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WO2025142253A1 - Dispositif de traitement d'informations, procédé de traitement d'informations, programme de traitement d'informations et procédé de fabrication de pièce - Google Patents

Dispositif de traitement d'informations, procédé de traitement d'informations, programme de traitement d'informations et procédé de fabrication de pièce Download PDF

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Publication number
WO2025142253A1
WO2025142253A1 PCT/JP2024/041637 JP2024041637W WO2025142253A1 WO 2025142253 A1 WO2025142253 A1 WO 2025142253A1 JP 2024041637 W JP2024041637 W JP 2024041637W WO 2025142253 A1 WO2025142253 A1 WO 2025142253A1
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WO
WIPO (PCT)
Prior art keywords
energy
amount
measurement
distribution
calibration curve
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PCT/JP2024/041637
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English (en)
Japanese (ja)
Inventor
誠 大元
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Fujifilm Corp
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Fujifilm Corp
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Publication of WO2025142253A1 publication Critical patent/WO2025142253A1/fr
Pending legal-status Critical Current
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01K—MEASURING TEMPERATURE; MEASURING QUANTITY OF HEAT; THERMALLY-SENSITIVE ELEMENTS NOT OTHERWISE PROVIDED FOR
    • G01K17/00—Measuring quantity of heat
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01L—MEASURING FORCE, STRESS, TORQUE, WORK, MECHANICAL POWER, MECHANICAL EFFICIENCY, OR FLUID PRESSURE
    • G01L1/00—Measuring force or stress, in general
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01L—MEASURING FORCE, STRESS, TORQUE, WORK, MECHANICAL POWER, MECHANICAL EFFICIENCY, OR FLUID PRESSURE
    • G01L5/00—Apparatus for, or methods of, measuring force, work, mechanical power, or torque, specially adapted for specific purposes
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N25/00—Investigating or analyzing materials by the use of thermal means

Definitions

  • 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.
  • 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.
  • the processor may obtain a second measurement distribution representing the distribution of second measurement values on the surface to be measured, and derive a distribution of the second energy amount from the second measurement distribution based on the selected second calibration curve.
  • the processor may obtain 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.
  • 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.
  • the first amount of energy may be pressure
  • the second amount of energy may be heat
  • the first measurement value is a value corresponding to the color density of a color-producing member that produces a color with a density corresponding to the applied pressure
  • the second measurement value corresponding to the second amount of energy may be an electrical resistance value output from a temperature sensor that outputs an electrical resistance value corresponding to the applied amount of heat.
  • 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.
  • a third aspect of the present disclosure is for a computer to execute a process of acquiring a first measurement value according 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.
  • a fourth aspect of the present disclosure is a method for manufacturing a workpiece using a jig, which includes obtaining a first measurement value that corresponds to a first amount of energy applied to the workpiece and that is dependent on a second amount of energy of a type different from the first amount of energy, deriving a 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 corresponds to the second amount of energy, and adjusting the jig so that a predetermined standard amount of first energy is applied to the workpiece based on the derived first amount of energy.
  • 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. 4 is a diagram showing an example of a temperature distribution on a processing surface under heating.
  • FIG. 13 is a diagram showing an example of pressure distribution on a processing surface under non-heating.
  • FIG. 13 is a diagram showing an example of pressure distribution on a processing surface under heating.
  • FIG. 2 illustrates an example of a hardware configuration of an information processing device.
  • FIG. 4 is a diagram showing an example of a first calibration curve.
  • FIG. 13 is a diagram showing an example of a second calibration curve.
  • FIG. 2 is a functional block diagram illustrating an example of a functional configuration of an information processing device.
  • 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. 4 is a diagram showing an example of a temperature
  • the information processing device 10 acquires a first measurement value corresponding to one type of energy (hereinafter referred to as the first energy) applied to the workpiece 80, measured using the color-developing member 50.
  • the information processing device 10 also acquires a second measurement value corresponding to another type of energy (hereinafter referred to as the second energy) applied to the workpiece 80, measured using the sensor device 60.
  • the information processing device 10 then derives the distribution of the first energy and the distribution of the second energy applied to the workpiece 80 based on the acquired first and second measurement values.
  • the color-developing member 50 for example, Prescale (registered trademark) (manufactured by Fujifilm Corporation), which develops color with a concentration distribution according to the applied pressure, can be used.
  • the prescale is a sheet-like support on which a color-developing agent layer in which microcapsules containing a colorless dye are dispersed and a color-developing agent layer containing a color developer are laminated.
  • 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 destroyed microcapsules and adsorbs to the color developer changes depending on the pressure applied to the prescale. Therefore, the prescale develops color at a concentration according to the applied pressure.
  • the sensor device 60 is a device in which multiple sensor elements are arranged on a sheet, and when a second energy such as pressure or heat is applied, the sensor elements output an electrical signal corresponding to the amount of energy applied.
  • the sensor device 60 can be a temperature measurement sheet in which multiple temperature sensors made of a material whose volume and electrical resistance value change depending on temperature are arranged in a matrix (see JP 2021-032806 A). By analyzing the electrical resistance value of each of the multiple temperature sensors, the surface distribution of the heat (temperature) applied to the temperature measurement sheet can be monitored.
  • the sensor device 60 for measuring temperature is not limited to a temperature measurement sheet equipped with the above-mentioned temperature sensor.
  • it may be a sheet on which multiple elements, such as resistance temperature detectors, thermocouples, and thermistors, that generate electrical changes such as electrical resistance values and potential differences in response to temperature changes, are formed.
  • the sensor device 60 is not limited to being formed as a single unit (for example, in a sheet shape).
  • the surface distribution of the second energy can also be monitored by individually placing multiple sensor elements at any location on the surface to be measured and analyzing the electrical changes of each of them.
  • FIG. 2 is a diagram showing the 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.
  • the measurement is not limited to the form in which the workpiece 80 and the color-forming member 50 or the sensor device 60 are overlapped, but 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 either the color-forming member 50 or the sensor device 60 on the other (e.g., 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.
  • Figure 3 shows an example of a temperature distribution 62 on the machining surface when heated.
  • Figure 4 shows an example of a pressure distribution 52A on the machining surface when not heated.
  • Figure 5 shows an example of a pressure distribution 52B on the machining surface when heated.
  • Figures 4 and 5 not only is the overall shape of the pressure distribution different between when not heated and when heated, but the magnitude of the pressure value (shown as density) also differs.
  • the temperature sensor measures an electrical resistance value corresponding to the volume expansion rate of the material in response to temperature changes, the volume of the material shrinks under pressure, which may reduce the accuracy of the measurement results (temperature distribution). Therefore, even if an attempt is made to select from a number of first calibration curves 18 (see FIG. 7) in which the relationship between the color density value of the color-producing member image 51 and the pressure value is predetermined for each temperature, it may not be possible to select an appropriate first calibration curve 18 because the temperature is not accurate. In other words, even if an attempt is made to correct the pressure value taking into account the temperature dependency of the prescale based on the measured temperature, the temperature measurement itself may not be accurate, and it may be difficult to derive the pressure value with high accuracy.
  • the information processing device 10 mutually corrects the distribution (pressure distribution) of the first energy obtained by the color-producing member 50 and the distribution (temperature distribution) of the second energy 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.
  • a prescale that develops a color with a density corresponding to the applied pressure is used as the color-developing member 50, and a temperature measurement sheet equipped with multiple temperature sensors that output an electrical resistance value corresponding to the applied amount of heat is used as the sensor device 60.
  • the first amount of energy is pressure.
  • the second amount of energy is an amount of 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 sensor.
  • the information processing device 10 includes a CPU (Central Processing Unit) 21, a non-volatile storage unit 22, and a memory 23 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 that various information can be exchanged between them.
  • the storage unit 22 is realized by a storage medium such as a hard disk drive (HDD), a solid state drive (SSD), and a flash memory.
  • the storage unit 22 stores an information processing program 27 in 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, expands it in the memory 23, and executes the expanded information processing program 27.
  • the CPU 21 is an example of a processor of the present disclosure.
  • the input unit 25 is for accepting user operations, and may be, for example, a touch panel, a button, 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).
  • the information processing device 10 for example, a smartphone, a tablet terminal, a wearable terminal, a personal computer, a server computer, etc. may be appropriately applied.
  • the first calibration curve 18 is a relationship between the first energy amount and the first measurement value, and shows a relationship according to the second energy amount. That is, the plurality of first calibration curves 18 are 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 plurality of first calibration curves 18 are 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 a manufacturer that manufactures the color-forming member 50. Note that the number and shape of the first calibration curves 18 shown in FIG. 7 are only an example, and the more the number, the better.
  • 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.
  • 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 just an example, and the more the number the better.
  • the information processing device 10 includes an acquisition unit 30, a selection unit 32, a derivation unit 34, and a control unit 36.
  • 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.
  • the acquisition unit 30 also 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. Specifically, the acquisition unit 30 acquires a second measurement distribution that represents the distribution of the second measurement values on the measured surface. 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 as the measurement conditions of the color density value (e.g., heating conditions and pressure conditions). Note that the measurement conditions being "same” 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 belongs and that does not go against the spirit of the technology of the present disclosure.
  • the second measurement value may be dependent on the first amount of energy.
  • the temperature sensor is pressure dependent, and therefore the electrical resistance value obtained from the temperature sensor is also pressure dependent.
  • Fig. 10 shows how the processing is repeated N times (N is an integer of 2 or more) for one part 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 of the table in Fig. 10.
  • the selection unit 32 selects, from among the multiple second calibration curves 19, the second calibration curve 19 that corresponds to the derived first energy amount. 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 that corresponds to 1.0 MPa.
  • the derivation unit 34 derives the second amount of energy from the second measurement value based on the selected second calibration curve 19.
  • the acquired electrical resistance value (second measurement value) is R1
  • the selected second calibration curve 19 is 1.0 MPa.
  • the derivation unit 34 derives the temperature (second amount of energy) to be 110 degrees.
  • the selection unit 32 selects, from among the multiple first calibration curves 18, the first calibration curve 18 that corresponds to the derived second amount of energy. For example, assume that the temperature (second amount of energy) 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.
  • 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.
  • the selection unit 32 selects, from among the multiple second calibration curves 19, the second calibration curve 19 that corresponds to the re-derived first amount of energy.
  • 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.
  • the selection unit 32 and 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.
  • 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.
  • the selection unit 32 may select a first calibration curve 18 corresponding to the second measurement distribution for each portion of the measured surface.
  • the derivation unit 34 may derive a 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.
  • the selection unit 32 may also select a second calibration curve 19 corresponding to the first measurement distribution for each portion of the measured surface.
  • the derivation unit 34 may derive a 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.
  • a calibration curve may be selected using representative values (e.g., the average, median, maximum, and minimum values) of the measurement distribution with a finer particle size.
  • the first calibration curve 18 corresponding to the second measurement distribution is selected for each portion of the measured surface corresponding to the grain size of the first measurement distribution.
  • the selection unit 32 identifies a representative value of the second measurement value for each portion of the measured surface corresponding to the grain size of the first measurement distribution based on the second measurement distribution, which has a finer grain size. Then, the selection unit 32 selects the first calibration curve 18 corresponding to the identified representative value of the second measurement value.
  • the second calibration curve 19 corresponding to the first measurement distribution is selected for each portion of the measured surface according to the grain size of the second measurement distribution.
  • the selection unit 32 identifies a representative value of the first measurement value for each portion of the measured surface according to the grain size of the second measurement distribution based on the first measurement distribution, which has a finer grain size. Then, the selection unit 32 selects the second calibration curve 19 corresponding to the identified representative value of the first measurement value.
  • 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 pressure distribution as an example of a two-dimensional graph representing the distribution of the first energy amount.
  • a heat map 72 representing temperature distribution as an example of a two-dimensional graph representing the distribution of the second energy amount.
  • control unit 36 may present a graph in which a two-dimensional graph representing the distribution of the first energy amount is superimposed on a two-dimensional graph representing the distribution of the second energy amount.
  • 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. In this way, the relationship between the pressure distribution and the temperature distribution becomes visually easier to understand.
  • control unit 36 may present the results of a comparison between a predetermined reference distribution for the first energy amount and the distribution of the derived first energy amount.
  • the reference distribution is, for example, the design distribution of applied pressure.
  • control unit 36 may present the results of a comparison between a predetermined reference distribution for the second energy amount and the distribution of the derived second energy amount.
  • the reference distribution is, for example, the design distribution of applied temperature.
  • the derived and reference pressure values, and the derived and reference temperature values are shown in table format for each of multiple measurement positions A to G on the surface to be measured.
  • the ratio of the derived value to the reference value is shown, with an excess being a positive value and a deficiency being a negative value.
  • Measurement positions A to G are also plotted on a heat map 74 that represents an overlap distribution. In this way, by presenting the derived values, reference values, and the results of comparing them, it becomes easier to understand the deviation of the derived values from the reference values.
  • step S22 the selection unit 32 selects, from among the multiple second calibration curves 19, a second calibration curve 19 that corresponds to the first amount of energy derived in step S20.
  • 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.
  • step S26 the derivation unit 34 determines whether or not 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 process repeats steps S18 to S24. In step S18, the selection unit 32 selects the first calibration curve 18 that corresponds to the second energy amount derived in the previous step S24.
  • step S28 the derivation unit 34 determines whether or not the derivation of the first energy amount and the second energy amount has been completed for all of the measured surfaces. 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.
  • step S28 when the derivation of the first energy amount and the second energy amount has been completed for the entire measured surface (step S28 is Y), the process proceeds to step S30. At this point, the derivation of the distribution of the first energy amount and the distribution of the second energy amount on the measured surface is completed.
  • step S30 the control unit 36 presents information corresponding to the distribution of the first energy amount and the distribution of the second energy amount on the measurement surface, and ends this information processing.
  • an information processing device 10 includes at least one processor, and the processor acquires a first measurement value that corresponds to a first amount of energy and that is dependent on a second amount of energy of a type different from the first amount of energy, and derives 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 corresponds to the second amount of energy.
  • 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.
  • an information processing device 10 includes at least one processor, which acquires a first measurement distribution representing a distribution on the measured surface of a first measurement value corresponding to a first amount of energy and dependent on a second amount of energy of a type different from the first energy, acquires a second measurement distribution representing a distribution on the measured surface of 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, and presents information corresponding to the first measurement distribution and the second measurement distribution.
  • 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.
  • the first energy amount and the second energy amount are both represented as surface distributions, but at least one of them may be represented by only one point rather than a surface distribution.
  • the first measurement value may be measured as a distribution
  • the second measurement value may be measured at only one point.
  • 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.
  • a thermometer that measures the temperature at a certain point may be applied as the sensor device 60.
  • the first measurement value may be measured at only one point, and the second measurement value may be measured as a distribution.
  • 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.
  • 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.
  • 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 (e.g., 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.
  • Appendix 8 The processor, selecting the first calibration curve corresponding to the second measurement distribution for each portion of the measurement surface according to the particle size of the first measurement distribution; The information processing device described in Appendix 7, wherein, when a grain size of the first measurement distribution is coarser than a grain size of the second measurement distribution, a representative value of the second measurement values is identified for each portion of the measured surface based on the second measurement distribution, and the first calibration curve corresponding to the identified representative value of the second measurement values is selected.
  • Appendix 9 The processor, obtaining a second measurement distribution representing a distribution of the second measurement values on the measurement surface; The information processing device according to claim 3, further comprising: deriving a distribution of the second energy amount from the second measurement distribution based on the selected second calibration curve.
  • Appendix 11 The processor, selecting the second calibration curve corresponding to the first measurement distribution for each portion of the measurement surface according to the particle size of the second measurement distribution; The information processing device described in Appendix 10, wherein, when the granularity of the second measurement distribution is coarser than the granularity of the first measurement distribution, a representative value of the first measurement values is identified for each portion of the measured surface based on the first measurement distribution, and the second calibration curve corresponding to the identified representative value of the first measurement values is selected.
  • the first amount of energy is pressure;
  • the information processing device according to any one of claims 1 to 11, wherein the second amount of energy is a heat amount.
  • Appendix 15 obtaining a first measurement value responsive 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 energy; an information processing program for causing a computer to execute a process of 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 in accordance with the second amount of energy.
  • a method for manufacturing a workpiece using a jig comprising: obtaining a first measurement value responsive 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 energy amount so that a predetermined reference first energy amount is applied to the workpiece.

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Abstract

Un dispositif de traitement d'informations comprend un processeur. Le processeur : acquiert une première valeur de mesure qui correspond à une première quantité d'énergie et dépend d'une seconde quantité d'énergie différente du type à partir de la première quantité d'énergie ; et détermine la première quantité d'énergie à partir de la première valeur de mesure sur la base de la relation entre la première quantité d'énergie et la première valeur de mesure, la relation correspondant à la seconde quantité d'énergie.
PCT/JP2024/041637 2023-12-28 2024-11-25 Dispositif de traitement d'informations, procédé de traitement d'informations, programme de traitement d'informations et procédé de fabrication de pièce Pending WO2025142253A1 (fr)

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JP2023223046 2023-12-28
JP2023-223046 2023-12-28

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WO2025142253A1 true WO2025142253A1 (fr) 2025-07-03

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Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JPS56109033U (fr) * 1980-01-24 1981-08-24
JP2006064600A (ja) * 2004-08-27 2006-03-09 Japan Aerospace Exploration Agency Ａ−ｐｒｉｏｒｉ／Ｉｎ−ｓｉｔｕＨｙｂｒｉｄ感圧塗料データ処理手法
JP2008232665A (ja) * 2007-03-16 2008-10-02 Fujifilm Corp 圧力解析システム
WO2020262329A1 (fr) * 2019-06-28 2020-12-30 富士フイルム株式会社 Ensemble de feuilles pour mesure de pression, feuille pour mesure de pression et liquide de dispersion
CN221898681U (zh) * 2024-03-22 2024-10-25 杭州共形场科技有限公司 一种压力敏感涂料的静态标定系统

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JPS56109033U (fr) * 1980-01-24 1981-08-24
JP2006064600A (ja) * 2004-08-27 2006-03-09 Japan Aerospace Exploration Agency Ａ−ｐｒｉｏｒｉ／Ｉｎ−ｓｉｔｕＨｙｂｒｉｄ感圧塗料データ処理手法
JP2008232665A (ja) * 2007-03-16 2008-10-02 Fujifilm Corp 圧力解析システム
WO2020262329A1 (fr) * 2019-06-28 2020-12-30 富士フイルム株式会社 Ensemble de feuilles pour mesure de pression, feuille pour mesure de pression et liquide de dispersion
CN221898681U (zh) * 2024-03-22 2024-10-25 杭州共形场科技有限公司 一种压力敏感涂料的静态标定系统

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
計測フィルムソリューション 圧力・熱・紫外線を、フィルムで簡単計測, 第１５回 オートモーティブ ワールド, 25 January 2023 (accession date), non-official translation (Measurement film solution: Easily measure pressure, heat, and UV light using this film solution, The 15th Automotive World) *

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