Lens molding method and lens molding system

Abstract

To mold lens with high accuracy.SOLUTION: A lens molding method is executed by an arithmetic unit making a lens molding machine mold a lens on the basis of a molding condition, and comprises: a process for acquiring a measured temperature at a temperature measurement portion of the lens molding machine; a process for creating input data containing lens design information and the measured temperature; a process for deriving an estimated temperature corresponding to the input data by inputting the input data into an AI model outputting the estimated temperature as an estimated value of the temperature during molding a lens material; a process for comparing the estimated temperature output from the AI model and an ideal temperature as an ideal value of the temperature during molding the lens material on the basis of the lens design information; and a process for controlling a heater of the lens molding machine for molding the lens on the basis of the comparison result.SELECTED DRAWING: Figure 11

Description

[Technical field]

[0001] The present disclosure relates to a lens molding method and system. [Background technology]

[0002] Conventionally, in the manufacture of lenses, a method has been put into practical use in which a heated glass material is held in a mold and pressurized to form a lens. For example, Patent Document 1 discloses a lens forming device that controls the heating temperature of the glass material so that the stress applied to the glass material does not exceed a certain value. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] JP 2008-285337 A Summary of the Invention [Problem to be solved by the invention]

[0004] In Patent Document 1, the temperature at a position away from the glass material is measured, and the heating temperature of the glass material is controlled based on the measured temperature. However, during molding, the temperature at a position away from the lens material does not necessarily match the actual temperature of the lens material itself. In order to mold a lens with higher precision, it is required to grasp the temperature of the lens material itself during molding, and to control the heating temperature of the lens material based on the measured temperature. Therefore, there is room for improvement in molding lenses with high precision.

[0005] The present disclosure has been devised in view of the above-mentioned conventional situation, and has an object to mold a lens with high precision. [Means for solving the problem]

[0006] The present disclosure provides a lens molding method executed by a computing device that causes a lens molding machine to mold a lens based on molding conditions, the lens molding method including the steps of: acquiring measured temperatures at temperature measurement locations on the lens molding machine; creating input data including design information of the lens and the measured temperatures; inputting the input data into an AI model that outputs a predicted temperature, which is a predicted value of the temperature during molding of the lens material, to derive a predicted temperature corresponding to the input data; comparing the predicted temperature output from the AI ​​model with an ideal temperature, which is an ideal value of the temperature during molding of the lens material based on the design information of the lens; and controlling a heater of the lens molding machine for molding the lens based on the comparison result.

[0007] The present disclosure also provides a lens molding system including a lens molding machine and a calculation device that causes the lens molding machine to mold a lens based on molding conditions, wherein the calculation device acquires measured temperatures at temperature measurement locations on the lens molding machine, creates input data including design information of the lens and the measured temperatures, derives a predicted temperature corresponding to the input data by inputting the input data into an AI model that outputs a predicted temperature that is a predicted value of the temperature during molding of the lens material, compares the predicted temperature output from the AI ​​model with an ideal temperature that is an ideal value of the temperature during molding of the lens based on the design information of the lens, and the lens molding machine controls a heater of the lens molding machine for molding the lens based on the comparison result, and stops the heater when molding of the lens is terminated.

[0008] Any combination of the above components, and conversion of the present disclosure into a method, device, system, storage medium, computer program, etc. are also valid aspects of the present disclosure. Effect of the Invention

[0009] According to the present disclosure, lenses can be molded with high precision. [Brief description of the drawings]

[0010] [Figure 1] FIG. 1 is a block diagram showing a configuration example of a lens forming system according to a first embodiment. [Diagram 2] A table diagram for explaining lens design information and lens molding conditions. [Diagram 3] Schematic showing the inputs and outputs of an AI model [Figure 4] Flowchart of AI model generation process [Diagram 5] Block diagram for explaining the data flow in the database construction process [Figure 6] Database construction process flowchart [Figure 7] Schematic diagram for explaining the database [Figure 8] FIG. 1 is a block diagram for explaining a data flow in an automatic optimization process according to a first embodiment. [Figure 9] Flowchart of automatic optimization process according to the first embodiment [Figure 10] FIG. 11 is a block diagram showing a configuration example of a lens forming system according to a second embodiment. [Figure 11] FIG. 11 is a block diagram for explaining a data flow of a temperature control process according to a second embodiment. [Figure 12] Flowchart of temperature control process according to the second embodiment DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0011] Hereinafter, various embodiments specifically disclosing the lens molding method and lens molding system according to the present disclosure will be described in detail with reference to the drawings as appropriate. However, more detailed explanation than necessary may be omitted. For example, detailed explanation of already well-known matters and duplicate explanation of substantially the same configuration may be omitted. This is to avoid the following explanation becoming unnecessarily redundant and to facilitate understanding by those skilled in the art. Note that the attached drawings and the following explanation are provided to enable those skilled in the art to fully understand the present disclosure, and are not intended to limit the subject matter described in the claims.

[0012] (Embodiment 1) [System Configuration] First, a configuration example of a lens forming system 1 according to the first embodiment will be described with reference to Fig. 1. Fig. 1 is a block diagram showing a configuration example of the lens forming system 1 according to the first embodiment.

[0013] The lens molding system 1 is a system for realizing work efficiency at the lens design stage and molding lenses with high precision by utilizing artificial intelligence (hereinafter referred to as "AI") technology in lens molding. The lens molding system 1 includes a calculation device 10, a database 20, a lens molding machine 30, and a shape measuring machine 40. Note that the "lens" according to this embodiment does not limit the application, shape, size, or device used. As long as the molding method described below is applicable, it may be applied to similar optical elements in general.

[0014] The arithmetic device 10 is a device that sets various conditions for molding a lens and executes various calculations, analyses, and the like. The arithmetic device 10 also functions as a control device that controls the lens molding machine 30 and the shape measuring machine 40. The arithmetic device 10 is configured using a general-purpose computer device such as a personal computer or a server computer. The arithmetic device 10 includes a processor 11, a memory 12, an input device 13, a display device 14, a communication device 15, and an external interface device 16. Each part of the arithmetic device 10 is connected to each other via an internal bus 17 so as to be able to communicate with each other.

[0015] The processor 11 is configured using, for example, a Central Processing Unit (hereinafter referred to as "CPU"), a Graphics Processing Unit (hereinafter referred to as "GPU"), a Micro Processing Unit (hereinafter referred to as "MPU"), a Digital Signal Processor (hereinafter referred to as "DSP"), a Field Programmable Gate Array (hereinafter referred to as "FPGA"), etc. The processor 11 realizes various functions by reading and executing various data and programs stored in the memory 12.

[0016] The memory 12 is a storage area for storing and holding various data, information, programs, etc. The memory 12 is composed of, for example, a Read Only Memory (hereinafter referred to as "ROM"), which is a non-volatile storage area, a Hard Disk Drive (hereinafter referred to as "HDD"), and a Random Access Memory (hereinafter referred to as "RAM"), which is a volatile storage area. The RAM is, for example, a work memory used during the operation of the arithmetic device 10. The ROM stores and holds, for example, programs for controlling the arithmetic device 10 in advance.

[0017] The input device 13 includes a keyboard, a mouse, a touch panel, or other input devices. The input device 13 accepts input of various data, information, and the like. The input device 13 is operated by, for example, a user who uses the lens forming system 1 to perform lens forming.

[0018] The display device 14 displays data generated by the processor 11, etc. The display device 14 displays, for example, various conditions set for lens molding, and various data acquired from the database 20, etc. The display device 14 is, for example, a display. The display device 14 may be provided separately from the arithmetic device 10.

[0019] The communication device 15 communicates with the lens forming machine 30 and the shape measuring machine 40 via a network (not shown) to transmit and receive various data or information. The communication device 15 may support both wired and wireless communication. The communication method used by the communication device 15 may be, for example, a Wide Area Network (hereinafter referred to as "WAN"), a Local Area Network (hereinafter referred to as "LAN"), Long Term Evolution (hereinafter referred to as "LTE"), mobile communication such as 5G, power line communication, short-range wireless communication such as Wi-Fi (registered trademark) and Bluetooth (registered trademark), or a combination of these.

[0020] The external interface device 16 is an interface device for transmitting and receiving various data or information to and from an external device (not shown). The connection with the external device by the external interface device 16 may be compatible with either a wired communication or a wireless communication method.

[0021] The database 20 stores various data such as lens design information and lens molding conditions. The database 20 will be described later with reference to Figs. 5, 6, and 7. Although the arithmetic device 10 and the database 20 are shown separately in Fig. 1, they may be configured as an integrated unit. In this case, the database 20 may be held in the memory 12, for example. The database 20 may be held on a cloud (not shown) or in an external device (not shown) so that the arithmetic device 10 can access it. The database 20 may be configured using a storage medium such as a flash memory, HDD, or Solid State Drive (hereinafter referred to as "SSD").

[0022] The lens molding machine 30 executes molding of lenses. The lens molding machine 30 is configured to include at least a processor 31, a memory 32, a heater 33, and a pair of a first mold 34 and a second mold 35. Various functions for molding lenses of the lens molding machine 30 are realized by cooperation between the processor 31 and the memory 32. Note that in the description of this specification, the expressions "first" and "second" are used merely to distinguish from other elements, and are not intended to be interpreted in a limiting manner.

[0023] The heater 33 heats the lens material when molding the lens. The heater 33 heats the lens material based on, for example, a molding temperature. The molding temperature will be described later with reference to FIG.

[0024] The pair of first and second dies 34 and 35 are arranged, for example, facing each other, and hold and pressurize the lens material by sandwiching it. As a result, the lens material is molded into a lens of a predetermined shape by the pair of first and second dies 34 and 35. The pair of first and second dies 34 and 35 pressurize the lens material based on, for example, a molding pressure. The molding pressure will be described later with reference to FIG. 2. A pair of dies for molding the lens may be prepared in advance by the user and used as the first and second dies 34 and 35. The dies for molding the lens may be formed as one unit. In addition, the lens molding machine 30 may be configured to be able to switch between pairs of the first and second dies 34 and 35 of different shapes.

[0025] The shape measuring machine 40 measures the shape of a molded lens. Here, "shape" may include dimensions, surface roughness, quality, etc. The shape measuring machine 40 is configured to include at least a processor 41 and a memory 42. Various functions of the shape measuring machine 40 for measuring the shape of a lens are realized by cooperation between the processor 41 and the memory 42.

[0026] Although a configuration example of the lens molding system 1 has been described above with reference to Fig. 1, the above-mentioned configuration example is merely an example, and the lens molding system 1, the computing device 10 constituting the lens molding system 1, the lens molding machine 30 and the shape measuring machine 40 may further include parts related to lens molding, etc. For example, the lens molding machine 30 may include a pressure sensor for measuring the pressure with which the pair of first and second molds 34 and 35 pressurize the lens material. Also, for example, the shape measuring machine 40 may include various devices for measuring the shape of the molded lens. Here, the description will be given with a focus on the functions related to this embodiment.

[0027] In order for the lens molding system 1 to mold a lens, it is necessary to set various conditions for molding the lens. Lens design information and lens molding conditions required for molding the lens will be described with reference to Fig. 2. Fig. 2 is a table diagram for explaining the lens design information and lens molding conditions according to the first embodiment. Note that the table diagram in Fig. 2 shows design information and molding conditions related to one lens.

[0028] The lens design information includes data on the lens shape, lens material, shape of first mold 34, material of first mold 34, shape of second mold 35, and material of second mold 35.

[0029] The data on the shape of the lens includes shape parameters as data. The shape of the lens is determined based on the shape parameters. For example, the shape parameter a1 indicates the radius of curvature of the first surface of a lens consisting of a first surface and a second surface. Also, for example, the shape parameter a2 indicates the thickness of the lens.

[0030] The lens material data includes various physical property values ​​of the material that constitutes the lens. The lens material may be a resin material or a glass material (in other words, optical glass). Examples of the lens resin material include acrylic resin and polycarbonate. For example, the physical property value b indicates the refractive index of the material. Hereinafter, the lens shape data and material data may be collectively referred to as lens data.

[0031] The data on the shape of the first mold 34 includes shape parameters as data. The shape of the first mold 34 is determined based on the shape parameters. For example, the shape parameter c1 indicates the radius of curvature of the molding surface of the first mold 34. Also, for example, the shape parameter c2 indicates the perimeter of the molding surface of the first mold 34.

[0032] The data on the material of the first mold 34 includes various physical property values ​​of the material constituting the first mold 34. Examples of the material of the first mold 34 include alloys such as stainless steel and super steel, silicon carbide, and glassy carbon. In addition, for example, the physical property value d is the thermal conductivity of the material constituting the first mold 34.

[0033] The data on the shape of the second mold 35 includes shape parameters as data. The shape of the second mold 35 is determined based on the shape parameters. For example, the shape parameter e1 indicates the radius of curvature of the molding surface of the second mold 35. Also, for example, the shape parameter e2 indicates the perimeter of the molding surface of the second mold 35.

[0034] The data on the material of the second mold 35 includes various physical property values ​​of the material constituting the second mold 35. Examples of the material of the second mold 35 include alloys such as stainless steel and super steel, silicon carbide, and glassy carbon. In addition, for example, the physical property value f is the thermal conductivity of the material constituting the second mold 35. Hereinafter, the data on the shape of the first mold 34, the data on the material of the first mold 34, the data on the shape of the second mold 35, and the data on the material of the second mold 35 may be collectively referred to as mold data.

[0035] The lens molding conditions include data on molding temperature, molding pressure, and molding time.

[0036] The lens molding machine 30 heats the lens material for molding the lens. When heating the lens material, the lens molding machine 30 controls the heater based on the molding temperature. For example, when the molding temperature is temperature g, the lens material is heated by the heater 33 at temperature g. However, the molding temperature may differ from the temperature during the actual molding of the lens material. For example, when the molding temperature is temperature g and the lens material is heated at temperature g, the temperature during the actual molding of the lens material may differ from temperature g. This is because the lens molding machine 30 controls the output of the heater 33 based on the temperature at a position away from the lens material in order to heat the lens material at temperature g. More specifically, since it is difficult to attach a temperature sensor (not shown) to the lens material, the lens molding machine 30 acquires a temperature measured by a temperature sensor attached to a position away from the lens material, for example, the first mold 34. The lens molding machine 30 compares the acquired temperature with temperature g, and when the acquired temperature is lower than temperature g, for example, increases the output of the heater 33. On the other hand, for example, when the acquired temperature is higher than the temperature g, the lens forming machine 30 reduces the output of the heater 33. The forming temperature may be set as an initial value in advance by, for example, a user who forms the lens, or may be adjusted by the computing device 10.

[0037] The lens molding machine 30 pressurizes the lens material to mold the lens. When pressurizing the lens material, the lens molding machine 30 controls the first mold 34 and the second mold 35 based on the molding pressure. For example, when the molding pressure is a pressure h, the lens material is pressed at the pressure h by being sandwiched between the first mold 34 and the second mold 35. The molding pressure may be an initial value set in advance by, for example, a user molding the lens, or may be adjusted by the computing device 10.

[0038] The molding time is the time during which the molding temperature and molding pressure are maintained. For example, when molding a lens, the lens material is heated to temperature g and pressurized to pressure h and maintained for time i.

[0039] Of the various data described with reference to Fig. 2, the lens shape data is a fixed parameter, as will be described in detail later. On the other hand, the lens material data, mold data, and molding conditions are variable parameters.

[0040] [AI model] In this embodiment, a trained AI model is used to efficiently adjust design information, molding conditions, or both, excluding the lens shape, for molding the lens. The AI ​​model may be generated by an arbitrary learning algorithm so as to output a predicted value of the temperature during molding of the lens material when input data created based on the lens design information and the lens molding conditions is input. The learning algorithm for generating the trained AI model according to this embodiment is not particularly limited, and machine learning including neural network technology such as Multi Layer Perceptron (hereinafter referred to as "MLP") and deep learning technology may be used. In addition, the AI ​​model may be generated for each lens molding machine (for example, lens molding machine 30). This is because the specifications may differ for each lens molding machine.

[0041] The AI ​​model 50 will be described with reference to Fig. 3 and Fig. 4. First, the input data and output data of the AI ​​model 50 will be described with reference to Fig. 3. Fig. 3 is a schematic diagram showing the input and output of the AI ​​model 50.

[0042] The input data to the AI ​​model 50 is the lens shape, the lens material, the shape and material of the first mold 34, the shape and material of the second mold 35, the molding temperature, the molding pressure, and the molding time. That is, in the present embodiment, the input data input to the AI ​​model 50 is the lens design information and lens molding conditions described with reference to FIG.

[0043] When input data for a certain lens is input, the AI ​​model 50 outputs a predicted value of the temperature during molding of the material of the lens. More specifically, when a lens is molded based on the design information and molding conditions that are the basis of the input data, the AI ​​model 50 outputs a predicted value of the temperature during molding of the material of the lens. Note that "during molding" means during the molding time. Hereinafter, the predicted value of the temperature during molding of the material of the lens may be referred to as the predicted temperature of the lens.

[0044] It may be difficult to accurately measure the temperature of the lens material during molding. For example, it is not practical to directly contact a temperature sensor with the lens material during molding. However, if the temperature of the lens material during molding can be grasped, the calculation device 10 can adjust the lens design information, the lens molding conditions, or both to be more suitable. The calculation device 10 acquires the predicted temperature of the lens output by the AI ​​model 50, and executes adjustment of the design information excluding the lens shape, the lens molding conditions, or both. Specifically, this will be described later with reference to FIG. 8 and FIG. 9.

[0045] Next, the generation of the AI ​​model 50 will be described with reference to Fig. 4. Fig. 4 is a flowchart of the generation process of the AI ​​model 50. Each process of the flowchart related to Fig. 4 is executed by the processor 11 of the arithmetic device 10. The processor 11 may use a simulation for the process of step St203 of the flowchart related to Fig. 4. The simulation used by the processor 11 for the process is not particularly limited, and for example, a physical simulation (particularly a thermal simulation or a structural simulation) may be used.

[0046] Processor 11 randomly sets the lens shape and material within a certain range (step St200). In other words, processor 11 randomly sets lens shape data, such as shape parameter a1, and lens material data, such as physical property value b, within a certain range. Setting the lens material data may be read as setting the lens material. This is because, when the material for molding the lens is set to a specific material, the lens material data, such as physical property values, are also set based on the specific material.

[0047] The processor 11 randomly sets the shape and material of the first mold 34 and the shape and material of the second mold 35 within a certain range for the lens whose shape and material have been set in the process of step St200 (step St201). In other words, the processor 11 randomly sets the shape data of the first mold 34, the material data of the first mold 34, the shape data of the second mold 35, and the material data of the second mold 35 within a certain range. Setting these data may be read as setting the first mold 34 and the second mold 35. This is because, when a pair of the first mold 34 and the second mold 35 is prepared in advance and it is set that the pair of the first mold 34 and the second mold 35 is used to mold the lens, these data are also set based on the first mold 34 and the second mold 35. The processor 11 randomly sets the design information of the lens within a certain range by the processes of steps St200 and St201.

[0048] Processor 11 randomly sets the molding temperature, molding pressure, and molding time within a certain range for the lens whose design information has been set by the processing of steps St200 and St201 (step St202). Processor 11 randomly sets the molding conditions for the lens within a certain range by the processing of step St202.

[0049] The processor 11 calculates the temperature of the lens material during molding when the lens is molded based on the design information set by the processes of steps St200 and St201 and the molding conditions set by the process of step St202 (step St203). The temperature calculated by the process of step St203 is a predicted temperature calculated by simulation.

[0050] The processor 11 generates learning data using the lens design information set by the processing of steps St200 and St201 and the molding conditions set by the processing of step St203 as input data and the predicted lens temperature calculated by the processing of step St204 as output data (step St204).

[0051] The processor 11 determines whether the number of pieces of learning data is sufficient (step St205). A threshold value for determining whether the number of pieces of learning data is sufficient, in other words, a specified value for the number of pieces of learning data required, may be set in advance by, for example, a user.

[0052] When the processor 11 determines that the number of pieces of learning data is not sufficient (step St205; NO), the processor 11 returns to step St201 and repeats the process. The processor 11 can generate a large amount of learning data at high speed by using a simulation.

[0053] When the processor 11 determines that the number of learning data is sufficient (step St205; YES), it generates the AI ​​model 50 using the generated learning data (step St206). Specifically, the processor 11 adjusts the parameters of the AI ​​model 50 based on the error between the output value output by the AI ​​model 50 when the input data, i.e., the lens design information and molding conditions, are input, and the output data, i.e., the predicted temperature of the lens. In other words, the processor 11 performs learning of the AI ​​model 50. As a result, when the lens design information and molding conditions are input as input data, the AI ​​model 50 outputs the predicted temperature of the lens as output data. After the process of step St206, the processor 11 ends this processing flow.

[0054] For ease of explanation, in this embodiment, the generated AI model 50 is stored in the memory 12 of the arithmetic device 10. However, this is not limiting, and the AI ​​model 50 may be stored, for example, in an external device (not shown) accessible to the arithmetic device 10. Since the learning process generally involves a high processing load, it is preferable to perform the process of generating the AI ​​model 50 at a different timing from the processes of building a database and molding a lens, which will be described later. Furthermore, from the viewpoint of distributing processing, etc., the process may be performed by separate devices.

[0055] [Database construction] Specifically, as will be described later with reference to FIG. 8 and FIG. 9, the arithmetic device 10 acquires the predicted temperature of the lens output by the AI ​​model 50, and adjusts the design information excluding the lens shape, the molding conditions of the lens, or both. The reason why the lens shape is excluded is because it is assumed that in the molding of the lens, the lens shape is determined first, and then the material and the mold are determined. The arithmetic device 10 adjusts the design information excluding the lens shape, the molding conditions of the lens, or both within an adjustable range. For example, the arithmetic device 10 performs adjustment so that the design information of the lens does not indicate a mold that cannot be used because it has not been made, or a material that cannot be used as a lens material. At this time, the arithmetic device 10 uses the database 20. The database 20 will be described with reference to FIG. 5, FIG. 6, and FIG. 7. First, the flow of various data when the database 20 is constructed will be described with reference to FIG. 5. FIG. 5 is a block diagram for explaining the flow of data in the database 20 construction process. The construction of the database 20 means storing data in the database 20 so that the arithmetic device 10 can utilize the database 20. In addition, when constructing the database, it is assumed that the AI ​​model 50 described with reference to FIGS. 3 and 4 is generated and is in a state in which it can be used by the computing device 10.

[0056] First, the description will be focused on data acquired or output by the arithmetic device 10. The arithmetic device 10 acquires lens design information and molding conditions by input to the input device 13 by user operation, communication with an external device, communication with a cloud on a network, etc. The processor 11 of the arithmetic device 10 creates input data to be input to the AI ​​model 50 based on the lens design information and molding conditions acquired by the arithmetic device 10. The configuration of the input data is the same as the input data shown in FIG. 3. The processor 11 inputs the input data to the AI ​​model 50 and acquires the predicted temperature of the lens output from the AI ​​model 50. The arithmetic device 10 outputs the lens molding conditions acquired by user operation, etc. to the lens molding machine 30. The arithmetic device 10 also outputs the lens design information acquired by user operation, etc., the molding conditions, and the predicted temperature of the lens output from the AI ​​model to the database 20.

[0057] The lens molding machine 30 molds a lens based on the lens molding conditions output from the arithmetic device 10. The lens molding machine 30 outputs analysis data obtained during lens molding to the database 20. An example of the analysis data is the internal stress of the lens during molding. In this case, the lens molding machine 30 may include a means for measuring the internal stress of the lens during molding. The output of the analysis data from the lens molding machine 30 to the database 20 may be performed via the arithmetic device 10. The output of the analysis data from the lens molding machine 30 to the database 20 may be omitted. The shape measuring machine 40 measures the shape of the molded lens. The shape measuring machine 40 outputs the measurement result to the database 20. In the lens molding system 1, the measurement result is treated as the molding result. Hereinafter, the measurement result may be referred to as the molding result.

[0058] The lens design information, molding conditions, predicted temperatures, analysis data, and molding results output to the database 20 are linked together and stored in the database 20. In this way, data is stored in the database 20 every time a lens is molded, and the database is constructed.

[0059] In order to simplify the explanation, some of the data flows are omitted in Fig. 5. For example, operation instructions from the arithmetic device 10 to the lens molding machine 30 and the shape measuring machine 40 are omitted. Furthermore, as will be described later with reference to Fig. 6, the lens design information, molding conditions, predicted temperature, analysis data, and molding results may be linked together by, for example, the arithmetic device 10. In this case, the lens molding results obtained by the shape measuring machine 40 are input to the arithmetic device 10 before being stored in the database 20.

[0060] Next, a processing flow when the database 20 is constructed will be described with reference to Fig. 6. Fig. 6 is a flowchart of the database 20 construction process. Each process in the flowchart of Fig. 6 is executed by the processor 11 of the arithmetic device 10. Note that in the description of this flow, a description of manual work in lens molding, such as preparation of the lens material, the first mold 34 and the second mold 35, etc. is omitted.

[0061] The processor 11 accepts an input of lens shape data by a user operation (step St300). The processor 11 acquires the lens shape data.

[0062] The processor 11 accepts input of lens material data and mold data by a user operation for the lens whose shape data has been acquired in the processing of step St300 (step St301). The processor 11 acquires lens design information through the processing of steps St300 and St301.

[0063] The processor 11 accepts an input of molding conditions by a user operation for the lens about which the design information is acquired by the processing of steps St300 and St301 (step St302). The processor 11 acquires the molding conditions of the lens by the processing of step St302.

[0064] The processor 11 creates input data to be input to the AI ​​model 50 based on the lens design information acquired in the processes of steps St300 and St301 and the lens molding conditions acquired in the process of step St302 (step St303).

[0065] The processor 11 inputs the input data created in the process of step St303 to the AI ​​model 50 (step St304).

[0066] The processor 11 acquires the predicted temperature of the lens output from the AI ​​model 50 in response to the input data in the process of step St304 (step St305).

[0067] The processor 11 causes the lens forming machine 30 to form a lens based on the lens forming conditions acquired in the process of step St302 (step St306). In this way, the lens is formed.

[0068] The processor 11 causes the shape measuring device 40 to measure the shape of the lens molded by the lens molding machine 30 in the process of step St306, and acquires the measurement result as the molding result (step St307). If the lens molded in the process of step St306 is molded according to the lens design information acquired in the processes of steps St300 and St301, the molding result is, for example, "good". On the other hand, if the molded lens is not molded according to the design information, for example, if the thickness of the molded lens is different from the thickness specified by the data of the lens shape, the molding result is, for example, "bad". Note that in this embodiment, an example is shown in which the molding result is defined in two categories, good and bad, but the present invention is not limited to this, and three or more stages of evaluation categories may be used. Details including the criteria for determining whether the molded lens is molded according to the design information will be described later with reference to FIG. 7.

[0069] The processor 11 associates the lens design information acquired in the processes of steps St300 and St301, the lens molding conditions acquired in the process of step St302, the lens predicted temperature acquired in the process of step St305, and the lens molding result acquired in step St307, and stores them in the database 20 (step St308). Then, the processor 11 ends this processing flow.

[0070] Next, an example of various data stored in the database 20 will be described with reference to Fig. 7. Fig. 7 is a schematic diagram for explaining the database 20.

[0071] The database 20 includes lens data, mold data, molding conditions, analysis data, AI output data, and molding results. The lens data includes data on the shape of the lens and data on the material. The lens data and mold data together indicate lens design information. For ease of explanation, FIG. 7 shows various data related to one lens. Specifically, FIG. 7 shows data related to a lens whose ID for identifying the lens is "100." The various data includes an ID for identifying the lens. Hereinafter, the ID for identifying the lens may be referred to as a lens ID.

[0072] The lens data includes a lens ID, lens material data, and lens shape data. The lens ID is expressed by a number, for example. In the example of FIG. 7, the lens design data includes material data and shape data of a lens with a lens ID of "100". More specifically, the physical property value b of the material of the lens with a lens ID of "100", and shape parameters a1 and a2 are stored in the database 20 as the lens data.

[0073] The mold data includes a lens ID, data on the material of the first mold 34, data on the material of the second mold 35, data on the shape of the first mold 34, and data on the shape of the second mold 35. In the example of Fig. 7, the database 20 stores, as mold data, a physical property value d of the material of the first mold, a physical property value f of the material of the second mold, a shape parameter c1 of the first mold, and a shape parameter e1 of the second mold for molding a lens with a lens ID of "100".

[0074] The molding condition data includes a lens ID, a molding machine ID for identifying a lens molding machine (e.g., lens molding machine 30), lens molding conditions, etc. In the example of Fig. 7, the molding machine ID of the lens molding machine for molding a lens with a lens ID of "100", temperature g as the molding temperature, and pressure h as the molding pressure are stored in database 20.

[0075] The analysis data includes the lens ID and various analysis results, such as the internal stress of the lens during molding.

[0076] The molding results include the lens ID and the lens measurement results by the shape measuring machine 40 corresponding to various items for evaluating the molded lens. In the example of FIG. 7, the lens measurement results for each of the first evaluation item and the second evaluation item for a lens with a lens ID of "100" are stored in the database 20. The first evaluation item may be, for example, the lens thickness. In this case, the measurement result of the lens thickness is stored in the database 20 as one of the molding results. In addition, the second evaluation item may be, for example, the radius of curvature of the first surface of the lens consisting of a first surface and a second surface. In this case, the measurement result of the radius of curvature of the first surface of the lens is stored in the database 20 as one of the molding results.

[0077] Evaluation criteria may be set for each of various items for evaluating the molded lens. For example, if the first evaluation item is the thickness of the lens, a reference value for the lens thickness and a range of error from the reference value may be set. If the measurement result of the lens thickness is within the range of error, the first evaluation item is passed. If all evaluation items are passed, the arithmetic device 10 judges that the molded lens is molded according to the design information, and determines that the molding result is "good". On the other hand, if even one of the evaluation items is failed, the arithmetic device 10 judges that the molded lens is not molded according to the design information, and determines that the molding result is "bad". The judgment result of whether the molding result is good or bad is not stored in the database 20, but the arithmetic device 10 can judge whether the molding result of the lens is "good" or "bad" from the molding result.

[0078] The various data stored in the database 20 described with reference to FIG. 7 are merely an example. Therefore, data other than the data shown in FIG. 7 may be further stored in the database 20. For example, the shape parameter c2 of the first mold may be stored as mold data. Also, for example, the time i may be stored as a molding condition as a molding time. Also, the names and configurations of the various data are not limited to these. For example, in this embodiment, analysis data is not essential as data stored in the database 20. In this embodiment, at least the lens design information, the lens molding conditions, the lens predicted temperature, and the lens molding results are linked to each other, in other words, stored in the database 20 together with the ID of the same lens.

[0079] [Automatic optimization of molding conditions] Next, with reference to Fig. 8 and Fig. 9, adjustment of design information excluding lens shape, lens molding conditions, or both, performed by the computing device 10 using the predicted temperature of the lens output by the AI ​​model 50 will be described. First, with reference to Fig. 8, the data flow during automatic optimization processing of the lens design information or lens molding conditions will be described. Fig. 8 is a block diagram for explaining the data flow of the automatic optimization processing according to the first embodiment.

[0080] First, the description will focus on data acquired or output by the arithmetic device 10. The arithmetic device 10 acquires lens design information and molding conditions through input to the input device 13 by user operation, communication with an external device, communication with a cloud on a network, etc. The processor 11 of the arithmetic device 10 creates input data to be input to the AI ​​model 50 based on the lens design information and molding conditions acquired by the arithmetic device 10. The processor 11 inputs the input data to the AI ​​model 50 and acquires the predicted temperature of the lens output from the AI ​​model 50.

[0081] The arithmetic device 10 acquires an ideal value of the temperature during molding of the lens from the database 20 based on the acquired design information of the lens. As described with reference to FIG. 5, FIG. 6, and FIG. 7, the processor 11 of the arithmetic device 10 causes the AI ​​model 50 to output the predicted temperature of the lens. In addition, the predicted temperature output from the AI ​​model 50 is stored in the database 20. The arithmetic device 10 causes the AI ​​model 50 to output the predicted temperature of the molded lens that was molded in the past and stored in the database 20, from the database 20. At this time, the arithmetic device 10 searches the database 20 for a molded lens that has the same or similar design information as the design information of the lens acquired by user operation or the like and has a molding result of "good". The criterion for determining whether the design information is similar or not may be set in advance by, for example, a user. For example, the arithmetic device 10 may be set to determine that the two lenses are similar in terms of thickness if the difference between the shape parameters that define the thickness among the shape data of each of the two lenses is within 1%. In this way, the arithmetic device 10 may determine that the design information of the two lenses is similar if, for example, the differences between various shape parameters are within a specified range. If the database 20 does not contain a lens corresponding to the molded lens having the same or similar design information as the design information of the lens acquired by user operation or the like, the user is notified of this fact. For example, the arithmetic device 10 causes the display device 14 to display that the corresponding lens is not in the database 20. The arithmetic device 10 acquires the predicted temperature of the molded lens stored in the database 20 based on the search result. The arithmetic device 10 handles the acquired predicted temperature as the ideal value of the temperature during molding of the material of the lens to be molded. In other words, the arithmetic device 10 acquires the predicted temperature stored in the database 20 as the ideal value of the temperature during molding of the material of the lens to be molded. Hereinafter, the ideal value of the temperature during molding of the material of the lens to be molded may be referred to as the ideal temperature.

[0082] The processor of the computing device 10 compares the ideal temperature of the lens acquired from the database 20 with the predicted temperature of the lens output from the AI ​​model 50. When the processor 11 determines that the design information excluding the shape of the lens, the molding conditions of the lens, or both need to be adjusted as a result of the comparison, the processor 11 adjusts the design information excluding the shape of the lens, the molding conditions of the lens, or both. The processor 11 may use any optimization method for adjusting the design information excluding the shape of the lens, the molding conditions of the lens, or both. For example, when the temperature difference between the ideal temperature and the predicted temperature is not within a specified range, the processor 11 changes at least one of the lens material, the shape of the first mold 34, the material of the first mold 34, the shape of the second mold 35, the material of the second mold 35, the molding temperature, the molding pressure, and the molding time within a specified range so that the temperature difference between the two is reduced. Note that when any data related to the first mold 34 or the second mold 35 is changed, data related to the first mold 34 and the second mold 35 other than the data may also be changed.

[0083] For example, if the temperature difference between the ideal temperature and the predicted temperature is not within a specified range and the predicted temperature is lower than the ideal temperature, the processor 11 adjusts the molding temperature to a temperature that is increased by a specified temperature from the currently set temperature. Then, the processor 11 compares the predicted temperature output by the AI ​​model 50 with respect to the input data including the adjusted molding temperature with the ideal temperature. If the temperature difference between the ideal temperature and the predicted temperature is not within a specified range and the predicted temperature is lower than the ideal temperature, the processor 11 again adjusts the molding temperature to a temperature that is increased by a specified temperature from the currently set temperature. By repeating such adjustments, lens design information and molding conditions are obtained such that the temperature difference between the predicted temperature and the ideal temperature is within the specified range. Note that an example of adjusting only the molding temperature has been shown, but this is merely one example for the purpose of simple explanation.

[0084] In addition, in order to adjust the design information excluding the lens shape and the molding conditions, the processor 11 may set an objective function to minimize the temperature difference between the ideal temperature and the predicted temperature, and perform optimization calculations using the design information excluding the lens shape and the molding conditions as variables. The processor 11 may use any optimization algorithm for the optimization calculations.

[0085] When the processor 11 of the computing device 10 adjusts the design information excluding the shape of the lens, the processor 11 again acquires the ideal temperature of the lens from the database 20 based on the adjusted design information. This is because the adjustment of the design information of the lens to be molded may change the molded lenses having the same or similar design information. However, for efficient adjustment, it is preferable that the ideal temperature for the lens to be molded is constant. For example, when it is determined whether the design information is the same or similar based only on the shape of the lens design information, the ideal temperature is constant because the data related to the shape is fixed. The processor 11 of the computing device 10 creates input data to be input to the AI ​​model 50 based on the adjusted design information or molding conditions of the lens. The processor 11 inputs the input data to the AI ​​model 50 and acquires the predicted temperature of the lens output from the AI ​​model 50. The processor 11 compares the ideal temperature with the predicted temperature, and adjusts the design information of the lens, the molding conditions, or both, based on the comparison result. In this way, processor 11 repeats creating input data, obtaining a predicted temperature, comparing the predicted temperature with an ideal temperature, adjusting the lens design information, molding conditions, or both, and obtaining the ideal temperature until adjustment of the lens design information, molding conditions, or both is completed.

[0086] When the adjustment between the lens design information and the molding conditions is completed, the processor 11 of the arithmetic device 10 outputs the lens molding conditions to the lens molding machine 30.

[0087] Next, a processing flow for automatic optimization of lens design information, lens molding conditions, or both will be described with reference to Fig. 9. Fig. 9 is a flowchart of automatic optimization processing according to embodiment 1. Each process in the flowchart according to Fig. 9 is executed by processor 11 of arithmetic device 10. Note that in the description of this flow, descriptions of manual operations in lens molding, such as preparation of lens materials, first mold 34, and second mold 35, are omitted.

[0088] The processor 11 accepts an input of lens shape data by a user operation (step St400). The processor 11 acquires the lens shape data.

[0089] The processor 11 accepts an input of an initial value of the lens material data by a user operation for the lens whose shape data was acquired in the processing of step St400 (step St401). The processor 11 acquires the lens material data as an initial value. This is because the lens material data can be adjusted in the subsequent processing.

[0090] The processor 11 acquires design values ​​in the process of step St400, and accepts input of initial values ​​of mold data by a user operation for the lens for which the initial values ​​of material data have been acquired in the process of step St401 (step St402). The processor 11 acquires the mold data as the initial values. This is because the mold data can be adjusted in subsequent processes. The processor 11 acquires lens design information through the processes of steps St400, St401, and St402.

[0091] The processor 11 accepts input of initial molding conditions by a user operation for the lens whose design information has been acquired by the processing of steps St400, St401, and St402 (step St403). The processor 11 acquires the molding conditions of the lens as initial conditions. This is because the molding conditions of the lens may be adjusted in subsequent processing. The processor 11 acquires the molding conditions of the lens by the processing of step St403.

[0092] The processor 11 acquires the ideal temperature of the lens from the database 20 based on the lens design information acquired in the processes of steps St400, St401, and St402 (step St404).

[0093] The processor 11 creates input data to be input to the AI ​​model 50 based on the lens design information acquired in the processing of steps St400, St401, and St402, and the lens molding conditions acquired in the processing of step St403 (step St405).

[0094] The processor 11 inputs the input data created in the process of step St405 to the AI ​​model 50 (step St406).

[0095] The processor 11 acquires the predicted temperature of the lens output from the AI ​​model 50 in response to the input data in the process of step St406 (step St407).

[0096] The processor 11 compares the predicted temperature acquired in the process of step St407 with the ideal temperature acquired in the process of step St404, and calculates the temperature difference (step St408).

[0097] The processor 11 determines whether the temperature difference calculated in the process of step St408 is within a specified range (step St409). The specified range may be set in advance by a user or the like, or may be set by the calculation of the calculation device 10.

[0098] When the processor 11 determines that the temperature difference calculated in step St408 is not within the specified range (step St409; NO), it adjusts at least one of the data of the material, the mold data, and the various data of the lens molding conditions (step St410). For example, when the predicted temperature is higher than the ideal temperature, the processor 11 changes the data of the material of the first mold 34 currently set as the initial value. Specifically, a material having a lower thermal conductivity than the thermal conductivity of the material of the first mold 34 currently set is newly set as the material of the first mold 34. In this case, the pair of the first mold 34 and the second mold 35 is changed to a different pair of existing molds. This is because, if only the material of the first mold 34 is changed, the corresponding mold can be used if it exists, but if the corresponding mold does not exist, for example, has not been made, the process must be carried out from the stage of making the mold. Note that an example of changing the mold data has been shown, but this is merely one example for the purpose of simple explanation. After the process of step St410, the processor 11 returns to step St404 and repeats the process.

[0099] When the processor 11 determines that the temperature difference calculated in step St408 is within the specified range (step St409; YES), the processor 11 causes the lens forming machine 30 to form a lens based on the lens forming conditions (step St411). Then, the processor 11 ends this processing flow.

[0100] In conventional lens molding, highly accurate lens molding is achieved by repeating a cycle that includes molding the lens, evaluating the molded lens, and adjusting various conditions based on the evaluation results. However, automatic optimization of the lens molding conditions as explained using Figures 8 and 9 enables efficient and highly accurate lens molding.

[0101] 9, the shape of the molded lens is measured by a shape measuring machine 40. The measurement results from the shape measuring machine 40 are linked to the design information and molding conditions of the molded lens and the predicted temperature of the lens output from the AI ​​model 50, and stored in the database 20. As a result, new data is added to the database 20.

[0102] (Modification of the first embodiment) In the above description of the first embodiment, an example was shown in which the processor 11 of the arithmetic device 10 acquires the ideal temperature of the lens from the database 20 based on the design information of the lens. However, this is not limited to this, and the processor 11 may acquire the ideal temperature of the lens from the database 20 based only on the shape of the lens among the design information of the lens. This is because, in the molding of the lens, various other conditions, such as the material and the mold, are determined based on the shape of the lens. In other words, the shape of the lens is fixed. As shown in the description of the processing of step St410 in the flowchart of FIG. 9, in the automated processing of the design information and molding conditions excluding the shape of the lens by the lens molding system 1, the data of the material of the lens, the mold data, and the molding conditions are subject to adjustment. However, the data of the shape of the lens is fixed and is not adjusted. When acquiring the ideal temperature of the lens from the database 20 based only on the shape of the lens, the processor 11 returns to the processing of step St405 after the processing of step St410 and repeats the processing. This is because, when the processor 11 acquires the ideal temperature based only on the shape of the lens among the design information of the lens, the ideal temperature does not change even if the material or the mold of the lens is changed. Processor 11 searches database 20 for molded lenses that have the same or similar shape as the lens to be molded and have a "good" molding result. Then, based on the search result, processor 11 obtains the predicted temperature of the molded lens stored in database 20 as the ideal temperature of the lens to be molded.

[0103] (Summary of the first embodiment) At least the following techniques are disclosed by the above description of the first embodiment. Note that, in parentheses, examples of components corresponding to the first embodiment are shown, but the present invention is not limited to these.

[0104] (Technology 1) A calculation device (e.g., calculation device 10) executes a method for automatically optimizing lens molding conditions, the method including the steps of: creating input data including lens design information and lens molding conditions; inputting the input data into an AI model (e.g., AI model 50) that outputs a predicted temperature, which is a predicted value of the temperature during molding of the lens material, to derive a predicted temperature corresponding to the input data; comparing the predicted temperature output from the AI ​​model with an ideal temperature, which is an ideal value of the temperature during molding of the lens material based on the lens design information; and adjusting at least one of the design information and the molding conditions based on the comparison result.

[0105] As a result, the arithmetic device can input input data including the lens design information and molding conditions into the AI ​​model, and obtain a predicted temperature, which is a predicted value of the temperature during molding of the material of the lens output from the AI ​​model. In addition, the arithmetic device can adjust at least one of the design information and molding conditions of the lens by comparing the predicted temperature with an ideal temperature, which is an ideal value of the temperature during molding of the material of the lens based on the lens design information. As a result, the arithmetic device can make the molding conditions of the lens more suitable, for example, without performing temporary molding of the lens (in other words, prototyping) for adjusting the molding conditions.

[0106] (Technology 2) In the automatic optimization method for lens molding conditions described in Technique 1, the computing device repeats a series of steps until the temperature difference calculated by comparing the predicted temperature with the ideal temperature falls within a specified range.

[0107] This allows the calculation device to adjust at least one of the design information and the molding conditions based on the temperature difference between the predicted temperature and the ideal temperature. Also, the calculation device can repeat the adjustment of at least one of the design information and the molding conditions until the temperature difference between the predicted temperature and the ideal temperature falls within a specified range.

[0108] (Technology 3) In the method for automatically optimizing lens molding conditions described in Technology 1 or 2, the design information includes the material and shape of the lens, and the material and shape of the molds (e.g., first mold 34 and second mold 35) for molding the lens, and the molding conditions include the molding temperature, molding pressure, and molding time.

[0109] Thus, the design information includes the material and shape of the lens, and the material and shape of the mold for molding the lens, and the molding conditions include the molding temperature, molding pressure, and molding time.

[0110] (Technology 4) In the method for automatically optimizing molding conditions for a lens according to any one of Techniques 1 to 3, the calculation device generates learning data for an AI model using a simulation, and generates an AI model using the learning data with a predicted temperature of the lens corresponding to the input data as output data.

[0111] This allows the computing device to generate learning data for generating an AI model through simulation. The computing device can generate a large amount of learning data at high speed by using, for example, physical simulation (particularly thermal simulation and structural simulation).

[0112] (Technology 5) In the automatic optimization method for lens molding conditions described in Technique 4, the learning data includes lens design information and lens molding conditions as input data, and includes a predicted lens temperature calculated by simulation as output data.

[0113] Thus, the learning data includes the lens design information and the lens molding conditions as input data, and the learning data includes the predicted lens temperature as output data.

[0114] (Technology 6) In the automatic optimization method for lens molding conditions described in any one of Techniques 1 to 5, the calculation device treats the predicted temperature of a molded lens, which is output by the AI ​​model during molding of a molded lens that is molded according to design information that is identical or similar to the design information of the lens, as an ideal temperature of the lens.

[0115] This allows the calculation device to treat the predicted temperature for the lens that has already been molded according to design information that is the same as or similar to the design information for the lens to be molded as the ideal temperature for the lens to be molded. Furthermore, by comparing the predicted temperature for the lens to be molded with the ideal temperature, the calculation device can adjust at least one of the design information and molding conditions for the lens.

[0116] (Technology 7) In the automatic optimization method for lens molding conditions described in Technique 6, the calculation device acquires the ideal temperature from a database (e.g., database 20) in which design information of a molded lens and a predicted temperature of the molded lens output from an AI model are associated and stored.

[0117] This allows the calculation device to obtain the ideal temperature for the lens to be molded from a database in which design information for the already molded lens and the predicted temperature for that already molded lens are stored in association with each other.

[0118] (Technology 8) In the automatic optimization method for molding conditions of a lens described in Technology 7, the database stores molding conditions of a molded lens and molding results of the molded lens, which are further linked to design information of the molded lens, and the calculation device uses the database to search for molded lenses whose design information is identical or similar to the design information of the lens and whose molding results are "good," and obtains the predicted temperature of the molded lens stored in the database as the ideal temperature based on the search results.

[0119] This allows the calculation device to use the database to search for already-molded lenses whose design information is the same or similar to that of the lens to be molded and whose molding results are "good." Furthermore, based on the search results, the calculation device can obtain the predicted temperature for the already-molded lens as the ideal temperature for the lens to be molded.

[0120] (Technology 9) In the automatic optimization method for lens molding conditions described in Technique 3, the computing device changes, based on the comparison result, either the design information excluding the lens shape or the lens molding conditions within a specified range so as to reduce a temperature difference between the ideal temperature and the predicted temperature.

[0121] This enables the calculation device to change, within a specified range, any of the design information and molding conditions other than the lens shape, i.e., the lens material, mold shape, mold material, molding temperature, molding pressure, and molding time, while keeping the lens shape fixed.

[0122] (Technology 10) A lens molding system (e.g., lens molding system 1) includes a lens molding machine (e.g., lens molding machine 30) and a calculation device (e.g., calculation device 10) that controls the lens molding machine, and the calculation device creates input data including lens design information and lens molding conditions, derives a predicted temperature corresponding to the input data by inputting the input data to an AI model (e.g., AI model 50) that outputs a predicted temperature that is a predicted value of the temperature during molding of the lens material, compares the predicted temperature output from the AI ​​model with an ideal temperature that is an ideal value of the temperature during molding of the lens material based on the lens design information, and adjusts at least one of the design information and the molding conditions based on the comparison result, and the lens molding machine molds a lens based on the adjusted design information and molding conditions.

[0123] This allows the lens forming system to obtain the same effect as that of Technology 1.

[0124] (Technology 11) In the lens molding system described in Technique 10, the lens molding system further includes a database (e.g., database 20) in which design information of an already molded lens, molding conditions, a predicted temperature output by the AI ​​model when molding the already molded lens, and molding results are each linked and stored, and when a new lens is molded, the calculation device adds the design information, molding conditions, predicted temperature, and molding results of the lens to the database, each linked to each other.

[0125] As a result, when the lens molding system molds a new lens, it can add the lens design information, molding conditions, predicted temperature, and molding results to the database by linking them together. This increases the amount of information stored in the database, making the database more useful for subsequent lens moldings.

[0126] (Embodiment 2) In the second embodiment, the lens molding system controls the output of a heater that heats the lens material for molding, in parallel with molding, based on the temperature of the lens material acquired successively during molding. In the first embodiment, an example was described in which the lens molding system 1 automatically adjusts the lens molding conditions, etc., at a stage before the lens is molded (e.g., the design stage). Meanwhile, in the second embodiment, the lens molding system molds a lens with high precision by controlling the output of the heater during molding. Note that in the description of the second embodiment, the description of matters similar to those described in the first embodiment will be omitted or simplified.

[0127] [System Configuration] FIG. 10 is a block diagram showing a configuration example of a lens molding system 1A according to the second embodiment. The lens molding system 1A in the second embodiment includes a calculation device 10A, a database 20, and a lens molding machine 30A. The calculation device 10A has a similar configuration to the calculation device 10 in the first embodiment. The calculation device 10A includes a processor 11A instead of the processor 11. The lens molding machine 30A includes a temperature sensor 36 in addition to the same configuration as the lens molding machine 30 in the first embodiment. The lens molding machine 30A includes a processor 31A instead of the processor 31. The operations of the processor 11A of the calculation device 10A and the processor 31A of the lens molding machine 30A will be described later with reference to FIG. 11.

[0128] The temperature sensor 36 is attached to a temperature measurement location of the lens molding machine 30A and measures the temperature at the temperature measurement location. The temperature measurement location is, for example, a predetermined location of the first mold 34 or the second mold 35. An example of the temperature sensor 36 is a thermocouple.

[0129] [Temperature control] The data flow during the temperature control process during lens molding will be described with reference to Fig. 11. Fig. 11 is a block diagram for explaining the data flow during the temperature control process according to the second embodiment.

[0130] First, the arithmetic device 10A acquires lens design information and molding conditions through input to the input device 13 by a user operation, communication with an external device, communication with a cloud on a network, or the like.

[0131] Furthermore, the arithmetic device 10A acquires the predicted temperature of the already molded lens stored in the database 20 based on the lens design information acquired by user operation or the like, as the ideal temperature of the lens to be molded.

[0132] The arithmetic device 10A outputs molding conditions acquired by user operations or the like to the lens forming machine 30A in order to cause the lens forming machine 30A to perform lens molding.

[0133] The processor 31A of the lens molding machine 30A outputs an output control instruction to the heater 33 based on the molding conditions in order to start heating the lens material. This drives the heater 33. After the heater 33 is driven, the processor 31A acquires the measured temperature of the temperature measurement location of the lens molding machine 30A from the temperature sensor 36 at regular intervals. The processor 31A outputs the measured temperature to the arithmetic device 10A. Note that the regular interval at which the processor 31A acquires the measured temperature from the temperature sensor 36 may be set in advance by a user or the like. For example, the processor 31A acquires the measured temperature from the temperature sensor 36 every few seconds.

[0134] The processor 11A of the arithmetic device 10A creates input data to be input to the AI ​​model 50 based on the lens design information and molding conditions acquired by user operation or the like, and the measured temperature of the temperature measurement location of the lens molding machine 30A acquired from the lens molding machine 30A. In this embodiment, the input data is the input data shown in FIG. 3 in which the molding temperature is replaced with the measured temperature. Specifically, the input data is various data on the shape of the lens, the material of the lens, the shape of the first mold 34, the material of the first mold 34, the shape of the second mold 35, the material of the second mold 35, the measured temperature of the temperature measurement location of the lens molding machine 30A, the molding pressure, and the molding time. The processor 11A inputs the input data to the AI ​​model 50 and acquires the predicted temperature of the lens output from the AI ​​model 50.

[0135] The processor 11A compares the predicted temperature with the ideal temperature. Based on the comparison result, the processor 11A transmits an instruction to the processor 31A of the lens forming machine 30A to control the output of the heater 33. For example, when the predicted temperature is lower than the ideal temperature, the processor 11A outputs an instruction to the processor 31A to increase the output of the heater 33. In addition, the processor 11A may calculate the temperature difference between the predicted temperature and the ideal temperature in order to compare the predicted temperature with the ideal temperature, or may set a threshold value for determining whether or not to control the output of the heater 33. The instruction to control the output of the heater 33 includes an instruction to maintain the current output, an instruction to increase the output, an instruction to decrease the output, and an instruction to stop the heater 33.

[0136] Processor 31A of lens molding machine 30A outputs an output control instruction to heater 33. As a result, the material of the lens being molded is heated to the same degree as before, heated more than before, or cooled. Then, the acquisition of the measured temperature at the temperature measurement point of lens molding machine 30A by processor 31A, output of the measured temperature by processor 31A to calculation device 10A, creation of input data using the measured temperature by processor 11A of calculation device 10A, acquisition of the predicted temperature of the lens output from AI model 50 by processor 11A, and output of an instruction to control the output of heater 33 from processor 11A to processor 31A are repeatedly executed at specified intervals.

[0137] Note that a part of the processing executed by the processor 11A of the arithmetic device 10A may be executed by the processor 31A of the lens forming machine 30A instead. For example, the processor 11A may output a predicted value and an ideal value of the lens temperature to the lens forming machine 30A. In this case, the processor 31A may compare the predicted value and the ideal value of the lens temperature and control the output of the heater 33 based on the comparison result.

[0138] Next, a process flow of temperature control during lens molding will be described with reference to Fig. 12. Fig. 12 is a flowchart of temperature control processing according to embodiment 2. Each process in the flowchart of Fig. 12 is executed by processor 11A of arithmetic device 10A. Note that in the description of this flow, a description of manual work in lens molding, such as preparation of lens material, first mold 34 and second mold 35, is omitted.

[0139] The processor 11A of the arithmetic device 10A receives the input of the lens shape data by the user operation (step St500). The processor 11A acquires the lens shape data.

[0140] The processor 11A of the arithmetic device 10A accepts input of lens material data, mold data, and molding conditions by a user operation for the lens whose shape data has been acquired in the processing of step St500 (step St501). The processor 11A acquires lens design information and molding conditions through the processing of steps St500 and St501.

[0141] The processor 11A of the arithmetic device 10A acquires the predicted temperature of the already molded lens from the database 20 as the ideal temperature of the lens to be molded, based on the lens design information acquired in the processes of steps St500 and St501 (step St502).

[0142] The processor 11A of the arithmetic device 10A causes the lens molding machine 30A to start molding the lens based on the lens molding conditions acquired in step St501 (step St503). The processor 11A outputs an instruction to the lens molding machine 30A to start molding the lens.

[0143] The processor 11A of the arithmetic device 10A causes the lens molding machine 30A to drive the heater 33 (step St504). For convenience of explanation, the processes of steps St503 and St504 are described separately, but in reality, the process of step St503 is executed, and thus the process of step St504 is also executed. That is, when the processor 31A of the lens molding machine 30A acquires an instruction to start molding a lens from the arithmetic device 10A in the process of step St503, the processor 31A drives the heater 33. The heater 33 heats the lens material based on the molding temperature included in the molding conditions. At this time, the lens molding machine 30A pressurizes the lens material based on the molding pressure by the first mold 34 and the second mold 35.

[0144] Processor 11A of arithmetic device 10A acquires the measured temperature of the temperature measurement location of lens molding machine 30A measured by temperature sensor 36 from lens molding machine 30A (step St505). More specifically, processor 31A of lens molding machine 30A first acquires the measured temperature of the temperature measurement location of lens molding machine 30A from temperature sensor 36 and outputs it to processor 11A of arithmetic device 10A. Then, processor 11A of arithmetic device 10A acquires the measured temperature of the temperature measurement location of lens molding machine 30A output from processor 31A of lens molding machine 30A.

[0145] Processor 11A of arithmetic device 10A creates input data to be input to AI model 50 based on the lens design information and molding conditions acquired in the processes of steps St500 and St501, and the measured temperature at the temperature measurement location of lens molding machine 30A acquired in the process of step St505 (step St506). The input data created in step St506 includes the lens design information, the molding pressure and molding time among the molding conditions, and the measured temperature at the temperature measurement location of lens molding machine 30A measured by temperature sensor 36.

[0146] The processor 11A of the arithmetic device 10A inputs the input data created in the process of step St506 to the AI ​​model 50 (step St507).

[0147] The processor 11A of the arithmetic device 10A acquires the predicted temperature of the lens output from the AI ​​model 50 in response to the input of the input data in the process of step St507 (step St508). The predicted temperature of the lens acquired by the processor 11A in step St508 is likely to be more accurate than the predicted temperature output from the AI ​​model 50 when the molding temperature is used as the input data. For example, when the molding temperature is used as the input data, there is a premise that the lens material is basically heated at a constant molding temperature during the molding time, apart from some temperature fluctuations. However, in reality, the temperature to which the lens material is heated may change, including such some temperature fluctuations. By using the actual measured temperature of the temperature measurement point of the lens molding machine 30A as input data, the predicted temperature of the lens at the timing when the measured temperature is measured can be acquired in a simultaneous manner.

[0148] The processor 11A of the arithmetic device 10A compares the ideal temperature acquired in the process of step St502 with the predicted temperature acquired in the process of step St508 (step St509).

[0149] Processor 11A of arithmetic device 10A outputs an instruction to lens molding machine 30A to control the output of heater 33 based on the comparison result between the predicted temperature and the ideal temperature in the process of step St509. As a result, processor 11A of arithmetic device 10A causes processor 31A of lens molding machine 30A to control the output of heater 33 (step St510). For example, when the predicted temperature of the lens is higher than the ideal temperature, processor 11A outputs an instruction to processor 31A to reduce the output of heater 33 in order to lower the temperature of the lens.

[0150] The processor 11A of the arithmetic device 10A determines whether or not to end the lens molding based on the molding time (step St511). More precisely, the processor 11A determines whether or not the elapsed time since the lens material was heated based on the molding temperature and pressurized based on the molding pressure in the process of step St504 has reached the molding time. If the processor 11A determines that the elapsed time has reached the molding time, it further determines to end the molding.

[0151] When the processor 11A of the arithmetic device 10A determines not to end the molding of the lens (step St511; NO), it determines whether or not the elapsed time since the measured temperature of the temperature measurement point of the lens molding machine 30A was acquired in the process of step St505 has reached a specified time (step St512). Note that the elapsed time since the measured temperature was acquired may be the elapsed time since the processor 11A of the arithmetic device 10 acquired the measured temperature, or may be the elapsed time since the processor 31A of the lens molding machine 30A acquired the measured temperature. In the description of this flowchart, the elapsed time since the measured temperature was acquired is the elapsed time since the processor 11A of the arithmetic device 10 acquired the measured temperature. Also, the specified time may be set in advance by a user or the like.

[0152] When the processor 11A of the arithmetic device 10 determines that the time elapsed since the measured temperature was acquired has reached the specified time (step St512; YES), the process returns to step St505 and repeats the process. As a result, a series of processes from measuring the temperature at the temperature measurement point of the lens forming machine 30A to controlling the output of the heater 33 is executed at specified time intervals, in other words, every specified time.

[0153] When the processor 11A of the arithmetic device 10 determines that the time elapsed since the measured temperature was acquired has not reached the specified time (step St512; NO), the processor 11A returns to step St511 and repeats the process.

[0154] When processor 11A of arithmetic device 10A determines that lens molding is to be terminated (step St511; YES), it causes lens molding machine 30A to terminate lens molding (step St513). Processor 31A of lens molding machine 30A stops heater 33, which causes the temperature of the lens to drop toward room temperature, in other words, the temperature of the surrounding environment. At this time, pressure applied to the lens by first mold 34 and second mold 35 is also stopped. Then, processor 11A of arithmetic device 10A terminates this processing flow.

[0155] Some of the processes in the flowchart shown in Fig. 12 may be executed in parallel with other processes. For example, the determination process of step St511 may be executed at all times after the heater 33 is driven in the process of step St504. This is to avoid the heating and pressurization of the lens material being executed for a specified time, i.e., beyond the molding time. Similarly, the determination process of step St512 may also be executed at all times after the measured temperature is acquired by the processor 11A of the arithmetic device 10A or the processor 31A of the lens molding machine 30A in the process of step St505.

[0156] In order to grasp the temperature of the lens material itself in parallel with the lens molding, the lens molding system 1A causes the AI ​​model 50 to output a predicted lens temperature using the measured temperature at a temperature measurement point of the lens molding machine 30A measured at a specified time interval. The lens molding system 1A realizes high-precision lens molding by simultaneously controlling the heating and cooling of the lens material while the lens design information and molding conditions are finalized and the lens is being molded based on the finalized molding conditions. Therefore, the lens molding system 1A is particularly useful at a stage where the lens design information and molding conditions are finalized, for example, at the mass production stage of lenses.

[0157] Furthermore, the lens molding system 1A may further include a shape measuring machine (for example, a shape measuring machine 40 included in the lens molding system 1). Although not shown in the process flow of FIG. 12, the shape of the lens molded by the lens molding machine 30A may be measured by the shape measuring machine. The measurement result of the lens by the shape measuring machine may be stored in the database 20 in association with the design information and molding conditions of the lens and the predicted temperature of the lens output from the AI ​​model 50. This adds new data to the database 20. The predicted temperature of the lens may be output multiple times by the AI ​​model 50. The predicted temperature stored in the database 20 may be, for example, an average value of multiple predicted temperatures output from the AI ​​model 50 during the molding of the lens. Alternatively, for example, multiple predicted temperatures output from the AI ​​model 50 during the molding of the lens may all be stored in the database 20. In this case, for example, the predicted temperature and the elapsed time from heating based on the molding temperature of the lens material may be stored in the database 20 in association with each other.

[0158] (Modification of the second embodiment) In the above description of the second embodiment, an example has been given in which arithmetic device 10A acquires the ideal temperature of the lens from database 20. However, this is not limiting, and lens molding machine 30A may acquire the ideal temperature of the lens from database 20. In this case, lens molding machine 30A may acquire lens design information from arithmetic device 10A in order to acquire the ideal temperature of the lens from database 20, for example. Also, in this case, lens molding machine 30A acquires a predicted temperature of the lens from arithmetic device 10A, compares the ideal temperature with the predicted temperature, and controls the output of heater 33 based on the comparison result.

[0159] Also, in the above description of the second embodiment, an example has been shown in which processor 11A of arithmetic device 10A acquires the ideal temperature of the lens from database 20 based on the lens design information. However, this is not limited to this, and processor 11A may acquire the ideal temperature of the lens from database 20 based only on the lens shape among the lens design information. When acquiring the ideal temperature of the lens from database 20 based on the lens shape, processor 11 uses database 20 to search for molded lenses that have an identical or similar shape to the shape of the lens to be molded and have a "good" molding result. Then, based on the search result, processor 11 acquires the predicted temperature of the molded lens stored in database 20 as the ideal temperature of the lens to be molded.

[0160] (Summary of the second embodiment) At least the following techniques are disclosed by the above description of the second embodiment. Note that, in parentheses, corresponding components in the second embodiment are illustrated, but the present invention is not limited to these.

[0161] (Technology 1) A calculation device (e.g., calculation device 10A) that causes a lens molding machine (e.g., lens molding machine 30A) to mold a lens based on molding conditions executes a lens molding method including the steps of acquiring measured temperatures at temperature measurement locations on the lens molding machine, creating input data including lens design information and the measured temperatures, inputting the input data into an AI model that outputs a predicted temperature, which is a predicted value of the temperature during molding of the lens material, to derive a predicted temperature corresponding to the input data, comparing the predicted temperature output from the AI ​​model (e.g., AI model 50) with an ideal temperature, which is an ideal value of the temperature during molding of the lens material based on the lens design information, and controlling a heater (e.g., heater 33) of the lens molding machine to mold the lens based on the comparison result.

[0162] As a result, the arithmetic device can input input data including lens design information and measured temperatures at temperature measurement points in the lens molding machine into the AI ​​model, and obtain a predicted temperature, which is a predicted value of the temperature during molding of the material of the lens, output from the AI ​​model. The arithmetic device can also control the output of the heater in the lens molding machine by comparing the predicted temperature with an ideal temperature, which is an ideal value of the temperature during molding of the material of the lens based on the lens design information. As a result, the arithmetic device can cause the lens molding machine to mold lenses with high precision.

[0163] (Technology 2) In the lens forming method described in Technique 1, the computing device repeats a series of steps at regular time intervals.

[0164] As a result, the calculation device repeats, at a specified time interval, the process from acquiring the measured temperature at the temperature measurement point of the lens molding machine to the process of controlling the heater. As a result, the heater output is controlled based on the specified time interval, for example, at intervals of several seconds, so that the lens is molded with high precision.

[0165] (Technology 3) In the lens molding method described in Technique 1 or 2, the design information includes the material and shape of the lens, and the material and shape of the molds (e.g., first mold 34 and second mold 35) for molding the lens, and the molding conditions include the molding temperature, molding pressure, and molding time.

[0166] Thus, the design information includes the material and shape of the lens, and the material and shape of the mold for molding the lens, and the molding conditions include the molding temperature, molding pressure, and molding time.

[0167] (Technology 4) In the lens forming method described in Technique 3, when the computing device determines that the time elapsed since the lens material was heated based on the forming temperature has reached the forming time, the computing device stops the heater.

[0168] Thereby, when the calculation device determines that the molding is completed based on the molding conditions, the calculation device can stop the heater, in other words, the calculation device can cause the lens molding machine to end the molding of the lens.

[0169] (Technology 5) In the lens forming method according to any one of Techniques 1 to 4, the calculation device generates learning data for the AI ​​model using a simulation, and generates an AI model using the learning data with a predicted temperature of the lens corresponding to the input data as output data.

[0170] This allows the computing device to generate learning data for generating an AI model through simulation. The computing device can generate a large amount of learning data at high speed by using, for example, physical simulation (particularly thermal simulation and structural simulation).

[0171] (Technology 6) In the lens molding method described in Technique 5, the learning data includes lens design information and lens molding conditions as input data, and includes a predicted lens temperature calculated by simulation as output data.

[0172] Thus, the learning data includes the lens design information and the lens molding conditions as input data, and the learning data includes the predicted lens temperature as output data.

[0173] (Technology 7) In the lens molding method described in any one of Techniques 1 to 6, the calculation device treats the predicted temperature of a molded lens, which is output by the AI ​​model when molding a molded lens that is molded according to design information that is identical or similar to the lens design information, as an ideal temperature of the lens.

[0174] This allows the calculation device to treat the predicted temperature for the lens that has already been molded according to design information that is the same as or similar to the design information for the lens to be molded as the ideal temperature for the lens to be molded. Furthermore, by comparing the predicted temperature for the lens to be molded with the ideal temperature, the calculation device can adjust at least one of the design information and molding conditions for the lens.

[0175] (Technology 8) In the lens molding method described in Technique 7, the calculation device acquires the ideal temperature from a database (e.g., database 20) in which design information of the molded lens and the predicted temperature of the molded lens output from the AI ​​model are associated and stored.

[0176] This allows the calculation device to obtain the ideal temperature for the lens to be molded from a database in which design information for the already molded lens and the predicted temperature for that already molded lens are stored in association with each other.

[0177] (Technology 9) In the lens molding method described in Technique 8, the database stores molding conditions for a molded lens and the molding results of the molded lens, which are further linked to design information of the molded lens. The computing device uses the database to search for molded lenses whose design information is identical or similar to the lens design information and whose molding results are "good," and obtains the predicted temperature of the molded lens stored in the database as the ideal temperature based on the search results.

[0178] This allows the calculation device to use the database to search for already-molded lenses whose design information is the same or similar to that of the lens to be molded and whose molding results are "good." Furthermore, based on the search results, the calculation device can obtain the predicted temperature for the already-molded lens as the ideal temperature for the lens to be molded.

[0179] (Technology 10) In the lens forming methods described in Techniques 1 to 9, the calculation device drives the heater based on the forming conditions, and then executes a series of steps.

[0180] As a result, the arithmetic device drives the heater based on the molding conditions, and then executes processes from the step of acquiring the measured temperature to the step of controlling the heater.

[0181] (Technology 11) A lens molding system (e.g., lens molding system 1A) includes a lens molding machine (e.g., lens molding machine 30A) and a calculation device (e.g., calculation device 10A) that causes the lens molding machine to mold a lens based on molding conditions. The calculation device acquires measured temperatures at temperature measurement points on the lens molding machine, creates input data including lens design information and the measured temperatures, derives a predicted temperature corresponding to the input data by inputting the input data to an AI model (e.g., AI model 50) that outputs a predicted temperature that is a predicted value of the temperature during molding of the lens material, compares the predicted temperature output from the AI ​​model with an ideal temperature that is an ideal value of the temperature during molding of the lens based on the lens design information, and the lens molding machine controls a heater (e.g., heater 33) of the lens molding machine for molding the lens based on the comparison result, and stops the heater when lens molding is terminated.

[0182] This allows the lens forming system to obtain the same effect as that of Technology 1.

[0183] (Technology 12) In the lens molding system described in Technique 11, the lens molding system further includes a database (database 20) in which design information of an already molded lens, molding conditions, a predicted temperature output by the AI ​​model when molding the already molded lens, and molding results are stored in a linked manner, and when a new lens is molded, the computing device adds the design information, molding conditions, predicted temperature, and molding results of the lens to the database in a linked manner.

[0184] As a result, when the lens molding system molds a new lens, it can add the lens design information, molding conditions, predicted temperature, and molding results to the database by linking them together. This increases the amount of information stored in the database, making the database more useful for subsequent lens moldings.

[0185] The functions of the various embodiments described above can also be realized by supplying programs and applications for realizing the functions of the various embodiments described above to a system or device via a network or a storage medium, and having one or more processors in a computer of the system or device read and execute the programs.

[0186] Furthermore, the functions of the various embodiments described above may be realized by a circuit that realizes one or more functions (for example, an Application Specific Integrated Circuit (hereinafter, referred to as "ASIC") or an FPGA).

[0187] Although various embodiments according to the present disclosure have been described above with reference to the drawings, it goes without saying that the present disclosure is not limited to such examples. It is clear that a person skilled in the art can think of various modifications, corrections, substitutions, additions, deletions, and equivalents within the scope of the claims, and it is understood that these also naturally belong to the technical scope of the present disclosure. In addition, the components in the various embodiments described above may be arbitrarily combined within the scope of the invention. [Industrial Applicability]

[0188] The present disclosure is useful as a lens molding method and a lens molding system. [Explanation of symbols]

[0189] 1. 1A Lens Molding System 10, 10A Calculation Unit 11, 11A, 31, 31A, 41 processors 12, 32, 42 memory 13 Input Devices 14 Display device 15. Communications Equipment 16 External interface device 17 Internal Bus 20 Database 30, 30A Lens forming machine 33 Heater 34 First Mold 35 2nd Mold 36 Temperature Sensor 40 Shape measuring machine 50 AI models

Claims

1. A lens molding method executed by a computing device that causes a lens molding machine to mold a lens based on molding conditions, comprising: acquiring a measured temperature at a temperature measurement location of the lens molding machine; creating input data including design information of the lens and the measured temperature; Deriving a predicted temperature corresponding to the input data by inputting the input data into an AI model that outputs a predicted temperature, which is a predicted value of a temperature during molding of the material of the lens; A step of comparing the predicted temperature output from the AI ​​model with an ideal temperature, which is an ideal value of a temperature during molding of a material of the lens based on design information of the lens; and controlling a heater of the lens forming machine for forming the lens based on the comparison result. Lens forming method.

2. Repeating the above steps at specified time intervals. The lens molding method according to claim 1 .

3. the design information includes a material and a shape of the lens, and a material and a shape of a mold for molding the lens; The molding conditions include molding temperature, molding pressure and molding time. The lens molding method according to claim 1 .

4. when it is determined that the elapsed time since the lens material was heated based on the molding temperature has reached the molding time, the heater is stopped. The lens molding method according to claim 3.

5. Generate training data for the AI ​​model using simulation; Using the learning data, the AI ​​model is generated with the predicted temperature of the lens corresponding to the input data as output data. The lens molding method according to claim 1 .

6. the learning data includes, as input data, design information of the lens and molding conditions of the lens, and includes, as output data, a predicted temperature of the lens calculated by the simulation; The lens molding method according to claim 5.

7. A predicted temperature of a molded lens outputted by the AI ​​model during molding of a molded lens that is molded according to design information identical or similar to the design information of the lens is treated as an ideal temperature of the lens. The lens molding method according to claim 1 .

8. The ideal temperature is acquired from a database in which design information of the molded lens and a predicted temperature of the molded lens output from the AI ​​model are associated and stored. The lens molding method according to claim 7.

9. In the database, molding conditions of the molded lens and molding results of the molded lens are stored while being further linked to design information of the molded lens, using the database, searching for the molded lens whose design information is identical or similar to the design information of the lens and whose molding result is "good", and obtaining, based on the search result, the predicted temperature of the molded lens stored in the database as the ideal temperature; The lens molding method according to claim 8.

10. After driving the heater based on the molding conditions, a series of the steps are performed. The lens molding method according to claim 1 .

11. A lens molding system comprising: a lens molding machine; and a calculation device that causes the lens molding machine to mold a lens based on molding conditions, The computing device includes: acquiring a measured temperature at a temperature measuring point of the lens molding machine; creating input data including design information of the lens and the measured temperature; deriving a predicted temperature corresponding to the input data by inputting the input data into an AI model that outputs a predicted temperature, which is a predicted value of the temperature during molding of the material of the lens; comparing the predicted temperature output from the AI ​​model with an ideal temperature, which is an ideal value of the temperature during molding of the lens based on design information of the lens; The lens forming machine includes: controlling a heater of the lens forming machine for forming the lens based on the comparison result; stopping the heater when the molding of the lens is completed; Lens forming system.

12. Further comprising a database in which design information of a molded lens, molding conditions, a predicted temperature outputted by the AI ​​model during molding of the molded lens, and molding results are stored in association with each other, the computing device, when a new lens is molded, adds design information, molding conditions, predicted temperature, and molding results of the lens to the database while linking them together; The lens molding system of claim 11.

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