Information processing device, information processing method, information processing program, and method for manufacturing workpiece

Abstract

This information processing device comprises a processor. The processor: acquires a first measurement value that corresponds to a first energy amount and is dependent on a second energy amount different in type from the first energy amount; and derives the first energy amount from the first measurement value on the basis of the relationship between the first energy amount and the first measurement value, the relationship corresponding to the second energy amount.

Description

Information processing device, information processing method, information processing program, and method for manufacturing workpiece

[0001] The disclosed technology relates to an information processing device, an information processing method, an information processing program, and a method for manufacturing a workpiece.

[0002] Various techniques are known in the art for measuring energy (eg, pressure, heat, ultraviolet light, etc.) applied to a surface.

[0003] First, a method using a color-forming material that changes color depending on the amount of energy applied is known. For example, a color-forming material such as Prescale (registered trademark) (manufactured by Fujifilm Corporation) can be used. For example, International Publication No. 2021 / 235364 discloses photographing a pressure measurement sheet (e.g., a Prescale) and converting the density value of the pressure measurement sheet contained in the photographed image into a pressure value.

[0004] Second, a method using multiple sensor elements that output an electrical signal according to energy is known. For example, Japanese Patent Application Laid-Open No. 2021-032806 discloses a hot wire flow measurement sheet in which multiple temperature-sensitive sensors that change electrical resistance depending on temperature are provided in a matrix on a seat heater.

[0005] In recent years, there has been a demand for technology capable of accurately measuring energy under various circumstances. For example, in a heating and pressing device that applies pressure to a workpiece while heating it, it is desirable to accurately measure both the pressure and the amount of heat (temperature) applied to the workpiece in order to more precisely adjust and manage the heating and pressing conditions. The heating and pressing device is an example of a processing device for performing processing such as adhesion, bonding, transfer, and deformation on the workpiece.

[0006] However, in conventional technology, it has sometimes been difficult to measure energy accurately. For example, the prescale described in International Publication No. 2021 / 235364 has temperature dependency, so the accuracy of the measurement results (pressure distribution) may decrease under heating. Also, for example, the temperature sensor described in Japanese Patent Application Laid-Open No. 2021-032806 measures the electrical resistance value according to the volume expansion coefficient of the material in response to temperature changes, so the volume of the material shrinks under pressure, and the accuracy of the measurement results (temperature distribution) may decrease.

[0007] The present disclosure provides an information processing device, an information processing method, and an information processing program that can measure energy with high accuracy, as well as a method for manufacturing a workpiece using the technology.

[0008] A first aspect of the present disclosure is an information processing device including a processor, wherein the processor acquires a first measurement value corresponding to a first energy amount, the first measurement value being dependent on a second energy amount of a type different from the first energy amount, and derives the first energy amount from the first measurement value based on a relationship between the first energy amount and the first measurement value, the relationship being dependent on the second energy amount.

[0009] In the above aspect, the processor may acquire a second measurement value corresponding to the second amount of energy measured under the same measurement conditions as the measurement conditions of the first measurement value, select a first calibration curve corresponding to the second measurement value from a plurality of first calibration curves in which the relationship between the first amount of energy and the first measurement value is predetermined for each second amount of energy, and derive the first amount of energy from the first measurement value based on the selected first calibration curve.

[0010] In the above aspect, the second measurement value may depend on the first energy amount, and the processor may select a second calibration curve corresponding to the derived first energy amount from a plurality of second calibration curves in which the relationship between the second energy amount and the second measurement value is predetermined for each first energy amount, and derive the second energy amount from the second measurement value based on the selected second calibration curve.

[0011] In the above aspect, the processor may select a first calibration curve from the plurality of first calibration curves that corresponds to the derived second energy amount, and re-derive the first energy amount from the first measurement value based on the selected first calibration curve.

[0012] In the above aspect, the processor may repeat the selection of the first calibration curve, the derivation of the first energy amount, the selection of the second calibration curve, and the derivation of the second energy amount until the derived first energy amount and second energy amount converge.

[0013] In the above aspect, the processor may acquire a first measurement distribution representing the distribution of first measurement values ​​on the surface to be measured, and derive a distribution of first energy amounts from the first measurement distribution based on the selected first calibration curve.

[0014] In the above aspect, the processor may acquire a second measurement distribution representing the distribution of second measurement values ​​on the measured surface, select a first calibration curve corresponding to the second measurement distribution for each portion of the measured surface, and derive a distribution of the first energy amount from the first measurement distribution based on the first calibration curve selected for each portion of the measured surface.

[0015] In the above aspect, the processor may select a first calibration curve corresponding to the second measurement distribution for each portion of the measured surface according to the particle size of the first measurement distribution, and if the particle size of the first measurement distribution is coarser than the particle size of the second measurement distribution, identify a representative value of the second measurement value for each portion of the measured surface based on the second measurement distribution, and select a first calibration curve corresponding to the identified representative value of the second measurement value.

[0016] In the above aspect, the processor may acquire a second measurement distribution representing the distribution of second measurement values ​​on the measured surface, and derive a distribution of second energy amounts from the second measurement distribution based on the selected second calibration curve.

[0017] In the above aspect, the processor may acquire a first measurement distribution representing the distribution of first measurement values ​​on the measured surface, select a second calibration curve corresponding to the first measurement distribution for each portion of the measured surface, and derive a distribution of the second energy amount from the second measurement distribution based on the second calibration curve selected for each portion of the measured surface.

[0018] In the above aspect, the processor may select a second calibration curve corresponding to the first measurement distribution for each portion of the measured surface according to the particle size of the second measurement distribution, and if the particle size of the second measurement distribution is coarser than the particle size of the first measurement distribution, identify a representative value of the first measurement value for each portion of the measured surface based on the first measurement distribution, and select a second calibration curve corresponding to the identified representative value of the first measurement value.

[0019] In the above aspect, the first amount of energy may be pressure, and the second amount of energy may be heat.

[0020] In the above aspect, the first measurement value may be a value corresponding to the color density of a color-producing member that produces color at a density corresponding to the applied pressure, and the second measurement value corresponding to the second amount of energy may be an electrical resistance value output from a temperature-sensitive sensor that outputs an electrical resistance value corresponding to the applied amount of heat.

[0021] A second aspect of the present disclosure is an information processing method in which a computer executes a process of acquiring a first measurement value corresponding to a first energy amount, the first measurement value being dependent on a second energy amount of a type different from the first energy, and deriving the first energy amount from the first measurement value based on a relationship between the first energy amount and the first measurement value, the relationship being dependent on the second energy amount.

[0022] A third aspect of the present disclosure is for a computer to execute a process of acquiring a first measurement value corresponding to a first energy amount, the first measurement value being dependent on a second energy amount of a type different from the first energy, and deriving the first energy amount from the first measurement value based on a relationship between the first energy amount and the first measurement value, the relationship being dependent on the second energy amount.

[0023] A fourth aspect of the present disclosure is a method for manufacturing a workpiece using a jig, which includes obtaining a first measurement value corresponding to a first amount of energy applied to the workpiece, the first measurement value being dependent on a second amount of energy of a type different from the first amount of energy, deriving the first amount of energy from the first measurement value based on a relationship between the first amount of energy and the first measurement value that is dependent on the second amount of energy, and adjusting the jig so that a predetermined standard first amount of energy is applied to the workpiece based on the derived first amount of energy.

[0024] According to the present disclosure, energy can be measured with high accuracy.

[0025] FIG. 1 is a diagram for explaining an overview of an information processing device. FIG. 2 is a schematic diagram showing an example of the configuration of a processing device. FIG. 3 is a diagram showing an example of temperature distribution on a processing surface under heating. FIG. 4 is a diagram showing an example of pressure distribution on a processing surface under non-heating. FIG. 5 is a diagram showing an example of pressure distribution on a processing surface under heating. FIG. 6 is a diagram showing an example of the hardware configuration of an information processing device. FIG. 7 is a diagram showing an example of a first calibration curve. FIG. 8 is a diagram showing an example of a second calibration curve. FIG. 9 is a functional block diagram showing an example of the functional configuration of an information processing device. FIG. 10 is a diagram for explaining a process of deriving an amount of energy. FIG. 11 is a diagram for explaining a process of deriving an amount of energy. FIG. 12 is a diagram showing an example of a screen displayed on a display. FIG. 13 is a flowchart showing an example of the flow of information processing.

[0026] An example of an embodiment of the disclosed technology will be described below with reference to the drawings. In each drawing, identical or equivalent components and parts are designated by the same reference numerals, and duplicate descriptions will be omitted. Also, the dimensional proportions in the drawings are exaggerated for the sake of explanation and may differ from the actual proportions.

[0027] First, an overview of an information processing device 10 according to this embodiment will be described with reference to Figures 1 to 5. The information processing device 10 according to this embodiment has a function for accurately measuring each of multiple types of energy applied to a workpiece 80 in a processing device 90 that processes the workpiece 80 using a jig 92.

[0028] Specifically, the information processing device 10 acquires a first measurement value corresponding to a certain type of energy (hereinafter referred to as a first energy) applied to the workpiece 80, measured using the color-forming member 50. The information processing device 10 also acquires a second measurement value corresponding to a different type of energy (hereinafter referred to as a second energy) applied to the workpiece 80, measured using the sensor device 60. Then, the information processing device 10 derives a distribution of the first energy and a distribution of the second energy applied to the workpiece 80 based on the acquired first and second measurement values.

[0029] The color-forming member 50 is a sheet-like member that, when subjected to a first energy such as pressure, ultraviolet light, or heat, develops color with a density distribution corresponding to the amount of energy applied. By analyzing the color-forming state of the color-forming member 50, the surface distribution of the first energy applied to the color-forming member 50 can be monitored. For example, the information processing device 10 may derive the surface distribution of the first energy based on the color density value of each pixel of a color-forming member image 51 obtained by photographing the color-forming member 50. The color-forming member 50 can be photographed using a digital camera or a scanner, and the color-forming member image 51 is obtained, for example, as a color image. The color density value is, for example, a gradation value when each pixel of the color-forming member image 51 is expressed using an arbitrary number of gradations (for example, 256 gradations).

[0030] An example of the color-forming member 50 is Prescale (registered trademark) (manufactured by Fujifilm Corporation), which develops color with a density distribution corresponding to the applied pressure. The prescale is a sheet-like support on which a color former layer containing dispersed microcapsules encapsulating a colorless dye and a developer layer containing a color developer are laminated. When pressure is applied to the prescale, the microcapsules are broken, and the colorless dye is adsorbed to the developer, resulting in color development through a chemical reaction. The colorless dye is encapsulated in multiple types of microcapsules with different sizes and strengths. The amount of colorless dye that flows out of the broken microcapsules and adsorbs to the developer varies depending on the pressure applied to the prescale. Therefore, the prescale develops color at a density corresponding to the applied pressure.

[0031] The sensor device 60 is a device in which a plurality of sensor elements are arranged on a sheet. When a second energy such as pressure or heat is applied, the sensor elements output an electrical signal corresponding to the amount of applied energy. For example, the sensor device 60 can be a temperature measurement sheet in which a plurality of temperature-sensitive sensors formed of a material whose volume and electrical resistance change with temperature are arranged in a matrix (see JP 2021-032806 A). By analyzing the electrical resistance of each of the plurality of temperature-sensitive sensors, the surface distribution of the heat (temperature) applied to the temperature measurement sheet can be monitored.

[0032] The sensor device 60 for measuring temperature is not limited to the temperature measurement sheet equipped with the above-described temperature sensor. For example, it may be a sheet formed with a plurality of elements, such as resistance temperature detectors, thermocouples, and thermistors, that generate electrical changes, such as electrical resistance or potential difference, in response to temperature changes. Furthermore, the sensor device 60 is not limited to being formed as an integrated unit (e.g., in a sheet shape). For example, the surface distribution of the second energy can also be monitored by individually arranging a plurality of sensor elements at any position on the surface to be measured and analyzing the electrical changes of each of the sensor elements.

[0033] 2 is a diagram showing a schematic configuration of a heat press machine as an example of a processing device 90. The heat press machine sandwiches the workpiece 80 between a heated upper jig 92U and a heated lower jig 92L, and applies pressure from the upper jig 92U side, thereby deforming the workpiece 80 by heat and pressure. The workpiece 80 may be, for example, an industrial product such as a metal plate or a semiconductor wafer, or a material thereof.

[0034] In order to more precisely adjust and manage the heating and pressure conditions of the processing device 90, it is desirable to monitor both the pressure and heat (temperature) applied to the workpiece 80. If a color-developing member 50 (prescale) capable of measuring pressure is placed on the workpiece 80 and pressure is applied, the pressure distribution applied to the workpiece 80 on the processing surface (XY plane in FIG. 2) can be measured. Also, if a sensor device 60 (temperature measurement sheet) capable of measuring temperature is placed on the workpiece 80 and heated, the temperature distribution applied to the workpiece 80 on the processing surface can be measured.

[0035] It should be noted that when measuring pressure distribution and temperature distribution, the measurement is not limited to a configuration in which the workpiece 80 and the color-forming member 50 or the sensor device 60 are overlapped, and the workpiece 80 may be removed and only the color-forming member 50 or the sensor device 60 may be placed on the processing surface for measurement. Also, the color-forming member 50 and the sensor device 60 may be overlapped for measurement. However, in order to avoid the influence of one of the color-forming member 50 and the sensor device 60 on the other (for example, the influence of thickness, unevenness, etc.), it is desirable to perform the measurement using the color-forming member 50 and the measurement using the sensor device 60 separately.

[0036] Incidentally, under heating (when the upper jig 92U and the lower jig 92L are at a high temperature), the pressure applied to the workpiece 80 may change from that under non-heating (when the upper jig 92U and the lower jig 92L are at room temperature) due to thermal expansion of the upper jig 92U and the lower jig 92L. Therefore, when heating and pressurization are performed simultaneously, it is necessary to monitor not only the temperature distribution but also the pressure distribution under heating.

[0037] However, because prescale is temperature dependent, the accuracy of the measurement results (pressure distribution) may decrease when heated. Therefore, even if changes in the color density distribution of the prescale are observed under heating and non-heating, it is difficult to distinguish whether the changes are due to changes in the characteristics of the prescale caused by heat or changes in pressure due to thermal expansion of the jig.

[0038] Fig. 3 shows an example of a temperature distribution 62 on the processing surface under heating. Fig. 4 shows an example of a pressure distribution 52A on the processing surface under non-heating. Fig. 5 shows an example of a pressure distribution 52B on the processing surface under heating. As shown in Figs. 4 and 5, the overall shape of the pressure distribution differs between under non-heating and under heating, and the magnitude of the pressure value (shown by density) also differs.

[0039] Furthermore, because the temperature sensor measures electrical resistance values ​​corresponding to the volumetric expansion coefficient of the material with respect to temperature changes, the volume of the material shrinks under pressure, which can reduce the accuracy of the measurement results (temperature distribution). Therefore, even if an attempt is made to select from multiple first calibration curves 18 (see FIG. 7 ), in which the relationship between the color density value of the color-forming member image 51 and the pressure value is predetermined for each temperature, an appropriate first calibration curve 18 may not be selected because the temperature is inaccurate. In other words, even if an attempt is made to correct the pressure value based on the measured temperature, taking into account the temperature dependency of the prescale, the temperature measurement itself may not be accurate, making it difficult to accurately derive the pressure value.

[0040] Therefore, the information processing device 10 according to this embodiment mutually corrects the distribution of the first energy (pressure distribution) obtained by the color-producing member 50 and the distribution of the second energy (temperature distribution) obtained by the sensor device 60. This makes it possible to accurately measure each of the multiple different types of energy. The information processing device 10 will be described in detail below.

[0041] In the following description, an example will be described in which a prescale that develops a color at a density corresponding to the applied pressure is used as the color-developing member 50, and a temperature measurement sheet equipped with multiple temperature-sensitive sensors that output an electrical resistance value corresponding to the applied heat amount is used as the sensor device 60. That is, as an example, the first amount of energy is pressure. The second amount of energy is heat (temperature). The first measurement value is a value corresponding to the color density of the prescale. The second measurement value is the electrical resistance value output from the temperature-sensitive sensor.

[0042] First, an example of the hardware configuration of the information processing device 10 will be described with reference to Fig. 6. As shown in Fig. 6, the information processing device 10 includes a CPU (Central Processing Unit) 21, a non-volatile storage unit 22, and a memory 23 serving as a temporary storage area. The information processing device 10 also includes a display 24 such as a liquid crystal display, an input unit 25, and a network I / F (Interface) 26. The CPU 21, the storage unit 22, the memory 23, the display 24, the input unit 25, and the network I / F 26 are connected via a bus 28 such as a system bus and a control bus so as to be able to exchange various information with each other.

[0043] The storage unit 22 is realized by a storage medium such as a hard disk drive (HDD), a solid state drive (SSD), or a flash memory. The storage unit 22 stores an information processing program 27 for the information processing device 10, a plurality of first calibration curves 18, and a plurality of second calibration curves 19. The CPU 21 reads the information processing program 27 from the storage unit 22, loads it into the memory 23, and executes the loaded information processing program 27. The CPU 21 is an example of a processor of the present disclosure.

[0044] The input unit 25 is for receiving user operations and may be, for example, a touch panel, buttons, a keyboard, or a mouse. The network I / F 26 performs wired or wireless communication with the sensor device 60, a digital camera or scanner for obtaining the color-developing member image 51, and other external devices (not shown). Examples of the information processing device 10 that may be used include a smartphone, a tablet device, a wearable device, a personal computer, and a server computer, as appropriate.

[0045] FIG. 7 shows an example of multiple first calibration curves 18. The first calibration curve 18 represents the relationship between the first energy amount and the first measurement value, and the relationship corresponds to the second energy amount. That is, each of the multiple first calibration curves 18 is data in which the relationship between the first energy amount and the first measurement value is predetermined for each second energy amount. In the example of FIG. 7 , the multiple first calibration curves 18 represent data in which the relationship between the pressure value applied to the color-forming member 50 and the color density value indicating the density of the color-forming member 50 is predetermined for each temperature. The information processing device 10 refers to the first calibration curve 18 when deriving the pressure value applied to the color-forming member 50 based on the color density value of the color-forming member image 51. The first calibration curve 18 may be provided by the manufacturer of the color-forming member 50. Note that the number and shape of the first calibration curves 18 shown in FIG. 7 are merely examples, and a larger number is preferable.

[0046] FIG. 8 shows an example of multiple second calibration curves 19. Each of the multiple second calibration curves 18 is data in which the relationship between the second energy amount and the second measurement value is predetermined for each first energy amount. In the example of FIG. 8, the multiple second calibration curves 19 are data in which the relationship between the amount of heat applied to the sensor device 60 and the electrical resistance value output from the sensor device 60 is predetermined for each pressure value. The information processing device 10 refers to the second calibration curve 19 when deriving the temperature of the sensor device 60 based on the electrical resistance value obtained from the sensor device 60. The second calibration curve 19 may be provided by the manufacturer of the sensor device 60. Note that the number and shape of the second calibration curves 19 shown in FIG. 8 are merely examples, and a larger number is preferable.

[0047] Next, an example of the functional configuration of the information processing device 10 will be described with reference to Fig. 9. As shown in Fig. 9, the information processing device 10 includes an acquisition unit 30, a selection unit 32, a derivation unit 34, and a control unit 36. When the CPU 21 executes the information processing program 27, the CPU 21 functions as each of the functional units of the acquisition unit 30, the selection unit 32, the derivation unit 34, and the control unit 36.

[0048] The acquisition unit 30 acquires first measurement values ​​corresponding to a first energy amount, the first measurement values ​​being dependent on a second energy amount of a type different from the first energy amount. Specifically, the acquisition unit 30 acquires a first measurement distribution representing the distribution of first measurement values ​​on the measurement surface. For example, the acquisition unit 30 acquires a distribution of color density values ​​that are dependent on temperature and correspond to pressure, based on the color-producing member image 51. As described above, since the prescale is temperature-dependent, the color density values ​​identified from the color-producing member image 51 obtained by photographing the prescale also have temperature dependence.

[0049] The acquisition unit 30 also acquires second measurement values ​​corresponding to the second amount of energy measured under the same measurement conditions as those for the first measurement values. Specifically, the acquisition unit 30 acquires a second measurement distribution representing the distribution of the second measurement values ​​on the surface to be measured. For example, the acquisition unit 30 acquires, from the sensor device 60, a distribution of electrical resistance values ​​corresponding to the amount of heat measured under the same measurement conditions (e.g., heating conditions and pressure conditions) as those for measuring the color density values. Note that the term "same" measurement conditions refers to "same" in the sense of including an error that is generally acceptable in the technical field to which the technology of the present disclosure pertains and that does not contradict the spirit of the technology of the present disclosure.

[0050] The second measurement value may be dependent on the first amount of energy. As described above, the temperature sensor has pressure dependency, and therefore the electrical resistance value obtained from the temperature sensor also has pressure dependency.

[0051] The selector 32 and the deriving unit 34 derive the first energy amount from the first measurement value and the second energy amount from the second measurement value for each portion of the measured surface. By performing this process for all portions of the measured surface, the distribution of the first energy amount and the distribution of the second energy amount are derived.

[0052] 10 and 11, the processing for each portion of the measurement surface by the selection unit 32 and the derivation unit 34 will be described. Fig. 10 is a diagram showing how the processing is repeated N times (N is an integer of 2 or more) for a certain portion until the pressure value derived from the color density value converges to Pn and the temperature derived from the electrical resistance value converges to Tn. Fig. 11 is a graph illustrating the table in Fig. 10.

[0053] First, the selection unit 32 selects a first calibration curve 18 corresponding to the second measurement value from among the multiple first calibration curves 18. For example, the selection unit 32 may derive the second amount of energy from the acquired second measurement value using an arbitrary second calibration curve 19, and select a first calibration curve 18 according to the derived second amount of energy. For example, in the example of FIG. 7 , it is assumed that the selected first calibration curve 18 is for 100 degrees. Note that the second calibration curve 19 used to derive the second amount of energy may be a predetermined second calibration curve 19, such as a second calibration curve 19 closest to the average or a second calibration curve 19 according to the designed applied pressure of the processing device 90.

[0054] The derivation unit 34 derives the first amount of energy from the first measurement value based on the selected first calibration curve 18. For example, in the example of FIG. 7 , assume that the acquired color density value (first measurement value) is D1 and the selected first calibration curve 18 is for 100 degrees. In this case, the derivation unit 34 derives the pressure value (first amount of energy) to be 1.0 MPa.

[0055] The selection unit 32 selects the second calibration curve 19 corresponding to the derived first amount of energy from among the plurality of second calibration curves 19. For example, if the pressure value is derived to be 1.0 MPa as described above, the selection unit 32 selects the second calibration curve 19 corresponding to 1.0 MPa.

[0056] The derivation unit 34 derives the second amount of energy from the second measurement value based on the selected second calibration curve 19. For example, in the example of Fig. 8, it is assumed that the acquired electrical resistance value (second measurement value) is R1 and the selected second calibration curve 19 is 1.0 MPa. In this case, the derivation unit 34 derives the temperature (second amount of energy) to be 110 degrees.

[0057] Up to this point, the pressure value and the temperature have each been derived once. Thereafter, the selection unit 32 selects, from the plurality of first calibration curves 18, the first calibration curve 18 that corresponds to the derived second energy amount. For example, assume that the temperature (second energy amount) was derived as 110 degrees in the previous derivation process. In this case, the selection unit 32 selects the first calibration curve 18 that corresponds to 110 degrees.

[0058] The derivation unit 34 re-derives the first amount of energy from the first measurement value based on the selected first calibration curve 18. For example, in the example of Fig. 7, if the acquired color density value (first measurement value) is D1 and the selected first calibration curve 18 is 110 degrees, the derivation unit 34 re-derives the pressure value (first amount of energy) to be 0.9 MPa.

[0059] The selection unit 32 selects a second calibration curve 19 corresponding to the re-derived first amount of energy from among the multiple second calibration curves 19. The derivation unit 34 re-derives the second amount of energy from the second measurement value based on the selected second calibration curve 19. For example, in the example of Fig. 8 , if the acquired electrical resistance value (second measurement value) is R1 and the selected second calibration curve 19 is 0.9 MPa, the derivation unit 34 re-derives the temperature (second amount of energy) to be 112 degrees.

[0060] Up to this point, the pressure value and the temperature have each been derived twice. The selection unit 32 and the derivation unit 34 repeat the selection of the first calibration curve 18, the derivation of the first energy amount, the selection of the second calibration curve 19, and the derivation of the second energy amount until the derived pressure value (first amount of energy) and temperature (second amount of energy) converge.

[0061] In this way, the derivation of the first energy amount and the second energy amount for one portion of the measured surface is completed. The selection unit 32 and the derivation unit 34 perform the above process for all portions of the measured surface to derive the distribution of the first energy amount and the distribution of the second energy amount.

[0062] That is, the selection unit 32 may select the first calibration curve 18 corresponding to the second measurement distribution for each portion of the measured surface. The derivation unit 34 may derive the distribution of the first energy amount from the first measurement distribution based on the first calibration curve 18 selected for each portion of the measured surface. Furthermore, the selection unit 32 may select the second calibration curve 19 corresponding to the first measurement distribution for each portion of the measured surface. The derivation unit 34 may derive the distribution of the second energy amount from the second measurement distribution based on the second calibration curve 19 selected for each portion of the measured surface.

[0063] It should be noted that the particle size of the first measurement distribution obtained by the color-developing member 50 (prescale) does not necessarily match the particle size of the second measurement distribution obtained by the sensor device 60 (temperature measurement sheet). When deriving the energy distribution from the measurement distribution with a coarser particle size, a calibration curve may be selected using representative values ​​(e.g., mean, median, maximum, minimum, etc.) of the measurement distribution with a finer particle size.

[0064] For example, if the particle size of the first measurement distribution is coarser than the particle size of the second measurement distribution, the first calibration curve 18 corresponding to the second measurement distribution is selected for each portion of the measurement surface corresponding to the particle size of the first measurement distribution. In this case, the selector 32 identifies a representative value of the second measurement value for each portion of the measurement surface corresponding to the particle size of the first measurement distribution based on the second measurement distribution having a finer particle size. Then, the selector 32 selects the first calibration curve 18 corresponding to the identified representative value of the second measurement value.

[0065] For example, if the particle size of the second measurement distribution is coarser than the particle size of the first measurement distribution, the second calibration curve 19 corresponding to the first measurement distribution is selected for each portion of the measurement surface corresponding to the particle size of the second measurement distribution. In this case, the selector 32 identifies a representative value of the first measurement value for each portion of the measurement surface corresponding to the particle size of the second measurement distribution based on the first measurement distribution having a finer particle size. Then, the selector 32 selects the second calibration curve 19 corresponding to the identified representative value of the first measurement value.

[0066] The control unit 36 ​​presents information corresponding to the first measurement distribution and the second measurement distribution. For example, the control unit 36 ​​may present the information corresponding to the first measurement distribution and the second measurement distribution as a two-dimensional graph. Specifically, the control unit 36 ​​presents information corresponding to the distribution of the first energy amount and the distribution of the second energy amount derived by the derivation unit 34. As an example, FIG. 12 shows an example of a screen D displayed on the display 24 by the control unit 36.

[0067] For example, the control unit 36 ​​may present a two-dimensional graph representing the distribution of the first energy amount and a two-dimensional graph representing the distribution of the second energy amount. Fig. 12 illustrates a heat map 70 representing a pressure distribution as an example of a two-dimensional graph representing the distribution of the first energy amount. Also, a heat map 72 representing a temperature distribution as an example of a two-dimensional graph representing the distribution of the second energy amount. By doing so, the pressure distribution and the temperature distribution can be visually understood more easily.

[0068] For example, the control unit 36 ​​may present a graph in which a two-dimensional graph representing the distribution of the first amount of energy is superimposed on a two-dimensional graph representing the distribution of the second amount of energy. Fig. 12 shows an example of a heat map 74 in which a heat map 70 representing the pressure distribution is superimposed on a heat map 72 representing the temperature distribution. This makes it easier to visually understand the relationship between the pressure distribution and the temperature distribution.

[0069] Furthermore, for example, the control unit 36 ​​may present a comparison result between a predetermined reference distribution for the first energy amount and the derived distribution of the first energy amount. The reference distribution is, for example, a designed applied pressure distribution. Similarly, the control unit 36 ​​may present a comparison result between a predetermined reference distribution for the second energy amount and the derived distribution of the second energy amount. The reference distribution is, for example, a designed applied temperature distribution.

[0070] 12 shows, in tabular form, the derived and reference pressure values ​​and the derived and reference temperature values ​​for each of multiple measurement locations A through G on the measurement surface. Furthermore, to the right of the reference value, the ratio of the derived value to the reference value is shown, with a positive value indicating an excess and a negative value indicating a shortage. Measurement locations A through G are also plotted on a heat map 74 that represents an overlapping distribution. By presenting the derived values, reference values, and their comparison results in this way, it becomes easier to understand the deviation of the derived values ​​from the reference values.

[0071] Furthermore, the first amount of energy derived by the derivation unit 34 can be said to indicate the amount of the first energy applied to the workpiece 80 using the jig of the processing device 90. Similarly, the derived second amount of energy can be said to indicate the amount of the second energy applied to the workpiece 80 using the jig of the processing device 90. Therefore, the control unit 36 ​​may present parameters for adjusting the jig of the processing device 90 based on the derived distribution of the first energy amount and the distribution of the second energy amount. That is, the control unit 36 ​​may present parameters such that a predetermined reference first amount of energy and a predetermined reference second amount of energy are applied to the workpiece 80.

[0072] Furthermore, by using the technology of the information processing device 10 according to this embodiment, it is possible to realize a method for manufacturing a workpiece 80 with good processing accuracy using a processing device 90 (jig). Specifically, the method for manufacturing a workpiece according to this embodiment includes adjusting the jig of the processing device 90 based on the first energy amount derived by the lead-out unit 34 so that a predetermined reference first energy amount is applied to the workpiece 80.

[0073] Next, the operation of the information processing device 10 according to this embodiment will be described with reference to Fig. 13. In the information processing device 10, the CPU 21 executes the information processing program 27, thereby performing the information processing shown in Fig. 13. The information processing is performed, for example, when a user issues an instruction to start the execution via the input unit 25.

[0074] In step S10, the acquisition unit 30 acquires a first measurement distribution representing a distribution of first measurement values ​​according to a first amount of energy on the measurement surface. In step S12, the acquisition unit 30 acquires a second measurement distribution representing a distribution of second measurement values ​​according to a second amount of energy on the measurement surface. Note that the first measurement values ​​depend on the second amount of energy, and the second measurement values ​​depend on the first amount of energy.

[0075] In step S14, the acquisition unit 30 determines a portion of the measurement surface as a target portion for deriving an amount of energy. In step S16, the acquisition unit 30 acquires a first measurement value for the target portion determined in step S14 by extracting it from the first measurement distribution acquired in step S10. The acquisition unit 30 also acquires a second measurement value for the target portion determined in step S14 by extracting it from the second measurement distribution acquired in step S12.

[0076] In step S18, the selection unit 32 selects a first calibration curve 18 corresponding to the second measurement value acquired in step S16 from the plurality of first calibration curves 18. In step S20, the derivation unit 34 derives the first amount of energy from the first measurement value acquired in step S16, based on the first calibration curve 18 selected in step S18.

[0077] In step S22, the selection unit 32 selects a second calibration curve 19 corresponding to the first amount of energy derived in step S20 from among the plurality of second calibration curves 19. In step S24, the derivation unit 34 derives the second amount of energy from the second measurement value acquired in step S16, based on the second calibration curve 19 selected in step S22.

[0078] In step S26, the derivation unit 34 determines whether the first energy amount derived in step S20 and the second energy amount derived in step S24 have both converged. If they have not converged (if step S26 is N), the processes of steps S18 to S24 are repeated. Note that, in step S18 to which the process returns, the selection unit 32 selects the first calibration curve 18 corresponding to the second energy amount derived in the immediately preceding step S24.

[0079] On the other hand, if both the first energy amount and the second energy amount have converged (if step S26 is Y), the process proceeds to step S28. In step S28, the derivation unit 34 determines whether derivation of the first energy amount and the second energy amount has been completed for the entire measured surface. If not completed (if step S28 is N), the process returns to step S14, and the acquisition unit 30 determines another portion to be derived and repeats the subsequent processes.

[0080] On the other hand, if the derivation of the first energy amount and the second energy amount has been completed for all of the measurement surfaces (if step S28 is Y), the process proceeds to step S30. At this point, the derivation of the first energy amount distribution and the second energy amount distribution on the measurement surfaces is completed. In step S30, the control unit 36 ​​presents information corresponding to the first energy amount distribution and the second energy amount distribution on the measurement surfaces, and ends this information processing.

[0081] As described above, an information processing device 10 according to one aspect of the present disclosure includes at least one processor, and the processor acquires a first measurement value corresponding to a first energy amount, the first measurement value being dependent on a second energy amount of a type different from the first energy amount, and derives the first energy amount from the first measurement value based on a relationship between the first energy amount and the first measurement value, the relationship being dependent on the second energy amount.

[0082] That is, according to the information processing device 10, even if the first measurement value is affected by the second energy in addition to the first energy, the first energy amount can be derived with high accuracy. Therefore, the energy can be measured with high accuracy.

[0083] In addition, an information processing device 10 according to another aspect of the present disclosure includes at least one processor, and the processor acquires a first measurement distribution representing a distribution on the measured surface of first measurement values ​​corresponding to a first energy amount, the first measurement values ​​being dependent on a second energy amount of a type different from the first energy, acquires a second measurement distribution representing a distribution on the measured surface of second measurement values ​​corresponding to the second energy amount, measured under the same measurement conditions as the measurement conditions of the first measurement values, and presents information corresponding to the first measurement distribution and the second measurement distribution.

[0084] That is, according to the information processing device 10, even if the first measurement value is affected by the second energy, the information processing device 10 can present information corresponding to the first measurement distribution and the second measurement distribution while taking into account the effect of the second energy. Therefore, the energy can be measured with high accuracy.

[0085] In the above embodiment, the first energy amount and the second energy amount are both expressed as a surface distribution. However, at least one of the first energy amount and the second energy amount may be expressed as a single point instead of a surface distribution.

[0086] For example, the first measurement value may be measured as a distribution, and the second measurement value may be measured at only one point. In this case, the selection unit 32 selects the first calibration curve 18 based on the second measurement value at one point. The derivation unit 34 derives the distribution of the first energy amount from the first measurement distribution based on the selected first calibration curve 18. That is, the first energy amount is derived using a common first calibration curve 18 over the entire area of ​​the first measurement distribution. In this case, for example, instead of a temperature measurement sheet capable of measuring a surface distribution of temperature, a thermometer that measures the temperature at a certain point may be applied as the sensor device 60.

[0087] Alternatively, for example, the first measurement value may be measured at only one point, and the second measurement value may be measured as a distribution. In this case, the selection unit 32 selects the second calibration curve 19 based on the first measurement value at one point. The derivation unit 34 derives the distribution of the second energy amount from the second measurement distribution based on the selected second calibration curve 19. That is, the second energy amount is derived using a common second calibration curve 19 over the entire area of ​​the second measurement distribution. In this case, for example, a sensor that measures pressure at a certain point may be applied instead of the color-developing member 50 that can measure the surface distribution of pressure.

[0088] In the above embodiment, the first energy amount and the second energy amount are mutually corrected. However, this is not limiting. Specifically, at least one of the first energy amount and the second energy amount may be corrected, and the other may not be corrected. For example, when measuring temperature using a sensor device 60 in which pressure dependency is negligible, only one second calibration curve 19 is required, and the temperature can be uniquely derived using the second calibration curve 19.

[0089] In the above embodiment, a heat press machine has been described as an example of the processing device 90, but the present invention is not limited to this. As the processing device 90, various devices for performing processes such as adhesion, bonding, transfer, and deformation on a workpiece can be applied.

[0090] For example, the processing device 90 may be an apparatus for laminating two or more web-like materials (e.g., films, sheets, paper, and thin metal films). Such an apparatus has two rolls arranged in contact with each other, at least one of which has a heating means, as a jig, and bonds the web-like material while transporting it between the two rolls. The information processing device 10 may derive the pressure distribution and temperature distribution applied to the workpiece (web-like material) between the two rolls.

[0091] Furthermore, for example, when manufacturing a battery such as a lithium-ion secondary battery, the processing device 90 may be a device for restraining a stack of layers constituting the battery with a restraining member. In lithium-ion secondary batteries, a restraining load may be applied to stacks of layers such as a positive electrode layer, a solid electrolyte layer, and a negative electrode layer to improve battery performance and battery life. Furthermore, lithium-ion secondary batteries may generate heat or expand in volume during charging and discharging. Therefore, the information processing device 10 may derive the pressure distribution and temperature distribution applied to the stack when the stack is restrained with a restraining member.

[0092] In the above embodiment, a pressure value is used as the first energy amount, a color density value is used as the first measurement value, heat (temperature) is used as the second energy amount, and an electrical resistance value is used as the second measurement value. However, this is not limiting. The first measurement value may be any physical quantity that is dependent on the second energy amount corresponding to the second measurement value. The second measurement value may be any physical quantity that is dependent on the first energy amount corresponding to the first measurement value, or may be any physical quantity that is independent of the first energy amount.

[0093] For example, UV Scale (product name) (manufactured by Fujifilm Corporation), which develops color according to the amount of ultraviolet light, is known to have temperature dependency. The UV Scale may be applied as the color-developing member 50 of the above embodiment, and the amount of ultraviolet light may be used as the first energy amount, the color density value as the first measurement value, heat (temperature) as the second energy amount, and the electrical resistance value as the second measurement value.

[0094] Furthermore, for example, Thermoscale (product name) (manufactured by Fujifilm Corporation), which develops color in response to the amount of heat applied, may be used as the color-developing member 50 in the above embodiment, and a tactile sensor that outputs an electrical resistance value in response to the applied pressure may be used as the sensor device 60. That is, the amount of heat may be used as the first amount of energy, the color density value as the first measured value, the pressure value as the second amount of energy, and the electrical resistance value as the second measured value.

[0095] Furthermore, in the above embodiment, the following various processors can be used as the hardware structure of processing units that perform various processes, such as the acquisition unit 30, the selection unit 32, the derivation unit 34, and the control unit 36. As described above, the various processors include a CPU, which is a general-purpose processor that executes software (programs) and functions as various processing units, as well as dedicated electrical circuits that are processors having a circuit configuration specifically designed to perform specific processes, such as a programmable logic device (PLD) that is a processor whose circuit configuration can be changed after manufacture, such as an FPGA (Field Programmable Gate Array), and an ASIC (Application Specific Integrated Circuit).

[0096] A single processing unit may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, multiple processing units may be configured with a single processor.

[0097] Examples of configuring multiple processing units with a single processor include: first, a form in which one processor is configured with a combination of one or more CPUs and software, as typified by computers such as client and server computers, and this processor functions as multiple processing units; second, a form in which a processor is used to realize the functions of an entire system including multiple processing units with a single IC (Integrated Circuit) chip, as typified by systems on chips (SoCs); and thus, various processing units are configured using one or more of the above-mentioned various processors as a hardware structure.

[0098] Furthermore, more specifically, the hardware structure of these various processors can be an electric circuit that combines circuit elements such as semiconductor elements.

[0099] In the above embodiment, the information processing program 27 is pre-stored (installed) in the storage unit 22, but this is not limiting. The information processing program 27 may be provided in a form recorded on a recording medium such as a CD-ROM (Compact Disc Read Only Memory), a DVD-ROM (Digital Versatile Disc Read Only Memory), or a USB (Universal Serial Bus) memory. The information processing program 27 may also be downloaded from an external device via a network. Furthermore, the technology disclosed herein extends to not only information processing programs but also storage media that non-temporarily store information processing programs.

[0100] The present disclosure can also be applied to programs and program products. Specifically, the information processing program 27 in each of the above embodiments may be provided as a program product. The program product includes any type of product for providing a program. For example, the program product includes a program provided via a network such as the Internet, and a non-transitory computer-readable recording medium such as a CD-ROM or DVD on which the program is stored.

[0101] The technology of the present disclosure can also be appropriately combined with the above-described exemplary embodiments and examples. The above-described description and illustrations are detailed descriptions of the parts related to the technology of the present disclosure and are merely examples of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or new elements may be replaced with other parts from the description and illustrations shown above, within the scope of the gist of the technology of the present disclosure.

[0102] The following supplementary notes are further disclosed in relation to the above embodiments. [Supplementary Note 1] An information processing device including a processor, wherein the processor acquires a first measurement value corresponding to a first energy amount, the first measurement value being dependent on a second energy amount of a type different from the first energy amount, and derives the first energy amount from the first measurement value based on a relationship between the first energy amount and the first measurement value, the relationship being dependent on the second energy amount. [Supplementary Note 2] The information processing device according to Supplementary Note 1, wherein the processor acquires a second measurement value corresponding to the second energy amount, measured under the same measurement conditions as those of the first measurement value, and selects a first calibration curve corresponding to the second measurement value from a plurality of first calibration curves, the relationship between the first energy amount and the first measurement value being predetermined for each of the second energy amounts, and derives the first energy amount from the first measurement value based on the selected first calibration curve. [Supplementary Note 3] The information processing device according to Supplementary Note 2, wherein the second measurement value depends on the first energy amount, and the processor selects the second calibration curve corresponding to the derived first energy amount from among a plurality of second calibration curves, the relationship between the second energy amount and the second measurement value being predetermined for each of the first energy amounts, and derives the second energy amount from the second measurement value based on the selected second calibration curve. [Supplementary Note 4] The information processing device according to Supplementary Note 3, wherein the processor selects the first calibration curve corresponding to the derived second energy amount from among the plurality of first calibration curves, and re-derives the first energy amount from the first measurement value based on the selected first calibration curve. [Supplementary Note 5] The information processing device according to Supplementary Note 4, wherein the processor repeats the selection of the first calibration curve, the derivation of the first energy amount, the selection of the second calibration curve, and the derivation of the second energy amount until the derived first energy amount and the second energy amount converge. [Supplementary Note 6] The information processing device described in any one of Supplementary Note 2 to Supplementary Note 5, wherein the processor acquires a first measurement distribution representing a distribution of the first measurement values ​​on the measurement surface, and derives a distribution of the first energy amount from the first measurement distribution based on the selected first calibration curve.[Supplementary Note 7] The information processing device according to Supplementary Note 6, wherein the processor acquires a second measurement distribution representing a distribution of the second measurement values ​​on the measurement surface, selects the first calibration curve corresponding to the second measurement distribution for each portion of the measurement surface, and derives the distribution of the first amount of energy from the first measurement distribution based on the first calibration curve selected for each portion of the measurement surface. [Supplementary Note 8] The information processing device according to Supplementary Note 7, wherein the processor selects the first calibration curve corresponding to the second measurement distribution for each portion of the measurement surface according to the granularity of the first measurement distribution, and if the granularity of the first measurement distribution is coarser than the granularity of the second measurement distribution, identifies a representative value of the second measurement values ​​for each portion of the measurement surface based on the second measurement distribution, and selects the first calibration curve corresponding to the identified representative value of the second measurement values. [Supplementary Note 9] The information processing device according to Supplementary Note 3, wherein the processor acquires a second measurement distribution representing a distribution of the second measurement values ​​on the measurement surface, and derives the distribution of the second amount of energy from the second measurement distribution based on the selected second calibration curve. [Supplementary Note 10] The information processing device according to Supplementary Note 9, wherein the processor acquires a first measurement distribution representing a distribution of the first measurement values ​​on the measurement surface, selects the second calibration curve corresponding to the first measurement distribution for each portion of the measurement surface, and derives the distribution of the second energy amount from the second measurement distribution based on the second calibration curve selected for each portion of the measurement surface. [Supplementary Note 11] The information processing device according to Supplementary Note 10, wherein the processor selects the second calibration curve corresponding to the first measurement distribution for each portion of the measurement surface according to the granularity of the second measurement distribution, and if the granularity of the second measurement distribution is coarser than the granularity of the first measurement distribution, identifies a representative value of the first measurement values ​​for each portion of the measurement surface based on the first measurement distribution, and selects the second calibration curve corresponding to the identified representative value of the first measurement values. [Supplementary Note 12] The information processing device according to any one of Supplements 1 to 11, wherein the first energy amount is pressure, and the second energy amount is heat.[Supplementary Note 13] The information processing device according to Supplementary Note 12, wherein the first measurement value is a value corresponding to a color density of a color-producing member that develops a color at a density corresponding to an applied pressure, and the second measurement value corresponding to the second amount of energy is an electrical resistance value output from a temperature-sensitive sensor that outputs an electrical resistance value corresponding to an applied amount of heat. [Supplementary Note 14] An information processing method, in which a computer executes a process of: acquiring a first measurement value corresponding to a first amount of energy, the first measurement value being dependent on a second amount of energy different from the first energy, and deriving the first amount of energy from the first measurement value based on a relationship between the first amount of energy and the first measurement value that is dependent on the second amount of energy. [Supplementary Note 15] An information processing program, in which a computer executes a process of: acquiring a first measurement value corresponding to a first amount of energy, the first measurement value being dependent on a second amount of energy different from the first energy, and deriving the first amount of energy from the first measurement value based on a relationship between the first amount of energy and the first measurement value that is dependent on the second amount of energy. [Supplementary Note 16] A method for manufacturing a workpiece using a jig, comprising: acquiring a first measurement value corresponding to a first amount of energy applied to the workpiece, the first measurement value being dependent on a second amount of energy of a type different from the first amount of energy; deriving the first amount of energy from the first measurement value based on a relationship between the first amount of energy and the first measurement value, the relationship being dependent on the second amount of energy; and adjusting the jig based on the derived first amount of energy so that a predetermined standard first amount of energy is applied to the workpiece.

[0103] The disclosure of Japanese Patent Application No. 2023-223046, filed on December 28, 2023, is incorporated herein by reference in its entirety. All documents, patent applications, and technical standards mentioned herein are incorporated herein by reference to the same extent as if each individual document, patent application, and technical standard was specifically and individually indicated to be incorporated by reference.

Claims

1. An information processing device comprising a processor, the processor acquiring a first measurement value corresponding to a first amount of energy, the first measurement value being dependent on a second amount of energy of a type different from the first amount of energy, and deriving the first amount of energy from the first measurement value based on a relationship between the first amount of energy and the first measurement value, the relationship being dependent on the second amount of energy.

2. The information processing device according to claim 1, wherein the processor acquires a second measurement value corresponding to the second amount of energy measured under the same measurement conditions as the measurement conditions of the first measurement value, selects the first calibration curve corresponding to the second measurement value from among a plurality of first calibration curves in which the relationship between the first amount of energy and the first measurement value is predetermined for each of the second amounts of energy, and derives the first amount of energy from the first measurement value based on the selected first calibration curve.

3. The information processing device of claim 2, wherein the second measurement value is dependent on the first amount of energy, and the processor selects the second calibration curve corresponding to the derived first amount of energy from among a plurality of second calibration curves in which the relationship between the second amount of energy and the second measurement value is predetermined for each of the first amounts of energy, and derives the second amount of energy from the second measurement value based on the selected second calibration curve.

4. The information processing device according to claim 3, wherein the processor selects, from among the plurality of first calibration curves, a first calibration curve that corresponds to the derived second amount of energy, and re-derives the first amount of energy from the first measurement value based on the selected first calibration curve.

5. The information processing device according to claim 4, wherein the processor repeats the selection of the first calibration curve, the derivation of the first energy amount, the selection of the second calibration curve, and the derivation of the second energy amount until the derived first energy amount and the derived second energy amount converge.

6. The information processing device according to claim 2, wherein the processor acquires a first measurement distribution representing a distribution of the first measurement values ​​on the surface to be measured, and derives a distribution of the first energy amount from the first measurement distribution based on the selected first calibration curve.

7. The information processing device described in claim 6, wherein the processor obtains a second measurement distribution representing a distribution of the second measurement values ​​on the measured surface, selects the first calibration curve corresponding to the second measurement distribution for each portion of the measured surface, and derives a distribution of the first energy amount from the first measurement distribution based on the first calibration curve selected for each portion of the measured surface.

8. The information processing device described in claim 7, wherein the processor selects the first calibration curve corresponding to the second measurement distribution for each portion of the measured surface according to the granularity of the first measurement distribution, and when the granularity of the first measurement distribution is coarser than the granularity of the second measurement distribution, identifies a representative value of the second measurement value for each portion of the measured surface based on the second measurement distribution, and selects the first calibration curve corresponding to the identified representative value of the second measurement value.

9. The information processing device according to claim 3, wherein the processor acquires a second measurement distribution representing a distribution of the second measurement values ​​on the measured surface, and derives a distribution of the second energy amount from the second measurement distribution based on the selected second calibration curve.

10. The information processing device described in claim 9, wherein the processor obtains a first measurement distribution representing a distribution of the first measurement values ​​on the measured surface, selects the second calibration curve corresponding to the first measurement distribution for each portion of the measured surface, and derives a distribution of the second energy amount from the second measurement distribution based on the second calibration curve selected for each portion of the measured surface.

11. The information processing device described in claim 10, wherein the processor selects the second calibration curve corresponding to the first measurement distribution for each portion of the measured surface according to the granularity of the second measurement distribution, and when the granularity of the second measurement distribution is coarser than the granularity of the first measurement distribution, identifies a representative value of the first measurement value for each portion of the measured surface based on the first measurement distribution, and selects the second calibration curve corresponding to the identified representative value of the first measurement value.

12. The information processing device according to claim 1, wherein the first amount of energy is pressure, and the second amount of energy is heat.

13. An information processing device as described in claim 12, wherein the first measurement value is a value corresponding to the color density of a color-producing material that produces a color at a density corresponding to the applied pressure, and the second measurement value corresponding to the second amount of energy is an electrical resistance value output from a temperature sensor that outputs an electrical resistance value corresponding to the applied amount of heat.

14. An information processing method in which a computer executes a process of acquiring a first measurement value corresponding to a first amount of energy, the first measurement value being dependent on a second amount of energy of a type different from the first amount of energy, and deriving the first amount of energy from the first measurement value based on a relationship between the first amount of energy and the first measurement value, the relationship being dependent on the second amount of energy.

15. An information processing program for causing a computer to execute a process of acquiring a first measurement value corresponding to a first amount of energy, the first measurement value being dependent on a second amount of energy of a type different from the first amount of energy, and deriving the first amount of energy from the first measurement value based on a relationship between the first amount of energy and the first measurement value, the relationship being dependent on the second amount of energy.

16. A method for manufacturing a workpiece using a jig, comprising: acquiring a first measurement value corresponding to a first amount of energy applied to the workpiece, the first measurement value being dependent on a second amount of energy of a type different from the first amount of energy; deriving the first amount of energy from the first measurement value based on a relationship between the first amount of energy and the first measurement value, the relationship being dependent on the second amount of energy; and adjusting the jig based on the derived first amount of energy, so that a predetermined standard amount of first energy is applied to the workpiece.

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