and / or T) are measured. The obtained input data is then input into the prediction model in the estimation step S8, thereby enabling the high-precision estimation of other stress characteristics (DOC, CT, CS80). This significantly reduces the operation time when measuring the stress characteristics of a large number of tempered glasses. Therefore, it allows for efficient strength checks and strength analysis of a large number of tempered glasses. Furthermore, it eliminates the need to install multiple measuring devices in the tempered glass manufacturing process, reducing equipment costs.

[0203] It should be noted that the present invention is not limited to the configuration of the above-described embodiments, nor to the effects described above. Various modifications can be made to the present invention without departing from its spirit.

[0204] The above embodiments illustrate a predictive model creation step S5 that uses DOS, CT, and CS80 as target variables for regression analysis, but the present invention is not limited to this configuration. It is not limited to CS80 (the stress value at a depth of 80 μm from the surface of the tempered glass), and can create a predictive model using stress values ​​at any depth and that depth as target variables (e.g., the stress value CSP of the second peak P2 in the stress distribution and its depth DOLp, etc.).

[0205] The above embodiments illustrate an example of creating a predictive model using regression analysis, but the present invention is not limited to this approach. Predictive models can be created using other machine learning (deep learning) techniques.

[0206] In the above embodiments, each process can be performed by different practitioners or by a single practitioner. For example, the processes in the model making stage (steps S3 to S5) and the processes in the model utilization stage (steps S6 to S8) can be performed by different practitioners.

[0207] Example

[0208] The tempered glass of the present invention will now be described based on embodiments. It should be noted that the following embodiments are merely illustrative and the present invention is not limited to any of them.

[0209] The sample was prepared as follows. First, a strengthening glass plate for ion exchange treatment was prepared. The strengthening glass plate contained, by mass%, 51.6% SiO2, 27.9% Al2O3, 0.3% B2O3, 0.6% K2O, 7.5% Na2O, 3.3% Li2O, 0.3% MgO, 8.4% P2O5, and 0.1% SnO2 as its glass composition.

[0210] The glass raw materials were blended according to the above composition and melted in a platinum kettle at 1600°C for 21 hours. The resulting molten glass was then poured from a refractory molding body using an overflow-pull method. The resulting glass strip was cut to specified dimensions to obtain multiple strengthening glass plates for use as test pieces. Glass plates of different thicknesses were prepared as strengthening glass plates. The thicknesses of the strengthening glass plates were 0.55 mm, 0.7 mm, and 0.8 mm.

[0211] Next, the aforementioned strengthening glass is immersed in a molten salt bath and subjected to ion exchange treatment based on the first ion exchange step and the second ion exchange step to obtain a strengthened glass plate.

[0212] In the first ion exchange process, for the chemical strengthening of a 0.55 mm thick tempered glass plate, a molten salt with a KNO3 to NaNO3 weight concentration ratio of 70%:30% is used. For the chemical strengthening of 0.7 mm and 0.8 mm thick tempered glass plates, a molten salt with a KNO3 to NaNO3 weight concentration ratio of 40%:60% is used.

[0213] The ion exchange treatment temperature of the molten salt in the first ion exchange process is 380℃. For a 0.55mm thick tempered glass plate, the ion exchange treatment time in the first ion exchange process is set to 90 minutes or 120 minutes. For a 0.7mm thick tempered glass plate, the ion exchange treatment time in the first ion exchange process is set to 180 minutes. For a 0.8mm thick tempered glass plate, the ion exchange treatment time in the first ion exchange process is set to 210 minutes.

[0214] In the second ion exchange step, the weight concentration ratio of KNO3 to LiNO3 in the molten salt is set to 99%:1%. The ion exchange treatment temperature of the molten salt in the second ion exchange step is 380℃. The ion exchange treatment time in the second ion exchange step is 45 minutes.

[0215] As Example 1, in order to generate the regression equations (4) to (6) in the above embodiments, the stress characteristics CS, DOL, CT, CS80, and T of the strengthened glass plate after the second ion exchange process were measured. For the measurement of stress characteristics, a surface stress gauge (FSM-6000LE) and a scattered light photoelastic stress gauge (SLP-1000) manufactured by Orihara Manufacturing Co., Ltd. were used. Using the measured data as the final training data, the statistical analysis software JMP (registered trademark) was used to generate a prediction model corresponding to the regression equations (4) to (6) in the above embodiments based solely on the final training data using a computational processing device.

[0216] The measured CS and DOL are input into the constructed regression equation, and the output (estimated) DOC, CT, and CS80 are compared with the measured DOC, CT, and CS80. Based on the estimated and measured values ​​of the stress characteristics, the coefficient of determination (R²) is calculated. 2 ) and root mean square error (RMSE).

[0217] As Example 2, in order to create a prediction model corresponding to the regression equations (10) to (12) in the above embodiments, the necessary training data (first training data and final training data) related to the stress characteristics were obtained using the same method as in Example 1. Using the same method as in Example 1, a prediction model corresponding to the regression equations (10) to (12) in the above embodiments was created based on the obtained training data. Then, similarly to Example 1, the coefficient of determination (R²) was calculated based on the estimated and measured values ​​of the stress characteristics. 2 ) and root mean square error (RMSE).

[0218] As Example 3, a prediction model corresponding to the regression equations (16) to (18) in the above embodiments was created using the same method as in Example 1. Then, similarly to Example 1, the coefficient of determination (R²) was calculated based on the estimated and measured values ​​of the stress characteristics. 2 ) and root mean square error (RMSE).

[0219] As Example 4, a predictive model is created by adding the product terms of each variable to the regression equations (7) to (9) in the above embodiments, using the same method as in Example 1. The added product term is T×CS. 1st T×DOL 1st T×CS 2nd T×DOL 2nd CS 1st ×DOL 1st CS 1st ×CS 2nd CS 1st ×DOL 2nd DOL 1st ×CS2nd DOL 1st ×DOL 2nd CS 2nd ×DOL 2nd Subsequently, similar to Example 1, the coefficient of determination (R²) was calculated based on the estimated and measured values ​​of the stress characteristics. 2 ) and root mean square error (RMSE).

[0220] The verification results of Examples 1 to 4 are shown in Tables 1 and 2.

[0221] Table 1

[0222]

[0223] Table 2

[0224]

[0225] As shown in Tables 1 and 2, the stress characteristics estimated by the prediction model show a high correlation with the actual measured stress characteristics. Therefore, this invention enables the estimation of stress characteristics (DOC, CT, CS80) with high accuracy.

Claims

1. A method for estimating the stress characteristics of tempered glass, characterized in that, This is a method for estimating the stress characteristics of strengthened glass, which involves inferring other stress characteristics based on a subset of stress characteristics within a compressive stress layer formed through multiple ion exchange treatments. The method comprises the following steps: The sampling process obtains the multiple stress characteristics in the sample reinforced glass having the compressive stress layer as training data. The prediction model creation process involves using the training data to create a prediction model representing the relationship between a subset of stress characteristics and the other stress characteristics through a computational processing device. The measurement process obtains a portion of the stress characteristics of the reinforced glass of the presumed object having the compressive stress layer, which is used as input data for the prediction model. and The estimation process involves inputting the input data obtained through the measurement process into the prediction model, and then using the calculation processing device to obtain the output data related to the other stress characteristics. The other stress characteristics include the depth of the compressive stress layer (DOC).

2. The method for estimating the stress characteristics of tempered glass according to claim 1, wherein, The tempered glass of the presumed object and the tempered glass of the sample are plate-shaped or sheet-shaped with surfaces. The stress characteristics include the diffusion depth DOL of the K ions introduced through the ion exchange treatment from the surface.

3. The method for estimating the stress characteristics of tempered glass according to claim 2, wherein, The tempered glass has a tensile stress layer at the center position in the thickness direction of the tempered glass. The aforementioned stress characteristics include the maximum compressive stress value CS in the compressive stress layer. The other stress characteristics include the maximum value CT of the tensile stress in the tensile stress layer.

4. The method for estimating the stress characteristics of tempered glass according to claim 3, wherein, The sampling process includes: The first sampling step involves obtaining the multiple stress characteristics of the strengthened glass sample after the first ion exchange treatment in the multiple ion exchange processes as first training data; and The final sampling process obtains the stress characteristics of the strengthened glass sample after the final ion exchange treatment in the multiple ion exchange processes as the final training data. In the prediction model creation process, the prediction model is created based on the first training data and the final training data. The measurement process includes: The first measurement step involves obtaining a portion of the stress characteristics of the reinforced glass of the presumed object after the first ion exchange treatment in the multiple ion exchange treatments, as the first input data for the prediction model; and The final measurement process involves obtaining a portion of the stress characteristics of the tempered glass of the presumed object after the final ion exchange treatment in the multiple ion exchange processes, which serves as the final input data for the prediction model. In the estimation process, the first input data and the final input data obtained through the measurement process are input into the prediction model to obtain the output data related to the other stress characteristics.

5. The method for estimating the stress characteristics of tempered glass according to claim 4, wherein, The multiple ion exchange treatments refer to two ion exchange treatments.

6. The method for estimating the stress characteristics of tempered glass according to claim 3, wherein, In the estimation process, a portion of the stress characteristics are used as explanatory variables, and the other stress characteristics are used as target variables for regression analysis, thereby obtaining the regression equation and its constants for the prediction model.

7. The method for estimating the stress characteristics of tempered glass according to claim 6, wherein, The regression equation is a linear equation.

8. The method for estimating the stress characteristics of tempered glass according to claim 7, wherein, When the maximum compressive stress value CS in the compressive stress layer and the diffusion depth DOL of K ions introduced through the ion exchange treatment from the surface are set as the explanatory variables, and the depth DOC of the compressive stress layer is set as the target variable, The regression equation includes the following equation (1). DOC=aCS+bDOL+c···(1) Here, a to c are constants.

9. The method for estimating the stress characteristics of tempered glass according to claim 7 or 8, wherein, When the maximum compressive stress value CS in the compressive stress layer and the diffusion depth DOL of K ions introduced through the ion exchange treatment from the surface are set as the explanatory variables, and the maximum value CT of the tensile stress is set as the target variable, The regression equation includes the following equation (2). CT=dCS+eDOL+f···(2) Here, d ~ f are constants.

10. The method for estimating the stress characteristics of tempered glass according to claim 7, wherein, The stress characteristics include the thickness T of the reinforced glass. When the maximum compressive stress value CS in the compressive stress layer, the diffusion depth DOL of K ions introduced through the ion exchange treatment from the surface, and the thickness T of the strengthened glass are set as the explanatory variables, and the depth DOC of the compressive stress layer is set as the target variable, The regression equation includes the following equation (4). DOC=aT+bCS+cDOL+d···(4) Here, a to d are constants.

11. The method for estimating the stress characteristics of tempered glass according to claim 7 or 10, wherein, The stress characteristics include the thickness T of the reinforced glass. When the maximum compressive stress value CS in the compressive stress layer, the diffusion depth DOL of K ions introduced through the ion exchange treatment from the surface, and the thickness T of the tempered glass are set as the explanatory variables, and the maximum value CT of the tensile stress is set as the target variable, The regression equation includes the following equation (5). CT=eT+fCS+gDOL+h···(5) Here, e ~ h are constants.

12. The method for estimating the stress characteristics of tempered glass according to claim 7, wherein, The multiple ion exchange treatments refer to two ion exchange treatments. In the two ion exchange treatments, the maximum compressive stress value CS in the compressive stress layer of the strengthened glass, which is located after the first ion exchange treatment and before the last (i.e., the second ion exchange treatment), is determined. 1st and the diffusion depth DOL of K ions introduced through the first ion exchange treatment from the surface. 1st Let this be the explanatory variable. The maximum compressive stress value CS in the compressive stress layer of the strengthened glass after the last, i.e., the second, ion exchange treatment. 2nd and the diffusion depth DOL of the K ions introduced from the surface through the last, i.e., the second ion exchange treatment. 2nd Let this be the explanatory variable. When the depth of the compressive stress layer (DOC) of the strengthened glass after the last (i.e., the second) ion exchange treatment is set as the target variable, The regression equation includes the following equation (7). DOC=aCS 1st +bDOL 1st +cCS 2nd +dDOL 2nd +e···(7) Here, a to e are constants.

13. The method for estimating the stress characteristics of tempered glass according to claim 7 or 12, wherein, The multiple ion exchange treatments refer to two ion exchange treatments. In the two ion exchange treatments, the maximum compressive stress value CS in the compressive stress layer of the strengthened glass, which is located after the first ion exchange treatment and before the last (i.e., the second ion exchange treatment), is determined. 1st and the diffusion depth DOL of K ions introduced through the first ion exchange treatment from the surface. 1st Let this be the explanatory variable. The maximum compressive stress value CS in the compressive stress layer of the strengthened glass after the last, i.e., the second, ion exchange treatment. 2nd and the diffusion depth DOL of the K ions introduced from the surface through the last, i.e., the second ion exchange treatment. 2nd Let this be the explanatory variable. When the maximum tensile stress CT of the strengthened glass after the last, i.e., the second, ion exchange treatment is set as the target variable, The regression equation includes the following equation (8). CT=fCS 1st +gDOL 1st +hCS 2nd +iDOL 2nd +j···(8) Here, f~j is a constant.

14. The method for estimating the stress characteristics of tempered glass according to claim 7, wherein, The stress characteristics include the thickness T of the reinforced glass. The multiple ion exchange treatments refer to two ion exchange treatments. In the two ion exchange treatments, the maximum compressive stress value CS in the compressive stress layer of the strengthened glass, which is located after the first ion exchange treatment and before the last (i.e., the second ion exchange treatment), is determined. 1st and the diffusion depth DOL of K ions introduced through the first ion exchange treatment from the surface. 1st Let this be the explanatory variable. The maximum compressive stress value CS in the compressive stress layer of the strengthened glass after the last, i.e., the second, ion exchange treatment. 2nd and the diffusion depth DOL of the K ions introduced from the surface through the last, i.e., the second ion exchange treatment. 2nd Let this be the explanatory variable. Let the thickness T of the tempered glass be the explanatory variable. When the depth of the compressive stress layer (DOC) of the strengthened glass after the last (i.e., the second) ion exchange treatment is set as the target variable, The regression equation includes the following equation (10). DOC=aT+bCS 1st +cDOL 1st +dCS 2nd +eDOL 2nd +f···(10) Here, a to f are constants.

15. The method for estimating the stress characteristics of tempered glass according to claim 7 or 14, wherein, The stress characteristics include the thickness T of the reinforced glass. The multiple ion exchange treatments refer to two ion exchange treatments. In the two ion exchange treatments, the maximum compressive stress value CS in the compressive stress layer of the strengthened glass, which is located after the first ion exchange treatment and before the last (i.e., the second ion exchange treatment), is determined. 1st and the diffusion depth DOL of K ions introduced through the first ion exchange treatment from the surface. 1st Let this be the explanatory variable. The maximum compressive stress value CS in the compressive stress layer of the strengthened glass after the last, i.e., the second, ion exchange treatment. 2nd and the diffusion depth DOL of the K ions introduced from the surface through the last, i.e., the second ion exchange treatment. 2nd Let this be the explanatory variable. Let the thickness T of the tempered glass be the explanatory variable. When the maximum tensile stress CT of the strengthened glass after the last, i.e., the second, ion exchange treatment is set as the target variable, The regression equation includes the following equation (11). CT=gT+hCS 1st +iDOL 1st +jCS 2nd +kDOL 2nd +l···(11) Here, g ~ l is a constant.

16. The method for estimating the stress characteristics of tempered glass according to claim 6, wherein, The regression equation is a multiple equation.

17. The method for estimating the stress characteristics of tempered glass according to claim 16, wherein, When the maximum compressive stress value CS in the compressive stress layer and the diffusion depth DOL of K ions introduced through the ion exchange treatment from the surface are set as the explanatory variables, and the depth DOC of the compressive stress layer is set as the target variable, The regression equation includes the following equation (13). DOC=a(CS+b) 2 +c(DOL+d) 2 +e ···(13) Here, a to e are constants.

18. The method for estimating the stress characteristics of tempered glass according to claim 16 or 17, wherein, When the maximum compressive stress value CS in the compressive stress layer and the diffusion depth DOL of K ions introduced through the ion exchange treatment from the surface are set as the explanatory variables, and the maximum value CT of the tensile stress is set as the target variable, The regression equation includes the following equation (14). CT=f(CS+g) 2 +h(DOL+i) 2 +j ···(14) Here, f~j is a constant.

19. The method for estimating the stress characteristics of tempered glass according to claim 16, wherein, The stress characteristics include the thickness T of the reinforced glass. The multiple ion exchange treatments refer to two ion exchange treatments. In the two ion exchange treatments, the maximum compressive stress value CS in the compressive stress layer of the strengthened glass, which is located after the first ion exchange treatment and before the last (i.e., the second ion exchange treatment), is determined. 1st and the diffusion depth DOL of K ions introduced through the first ion exchange treatment from the surface. 1st Let this be the explanatory variable. The maximum compressive stress value CS in the compressive stress layer of the strengthened glass after the last, i.e., the second, ion exchange treatment. 2nd and the diffusion depth DOL of the K ions introduced from the surface through the last, i.e., the second ion exchange treatment. 2nd Let this be the explanatory variable. Let the thickness T of the tempered glass be the explanatory variable. When the depth of the compressive stress layer (DOC) of the strengthened glass after the last (i.e., the second) ion exchange treatment is set as the target variable, The regression equation includes the following equation (16). DOC=a(T+b) 2 +c(CS 1st +d) 2 +e(DOL 1st +f) 2 +g(CS 2nd +h) 2 +i(DOL 2nd +j) 2 +k ···(16) Here, a~k are constants.

20. The method for estimating the stress characteristics of tempered glass according to claim 16 or 19, wherein, The stress characteristics include the thickness T of the reinforced glass. The multiple ion exchange treatments refer to two ion exchange treatments. In the two ion exchange treatments, the maximum compressive stress value CS in the compressive stress layer of the strengthened glass, which is located after the first ion exchange treatment and before the last (i.e., the second ion exchange treatment), is determined. 1st and the diffusion depth DOL of K ions introduced through the first ion exchange treatment from the surface. 1st Let this be the explanatory variable. The maximum compressive stress value CS in the compressive stress layer of the strengthened glass after the last, i.e., the second, ion exchange treatment. 2nd and the diffusion depth DOL of the K ions introduced from the surface through the last, i.e., the second ion exchange treatment. 2nd Let this be the explanatory variable. Let the thickness T of the tempered glass be the explanatory variable. When the maximum tensile stress CT of the strengthened glass after the last, i.e., the second, ion exchange treatment is set as the target variable, The regression equation includes the following equation (17). CT=l(T+m) 2 +n(CS 1st +o) 2 +p(DOL 1st +q) 2 +r(CS 2nd +s) 2 +t(DOL 2nd +u) 2 +v ···(17) Here, l to v are constants.

21. The method for estimating the stress characteristics of tempered glass according to claim 16, wherein, The regression equation includes the product term CS×DOL, which is the maximum compressive stress value CS in the compressive stress layer and the diffusion depth DOL of K ions introduced through the ion exchange treatment from the surface.

22. The method for estimating the stress characteristics of tempered glass according to any one of claims 1, 2, 3, 4, 5, 6, 7, 8, 10, 12, 14, 16, 17, 19 or 21, wherein, The tempered glass of the presumed object contains Na2O and Li2O as its glass composition. The compressive stress layer comprises a compressive stress layer caused by K ions introduced through the ion exchange treatment, and a compressive stress layer caused by Na ions introduced through the ion exchange treatment. In the sampling process, a portion of the stress characteristics are measured using a surface stress meter that utilizes the optical waveguide effect, and the other stress characteristics are measured using a scattered light photoelastic stress meter.

23. A method for fabricating a stress characteristic estimation model, which is a method for fabricating a stress characteristic estimation model for reinforced glass used to estimate the stress characteristics in a compressive stress layer formed through multiple ion exchange treatments. The prediction model is used to infer other stress characteristics based on a subset of stress characteristics in the compressive stress layer. The method for creating a model for estimating stress characteristics includes: The sampling process involves obtaining the plurality of stress characteristics from a sample of reinforced glass containing the compressive stress layer as training data; and The prediction model creation process involves using the training data to create a prediction model that represents the relationship between a subset of stress characteristics and the other stress characteristics through a computational processing device.

24. A method for estimating the stress characteristics of tempered glass, characterized in that, Among the multiple stress characteristics in a compressive stress layer formed through multiple ion exchange treatments, other stress characteristics are inferred based on some of the stress characteristics, possessing the following: The estimation process involves estimating the other stress characteristics using a calculation processing device capable of performing calculations based on a prediction model representing the relationship between the partial stress characteristics and the other stress characteristics. and The measurement process involves obtaining a portion of the stress characteristics of the tempered glass containing the presumed compressive stress layer as input data for the prediction model. The other stress characteristics include the depth of the compressive stress layer (DOC). In the estimation process, the input data obtained through the measurement process is input into the prediction model, and the output data related to the depth of compressive stress (DOC), which is one of the other stress characteristics, is obtained through the calculation processing device.

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