Management apparatus, management system, management method, and management program

Abstract

Provided is a management apparatus for managing a processing device that processes substances, the management apparatus comprising: an acquisition unit for acquiring a plurality of processing definition information items including processing conditions to be executed by the processing device; and a control information generation unit for generating, on the basis of the plurality of processing definition information items, control information including time-series information for controlling the processing device. The acquisition unit may acquire restriction information related to restriction on the processing device. The control information generation unit may generate control information on the basis of the plurality of processing definition information items and the restriction information. The processing definition information items may include information regarding the types of substances to be processed by the processing device. The restriction information may include information regarding the number of types of substances or the amounts of substances that can be prepared by the processing device. The control information generation unit may generate control information on the basis of the sum of the number of types of substances in the processing definition information items and the sum of the number of types of substances in the restriction information.

Description

Management device, management system, management method, and management program

[0001] The present invention relates to a management device, a management system, a management method, and a management program.

[0002] Patent Document 1 states that "a technique suitable for predicting the properties of a molecular compound according to the molecular structure of the molecular compound is provided" (Abstract). Patent Document 2 states that "an information processing device that enables appropriate creation of a substrate processing schedule is provided" (Abstract). [Prior Art Documents] [Patent Documents] [Patent Document 1] JP 2024-25242 A [Patent Document 2] JP 2024-27312 A Problem to be solved

[0003] In a material processing device, it is preferable to be able to efficiently perform multiple processes, but it may be difficult to improve the efficiency of the processes by performing each process in chronological order. General disclosure

[0004] In a first aspect of the present invention, there is provided a management device that manages a processing device for processing a substance. The management device includes an acquisition unit that acquires a plurality of pieces of process definition information, each piece including a processing condition to be executed by the processing device, and a control information generation unit that generates control information, each piece including time-series information for controlling the processing device, based on the plurality of pieces of process definition information.

[0005] The acquisition unit may acquire restriction information relating to restrictions on the processing device. The control information generation unit may generate the control information based on the plurality of pieces of process definition information and the restriction information.

[0006] In any of the above management devices, the process definition information may include information on types of substances processed by the processing device. The restriction information may include information on the number of types of substances or amounts of substances that the processing device can prepare. The control information generator may generate the control information based on the sum of the number of types of substances in the process definition information and the sum of the number of types of substances in the restriction information, or may generate the control information based on the sum of the amounts of one type of substance in the process definition information and the sum of the amounts of the one type of substance in the restriction information.

[0007] In any of the above management devices, the limitation information may include processing limitation information relating to limitations on processing conditions. The control information generator may generate the control information based on the number of processes in the processing conditions and the number of limiting conditions, which is the number of processes in the processing limitation information.

[0008] In any of the above management devices, the control information generator may generate the control information so that the number of processes in the processing conditions is equal to or less than the number of limiting conditions.

[0009] In any of the above management devices, the restriction information may include processing restriction information regarding restrictions on processing conditions. The processing device may have a preparation device that prepares one or more types of ingredients to be processed by the processing device at a predetermined preparation temperature and preparation time. The processing restriction information may be information regarding an upper limit value of the preparation temperature or preparation time in the preparation device. If the predetermined preparation temperature or the predetermined preparation time exceeds the upper limit value, the control information generation unit may generate control information that sets the predetermined preparation temperature or the predetermined preparation time as the upper limit value.

[0010] In any of the above management devices, the acquisition unit may acquire common information in the plurality of pieces of process definition information, and the control information generation unit may generate the control information based on the common information.

[0011] In any of the above management devices, the control information generator may generate the control information based on the similarity of the process definition information.

[0012] In any of the management devices described above, the process definition information may include a type of substance to be processed by the processing device. When the type of substance in the first process definition information and the type of substance in the second process definition information are the same, the control information generator may generate control information for processing the first process definition information and the second process definition information in parallel or successively in time series.

[0013] In any of the above management devices, the processing conditions may include a processing temperature for the processing to be performed by the processing device, and the control information generator may generate the control information based on a similarity between a first processing temperature under the first processing conditions and a second processing temperature under the second processing conditions.

[0014] In any of the above management devices, when the difference between the first processing temperature in the first processing definition information and the second processing temperature in the second processing definition information is equal to or less than a predetermined threshold, the control information generation unit may generate control information to process the first substance in the first processing definition information and the second substance in the second processing definition information at the first processing temperature, and to process the first substance in the first processing definition information and the second substance in the second processing definition information at the second processing temperature.

[0015] In any of the above management devices, the control information generation unit may read at least two pieces of process definition information for each predetermined processing period, and generate control information for controlling the processing device during the processing period based on the read process definition information.

[0016] Any of the management devices described above may further include a margin calculation unit that calculates a processing margin of the processing device during a processing period when the processing device is controlled by the control information. The control information generation unit may generate additional control information based on the processing margin.

[0017] In any of the above management devices, the control information generation unit may have an evaluation value inference model that outputs a predicted value of the evaluation value when one input parameter in the processing definition information is input, by machine learning the relationship between the evaluation value of a product generated by processing by the processing device controlled by the control information and multiple parameters in the processing definition information, including processing conditions. The acquisition unit may acquire at least one of the multiple processing definition information based on the predicted value.

[0018] Any of the above management devices may further include a device control unit that controls the processing device based on the control information.

[0019] In any of the above management devices, the processing device may be an experimental device, the processing conditions may be experimental conditions, and the processing definition information may be experiment definition information.

[0020] In a second aspect of the present invention, there is provided a management system comprising any one of the processing devices described above and a management device.

[0021] In a third aspect of the present invention, there is provided a management method for managing a processing device for processing a substance. The management method includes an acquisition step in which an acquisition unit acquires a plurality of pieces of process definition information, each piece containing processing conditions to be executed by the processing device, and a control information generation step in which a control information generation unit generates, based on the plurality of pieces of process definition information, control information including time-series information for controlling the processing device.

[0022] In a fourth aspect of the present invention, there is provided a management program that causes a computer to function as any one of the management devices described above.

[0023] The above summary of the invention does not list all of the features of the present invention, and subcombinations of these features may also be inventions.

[0024] 1 is a diagram showing an example of a management system 300 according to an embodiment of the present invention. FIG. 2 is a diagram showing an example of a processing device 200. FIG. 3 is a block diagram showing an example of a management device 100 according to an embodiment of the present invention. FIG. 4 is a diagram showing an example of processing definition information 220. FIG. 5 is a diagram showing an example of management of the processing device 200 by the management device 100. FIG. 6 is a diagram showing an example of control information Ic. FIG. 7 is a diagram showing an example of the control information Ic. FIG. 8 is a diagram showing another example of the control information Ic. FIG. 9 is a diagram showing an example of an evaluation value Ev of a product G generated by processing by the processing device 200. FIG. 10 is a diagram showing an example of learning by the control information generator 20. FIG. 11 is a diagram showing an example of inference by the evaluation value inference model 22. FIG. 11 is a conceptual diagram showing an example of a relationship between a plurality of parameters Pr and a predicted value Pv. FIG. 12 is a diagram showing another example of the control information Ic. FIG. 13 is a diagram showing an example of a predicted value Pv inferred by the evaluation value inference model 22. FIG. 14 is a diagram showing an example of a management system 300 according to an embodiment of the present invention. FIG. 15 is a diagram showing another example of the management system 300 according to an embodiment of the present invention. FIG. 16 is a diagram showing another example of the management system 300 according to an embodiment of the present invention.

[0025] The present invention will be described below through embodiments of the invention, but the following embodiments do not limit the scope of the invention as claimed. Furthermore, not all of the combinations of features described in the embodiments are necessarily essential to the solution of the invention.

[0026] 1 is a diagram showing an example of a management system 300 according to an embodiment of the present invention. The management system 300 includes a management device 100 and a processing device 200. The processing device 200 may include an evaluation device 250.

[0027] The processing device 200 processes a material. Processing a material refers to changing the state of the material. Changing the state of a material may refer to changing the shape of the material, or changing at least one of the material's properties and chemical formula by chemical reaction, firing, drying, kneading, or the like. Changing the shape of a material may include shaping the material into a predetermined shape. Shaping the material into a predetermined shape may include shaping the material into a film or the like, etching the material to form grooves, or etching the material into wiring, etc.

[0028] Management device 100 manages processing device 200. Managing processing device 200 refers to managing the start time, end time, processing time, processing sequence, processing temperature, etc. of processing of a substance in processing device 200, or managing the selection of the type of substance to be processed in processing device 200 or the amount of substance.

[0029] One or more users 400 (users 400-1 to 400-z, z is an integer) of management device 100, processing device 200, or management system 300 input process definition information 220 to management device 100. Process definition information 220 is information that defines the process in processing device 200. Process definition information 220 is information that indicates the content of the process of a substance that user 400 desires in processing device 200. Details of process definition information 220 will be described later.

[0030] In the management device 100, control information Ic for controlling the processing device 200 is generated based on the plurality of pieces of process definition information 220. The processing device 200 is controlled by the control information Ic. The processing device 200 may transmit the results of processing in the processing device 200 or the results of evaluation in the evaluation device 250 to the management device 100. This can improve the processing throughput in the processing device 200.

[0031] FIG. 2 is a diagram showing an example of a processing apparatus 200. The processing apparatus 200 of this example is an experimental apparatus that mixes and prepares multiple types of substances and then dries the prepared substances. The processing apparatus 200 of this example has a raw material storage section 202, an acquisition and input section 204, multiple preparation devices 206, multiple furnaces 208, and an evaluation apparatus 250. The raw material storage section 202 stores the raw materials to be processed by the processing apparatus 200. The processing apparatus 200 has multiple raw material storage sections 202. In this example, the processing apparatus 200 has k (k is an integer of 2 or greater) raw material storage sections 202 (raw material storage sections 202-1 to 202-k). In this example, different types of substances are stored in the raw material storage sections 202-1 to 202-k, respectively. In this example, a liquid substance is stored in the raw material storage section 202.

[0032] In this example, processing apparatus 200 has m (m is an integer of 2 or more) preparation devices 206 (preparation devices 206-1 to 206-m). In this example, processing apparatus 200 has n (n is an integer of 2 or more) furnaces 208 (furnaces 208-1 to 208-n).

[0033] The acquisition input unit 204 acquires the raw materials stored in the raw material storage unit 202. The acquisition input unit 204 may acquire predetermined amounts of the first raw material and the second raw material, respectively, so that the first raw material stored in the first raw material storage unit 202 and the second raw material stored in the second raw material storage unit 202 have a predetermined mass ratio or volume ratio. The first raw material storage unit 202 is any one of the plurality of raw material storage units 202 (e.g., raw material storage unit 202-1), and the second raw material storage unit 202 is any other one of the plurality of raw material storage units 202 (e.g., raw material storage unit 202-2).

[0034] The acquisition input unit 204 inputs the acquired raw materials into the preparation device 206. The acquisition input unit 204 may input predetermined amounts of the first raw material and the second raw material acquired from the raw material storage unit 202 into at least one preparation device 206. In this example, the acquisition input unit 204 is a pipette.

[0035] Predetermined amounts of the first ingredient and the second ingredient may be mixed in at least one preparation device 206. The mixed ingredients may be prepared in the preparation device 206 at a predetermined preparation temperature Te1 (described below) and preparation time Tm1 (described below).

[0036] The furnace 208 dries the raw materials prepared in the preparation device 206. The furnace 208 dries the raw materials to produce the substance to be produced. The raw materials may be dried in the furnace 208 at a predetermined drying temperature Te2 (described below) and drying time Tm2 (described below). The evaluation device 250 evaluates a product G (described below) produced in the furnace 208.

[0037] 3 is a block diagram showing an example of a management device 100 according to an embodiment of the present invention. The management device 100 includes an acquisition unit 10 and a control information generation unit 20. The management device 100 may include a capacity reserve calculation unit 30, a device control unit 40, a storage unit 50, and a processing unit 60.

[0038] A part or the whole of the management device 100 may be realized by a computer. The processing unit 60 may be the CPU (Central Processing Unit) of the computer. The control information generation unit 20, the spare capacity calculation unit 30, the device control unit 40, and the processing unit 60 may be the CPU (Central Processing Unit) of the computer. When the management device 100 is realized by a computer, a program for causing the computer to function as the management device 100 may be installed on the computer, and a program for causing the computer to execute the management method described below may be installed on the computer.

[0039] The management device 100 manages the processing device 200. As described above, managing the processing device 200 refers to managing the start time, end time, processing time, processing sequence, or processing temperature of the processing of materials in the processing device 200. When there are multiple types of materials, managing the processing device 200 refers to managing whether a first type of material and a second type of material are processed in parallel or separately, and, if they are processed separately, the processing sequence or interval, etc. The first type of material is any one of the multiple types of materials, and the second type of material is any other one of the multiple types of materials. In the example of FIG. 2 , for example, managing the type and amount of one or more raw materials, the selection of a preparation device 206 (one of preparation devices 206-1 to 206-m) to which the raw materials are input, the selection of an oven 208 (one of ovens 208-1 to 208-n) to dry the prepared raw materials, and the start time, end time, and drying temperature in the oven 208.

[0040] FIG. 4 is a diagram showing an example of process definition information 220. In this example, the process definition information 220 is experiment definition information that defines an experiment to be executed by the experimental device, which is the processing device 200. FIG. 4 shows four pieces of process definition information 220 (process definition information 220-1 to process definition information 220-4). A process definition information 220 may be defined for each of multiple users 400. In this example, the content of the processes desired by the four users 400 (user 400-1 to user 400-4) is defined in process definition information 220-1 to process definition information 220-4, respectively.

[0041] The process definition information 220 includes process conditions 222 to be executed by the processing device 200. In FIG. 4, the process conditions 222 are surrounded by a bold frame. In this example, the process conditions 222 are experimental conditions to be executed by the experimental device, which is the processing device 200. In this example, the process definition information 220-1 to 220-4 include process conditions 222-1 to 222-4, respectively. The process conditions 222 are conditions related to a process that changes the state of a substance. The process conditions 222 may include a process temperature or a process time in a process to be executed by the processing device 200. The process conditions 222 may further include a start time, an end time, or a process order of the process in the processing device 200. In this example, the process conditions 222 include a preparation temperature Te1 and a preparation time Tm1 in the preparation device 206, and a drying temperature Te2 and a drying time Tm2 in the furnace 208. If the processing device 200 is, for example, a device that performs a process of exposing a photosensitive resin to light, the processing conditions 222 may include exposure intensity and exposure time. Also, if the processing device 200 is, for example, a device that performs film stretching, the processing conditions 222 may include the film stretch ratio.

[0042] The process definition information 220 may include information on the number u (1≦u≦m) of the preparation device 206 to which the raw materials are input, information on the type of substance to be processed by the processing device 200 (in this example, information on the type and amount of raw materials input to the preparation device 206), information on the sample number s (described below) to be dried in the furnace 208, and information on the number v (1≦v≦n) of the furnace 208 in which the sample to be dried is dried. If the user 400 defining the process definition information 220 does not desire specific numbers for the number u and the number v, the process definition information 220 does not need to include information on the number u and the number v. In this example, cases in which the user 400 does not desire a specific number u or number v are indicated by blank spaces.

[0043] The process definition information 220 may include a sample number s. The sample number s may be defined for each of the multiple process definition information 220. In this example, four samples (A1 to A4) are defined in the process definition information 220-1, three samples (B1 to B3) are defined in the process definition information 220-2, two samples (C1 and C2) are defined in the process definition information 220-3, and one sample (D1) is defined in the process definition information 220-4.

[0044] The acquisition unit 10 (see FIG. 3 ) acquires multiple pieces of process definition information 220. The process definition information 220 may be determined in advance by a user 400 (in this example, users 400-1 to 400-4). The user 400 may input the determined process definition information 220 to the management device 100. The acquisition unit 10 may acquire the input process definition information 220. The storage unit 50 may store the process definition information 220 acquired by the acquisition unit 10.

[0045] FIG. 5 is a diagram illustrating an example of management of the processing device 200 by the management device 100. In this example, there are four users 400 (user 400-1 to user 400-4). The acquisition unit 10 acquires process definition information 220. In this example, each user 400 defines process definition information 220 and inputs the defined process definition information 220 to the management device 100. In the management device 100, the control information generation unit 20 (see FIG. 3) generates control information Ic (described below) based on the multiple pieces of process definition information 220. The device control unit 40 (see FIG. 3) controls the processing device 200 based on the control information Ic (described below). The processing device 200, controlled based on the control information Ic (described below), generates a product G (described below). The evaluation device 250 (see FIG. 1) evaluates the generation unit G (described below). An evaluation value Ev (described below) of the evaluated product G (described below) is stored in the storage unit 50 (see FIG. 3).

[0046] The period from when the acquisition unit 10 acquires the process definition information 220 to when the product G is evaluated is defined as one cycle of the processing period T in the processing apparatus 200. FIG. 5 shows a first cycle and a second cycle of the processing period T. In the second cycle, the acquisition unit 10 may acquire the process definition information 220 based on a predicted value Pv (described later) in addition to the process definition information 220 input by the user 400. The number x of cycles of the processing period T may be multiple. The number x of cycles of the processing period T may be predetermined by the user 400. Note that, although FIG. 5 shows that the process definition information 220 based on the predicted value Pv (described later) is acquired after the process definition information 220 input by the user 400 is acquired, this order may be reversed.

[0047] 6 and 7 are diagrams showing examples of control information Ic. Fig. 6 shows an example of control information Ic related to the control of the preparation device 206. The control information generator 20 (see Fig. 3) generates the control information Ic based on a plurality of pieces of process definition information 220. For example, the control information generator 20 generates control information Ic1 (see Fig. 6) by integrating or editing two or more pieces of process definition information 220 from the plurality of pieces of process definition information 220.

[0048] The control information Ic is information that causes the processing device 200 to execute all processes defined in the multiple pieces of process definition information 220 that are the source of the integration. The management device 100 may generate control information Ic that integrates processes commonly included in two or more pieces of process definition information 220 into a single process. The management device 100 may generate control information Ic that defines the timing at which each process should be executed and the devices that should execute each process, so that the multiple processes defined in the multiple pieces of process definition information 220 can be executed efficiently. In this example, the control information generation unit 20 generates control information Ic1 that integrates the process definition information 220-1, the process definition information 220-2, and the process definition information 220-4. The control information generation unit 20 may also generate control information Ic2 related to one piece of process definition information 220. In this example, the control information generation unit 20 generates control information Ic2 (see FIG. 7) related to the process definition information 220-3.

[0049] The control information Ic may include a sample number s'. The sample number s' is one of the sample numbers s in the process definition information 220, and is the number of the sample after integrating or editing multiple pieces of process definition information 220. 6 and 7 show the correspondence between the sample number s' and the sample number s in FIG. 4.

[0050] The control information generator 20 (see FIG. 3) may determine whether two or more pieces of process definition information 220 are inconsistent. A conflict between two or more pieces of process definition information 220 means that the two or more pieces of process definition information 220 cannot be integrated or edited to satisfy a predetermined condition. The condition may indicate a process that can be executed by the processing device 200.

[0051] For example, in one cycle of the processing apparatus 200, only one type of preparation process can be performed by one preparation device 206. In this case, if two pieces of process definition information 220 include multiple types of preparation processes in a common cycle and a common preparation device 206, the two pieces of process definition information 220 are inconsistent with each other. For example, in the example of FIG. 4, process definition information 220-1 specifies the sixth (u=6) preparation device 206 for sample number A3, while process definition information 220-3 specifies the sixth (u=6) preparation device 206 for sample number C1. In such a case, the control information generator 20 (see FIG. 3) determines that the process definition information 220-1 and the process definition information 220-3 are inconsistent. For example, in the example of FIG. 4, process definition information 220-1 specifies the sixth (u=6) preparation device 206 for sample number A3, while process definition information 220-4 specifies the fourth (u=4) preparation device 206 for sample number D1. In such a case, the control information generation unit 20 (see FIG. 3) determines that there is no contradiction between the process definition information 220-1 and the process definition information 220-4. The control information generation unit 20 does not need to integrate or edit two or more pieces of process definition information 220 that are determined to be contradictory.

[0052] The control information generator 20 (see FIG. 3) may generate control information Ic by integrating two or more pieces of non-contradictory processing definition information 220. In the example of FIG. 4, the processing definition information 220-1, processing definition information 220-2, and processing definition information 220-4 are not mutually contradictory. Therefore, the control information generator 20 generates control information Ic (control information Ic1) by integrating the processing definition information 220-1, processing definition information 220-2, and processing definition information 220-4.

[0053] When the control information generation unit 20 (see FIG. 3) integrates first process definition information 220 (e.g., process definition information 220-1) and second process definition information 220 (e.g., process definition information 220-2), if the number u of the preparation equipment 206 or the number v of the furnace 208 is specified in the first process definition information 220 and the number u of the preparation equipment 206 or the number v of the furnace 208 is not specified in the second process definition information 220, the control information generation unit 20 may generate control information Ic that specifies, for the second process definition information 220, the preparation equipment 206 with number u or the furnace 208 with number v, excluding the number u or number v specified in the first process definition information 220. The first process definition information 220 is any one of the multiple process definition information 220 (for example, process definition information 220-1), and the second process definition information 220 is any other one of the multiple process definition information 220 (for example, process definition information 220-2).

[0054] 4, the process definition information 220-1 specifies the sixth (u=6) preparation device 206, and the process definition information 220-4 specifies the fourth (u=4) preparation device 206, but the process definition information 220-2 does not specify any of the preparation devices 206 with the number u. Therefore, in the example of Fig. 6, the control information generator 20 generates control information Ic (control information Ic1) that specifies the first and second (u=1, 2) preparation devices 206 for the process definition information 220-2 and the third, fifth, and seventh (u=3, 5, 7) preparation devices 206 for the process definition information 220-1.

[0055] In the example of Fig. 4, the sixth (u=6) preparation device 206 is specified for sample number C1 in the process definition information 220-3, but no u-number preparation device 206 is specified for sample number C2. Therefore, in the example of Fig. 7, the control information generator 20 generates control information Ic (control information Ic2) that specifies the sixth (u=6) preparation device 206 for sample number C1 in the process definition information 220-3 and the eighth (u=8) preparation device 206 for sample number C2.

[0056] The control information Ic includes time-series information for controlling the processing device 200. In the example of Fig. 6, the control information Ic1 is information for executing the processes defined in the process definition information 220-1, the process definition information 220-2, and the process definition information 220-4 in parallel in time series in the processing device 200. In the example of Fig. 7, the control information Ic2 is information for executing the process defined in the process definition information 220-3 in the processing device 200 after the processing device 200 has been controlled by the control information Ic1. The device control unit 40 controls the processing device 200 based on the control information Ic.

[0057] Fig. 8 is a diagram showing another example of the control information Ic. Fig. 8 shows an example of the control information Ic relating to the control of the furnace 208. The control information generator 20 (see Fig. 3) generates the control information Ic based on a plurality of pieces of process definition information 220. In this example, the control information generator 20 generates control information Ic1' by integrating the process definition information 220-1 and the process definition information 220-2.

[0058] The control information generation unit 20 (see FIG. 3) may determine whether two or more pieces of process definition information 220 are inconsistent. In the example of FIG. 4, furnace 208 No. 1 (v=1) is specified in process definition information 220-1 and process definition information 220-3. In such a case, the control information generation unit 20 (see FIG. 3) determines that the process definition information 220-1 and process definition information 220-3 are inconsistent.

[0059] The control information generator 20 (see FIG. 3) may generate control information Ic by integrating two or more pieces of non-contradictory process definition information 220. In the example of FIG. 4, the process definition information 220-1 specifies the first furnace 208 (v=1), but the process definition information 220-2 does not specify any furnaces 208. Therefore, the process definition information 220-1 and the process definition information 220-2 do not contradict each other. Furthermore, in the example of FIG. 4, the process definition information 220-1 specifies the second furnace 208 (v=2), but the second furnace 208 (v=2) is not specified by any of the process definition information 220 other than the process definition information 220-1. Therefore, the control information generator 20 generates control information Ic1' by integrating the process definition information 220-1 and the process definition information 220-2.

[0060] The control information Ic includes time-series information for controlling the processing device 200. In the example of Fig. 8, the control information Ic1' is information for performing the processes defined by the process definition information 220-1 and the process definition information 220-2 in parallel in time series in the processing device 200. The device control unit 40 controls the processing device 200 based on the control information Ic.

[0061] As described above, in the management device 100, the control information generator 20 generates control information Ic including time-series information for controlling the processing device 200 based on multiple pieces of process definition information 220. As a result, the processes desired by multiple users 400 are optimized in the management device 100. This can improve the throughput of the processing in the processing device 200. Furthermore, each user 400 simply defines process definition information 220 that indicates the content of the desired process and inputs the defined process definition information 220 to the management device 100. The control information generator 20 generates control information Ic based on the input process definition information 220. This can reduce the burden on each user 400.

[0062] The acquisition unit 10 may acquire restriction information Ir relating to restrictions on the processing apparatus 200. The control information generation unit 20 may generate control information Ic based on a plurality of pieces of processing definition information 220 and the restriction information Ir. The restriction information Ir may be information relating to functional or specification restrictions on the processing apparatus 200. For example, if the processing apparatus 200 has m preparation devices 206, the control information generation unit 20 generates control information Ic with an upper limit of m preparation devices 206. For example, if the processing apparatus 200 has n furnaces 208, the control information generation unit 20 generates control information Ic with an upper limit of n furnaces 208.

[0063] The restriction information Ir may include processing restriction information Ip relating to restrictions on the processing conditions 222. The restrictions on the processing conditions 222 refer to restrictions on processing in the processing apparatus 200. For example, if there is an upper limit on the preparation temperature Te1 or preparation time Tm1 in the preparation device 206, the processing restriction information Ip is information regarding the upper limit of the preparation temperature Te1 or preparation time Tm1. For example, if there is an upper limit on the drying temperature Te2 or drying time Tm2 in the furnace 208, the processing restriction information Ip is information regarding the upper limit of the drying temperature Te2 or drying time Tm2. If the predetermined preparation temperature Te1 or preparation time Tm1 exceeds the upper limit in the processing restriction information Ip, the control information generator 20 may generate control information Ic in which the preparation temperature Te1 or preparation time Tm1 in the preparation device 206 is set as the upper limit in the processing restriction information Ip. If the predetermined preparation temperature Te2 or preparation time Tm2 exceeds the upper limit value in the processing restriction information Ip, the control information generation unit 20 may generate control information Ic in which the drying temperature Te2 or drying time Tm2 in the preparation device 206 is set to the upper limit value in the processing restriction information Ip.

[0064] The limit on the processing conditions 222 may refer to the number of processing conditions 222 that can be processed at one time in the processing device 200. The number of processing conditions 222 that can be processed at one time in the processing device 200 is referred to as the limited number of conditions Nr.

[0065] The process definition information 220 may include information on the type of material to be processed by the processing device 200. In the example of Fig. 4, the process definition information 220 includes information on the types of raw materials (raw material A and raw material B) to be processed by the processing device 200 and the amount of each type of raw material.

[0066] The limit information Ir may include information on the number of types of substances or the amount of substances that the processing apparatus 200 can prepare. In the example of FIG. 2 , the processing apparatus 200 has k raw material storage units 202. Therefore, the upper limit on the number of types of substances that the processing apparatus 200 can prepare is k types. Each of the k raw material storage units 202 may have an upper limit on the amount of substance that can be stored. Information on the amount of substance that the processing apparatus 200 can prepare is, for example, the upper limit on the amount of substance that the raw material storage unit 202 can store.

[0067] The control information generator 20 may generate the control information Ic based on the sum of the number of types of substances in the process definition information 220 and the sum of the number of types of substances in the restriction information Ir. For example, the control information generator 20 generates the restriction information Ic so that the sum of the number of types of substances in the process definition information 220 is equal to or less than the sum of the number of types of substances in the restriction information Ir.

[0068] The sum of the number of substance types in the process definition information 220 refers to the sum of the number of substance types in the multiple processes to be executed by the processing apparatus 200. In the example of FIG. 4, the sum of the number of substance types is 2. The sum of the number of substance types in the restriction information Ir refers to the sum of the number of substance types that can be stored in the raw material storage units 202 (see FIG. 2). If each of the k raw material storage units 202 stores a different type of raw material, the sum of the number of substance types in the restriction information Ir is k. In the example of FIG. 2, the raw material storage units 202 cannot prepare more than k types of raw material. Therefore, the control information generator 20 generates the restriction information Ic so that the sum of the number of substance types in the process definition information 220 is equal to or less than the sum of the number of substance types in the restriction information Ir.

[0069] The control information generator 20 may generate the control information Ic based on the sum of the amounts of one type of substance in the process definition information 220 and the sum of the amounts of the one type of substance in the restriction information Ir. For example, the control information generator 20 generates the restriction information Ic so that the sum of the amounts of one type of substance in the process definition information 220 is equal to or less than the sum of the amounts of the one type of substance in the restriction information Ir. The one type of substance is any one type of substance from among multiple types of substances.

[0070] The sum of the amounts of one type of substance in process definition information 220 refers to the sum of the amounts of one type of substance in multiple processes executed by processing device 200. In the example of Figure 4, process definition information 220-1 specifies a total amount of raw material A of 0.075 mol, process definition information 220-2 specifies a total amount of raw material A of 0.065 mol, process definition information 220-3 specifies a total amount of raw material A of 0.28 mol, and process definition information 220-4 specifies a total amount of raw material A of 0.015 mol. Therefore, in the example of Figure 4, the sum of the amounts of raw material A in process definition information 220 is 0.435 mol.

[0071] The sum of the amounts of one type of substance in the restriction information Ir is the sum of the amounts of one type of substance that can be stored in the ingredient storage unit 202 (see FIG. 2). When each of the k ingredient storage units 202 stores a different type of ingredient, for example, this is the upper limit of the amount of ingredient A that can be stored in the ingredient storage unit 202 that stores ingredient A. In the example of FIG. 2, the ingredient storage unit 202 cannot prepare an amount of ingredient A that exceeds this upper limit. Therefore, the control information generator 20 generates restriction information Ic so that the sum of the amounts of one type of substance in the process definition information 220 is equal to or less than the sum of the amounts of the one type of substance in the restriction information Ir.

[0072] The control information generator 20 may generate the control information Ir based on the number of processes in the processing conditions 222 and a limiting condition number Nr, which is the number of processes in the processing limiting information Ip. For example, the control information generator 20 generates the control information Ir so that the number of processes in the processing conditions 222 is equal to or less than the limiting condition number Nr.

[0073] In the example of FIG. 4 , the number of processes in the processing conditions 222 is the number of preparation temperatures Te1 or the number of preparation times Tm1. In the example of FIG. 4 , the number of preparation temperatures Te1 is six: 40°C, 50°C, 55°C, 60°C, 65°C, and 70°C. In the example of FIG. 4 , the number of preparation times Tm1 is four: 1 hour, 1.5 hours, 2 hours, and 3 hours. The number of processes in the processing restriction information Ip is the number of preparation temperatures Te1 or the number of preparation temperatures Tm1 that can be processed by the preparation device 206. The preparation device 206 cannot perform processes that exceed the number of preparation temperatures Te1 or the number of preparation times Tm1 in the processing restriction information Ip. Therefore, the control information generator 20 generates control information Ir so that the number of processes in the processing conditions 222 is equal to or less than the number of processes in the processing restriction information Ip.

[0074] In the example of FIG. 4 , the number of processes in the processing conditions 222 refers to the number of drying temperatures Te2 or the number of drying times Tm2. In the example of FIG. 4 , the number of drying temperatures Te2 is four: 200°C, 250°C, 300°C, and 350°C. In the example of FIG. 4 , the number of drying times Tm2 is three: 1 hour, 1.5 hours, and 2 hours. The number of processes in the processing restriction information Ip refers to the number of drying temperatures Te2 or drying temperatures Tm2 that can be processed in the furnace 208. The furnace 208 cannot perform more processes than the number of drying temperatures Te2 or the number of drying times Tm2 specified in the processing restriction information Ip. Therefore, the control information generator 20 generates the control information Ir so that the number of processes in the processing conditions 222 is equal to or less than the number of processes specified in the processing restriction information Ip.

[0075] The acquiring unit 10 may acquire common information Iq for the plurality of pieces of process definition information 220. The acquiring unit 10 may acquire, as the common information Iq, information that the preparation equipment 206 is the same, the substance to be processed is the same, the preparation temperature Te1 is the same, the preparation time Tm1 is the same, the sample number s is the same, the drying temperature Te2 is the same, or the drying time Tm2 is the same across the plurality of pieces of process definition information 220.

[0076] The control information generator 20 may generate the control information Ic based on the common information Iq. For example, the control information generator 20 may generate the control information Ic by integrating or editing the process definition information 220 in which a common ingredient is specified across multiple pieces of process definition information 220. In the examples of FIGS. 6 and 7, ingredient A and ingredient B are specified in the process definition information 220-1 to 220-4. Therefore, in the examples of FIGS. 6 and 7, the control information generator 20 generates the control information Ic by integrating the process definition information 220-1 to 220-4.

[0077] The control information generator 20 may generate the control information Ic based on the similarity of the process definition information 220. The similarity of the process definition information 220 is, for example, the distance d between the first process definition information 220 and the second process definition information 220. １１ ~x １ｐ and the p types of parameters in the second process definition information 220 are x ２１ ~x ２ｐ Then, the distance d is expressed by the following equation 1. In the example of Fig. 4, p is 6. The six parameters are raw material A, raw material B, preparation temperature Te1, preparation time Tm1, drying temperature Te2, and drying time Tm2.

[0078] The control information generator 20 may compare the similarity of some of the p types of parameters. When comparing the similarity of some of the parameters, parameters related to the processing conditions of the same process may be compared. In the example of FIG. 4, the same process refers to the preparation process using the preparation device 206 or the drying process using the furnace 208.

[0079] The control information generating unit 20 may calculate the distance d using Equation 1. The control information generating unit 20 may calculate the distance d for each of all combinations of two pieces of process definition information 220 selected from a plurality of pieces of process definition information 220. When the p types of parameters include a character parameter, the control information generating unit 20 may calculate the distance d using Equation 1, using the character parameter as a dummy variable. The control information generating unit 20 may normalize each of the p types of parameters, and may calculate the distance d for the normalized p types of parameters using Equation 1.

[0080] The control information generator 20 calculates a threshold distance d based on the calculated distances d. ｔｈ For example, the control information generator 20 may calculate the average or median of the multiple distances d as the threshold distance d ｔｈ The threshold distance d ｔｈ may be predetermined by the users 400 (in this example, users 400-1 to 400-4).

[0081] The control information generator 20 determines whether the distance d between the first process definition information 220 and the second process definition information 220 is equal to or greater than the threshold distance d ｔｈ In the following cases, the first process definition information 220 and the second process definition information 220 may be determined to be similar. When the control information generator 20 determines that the first process definition information 220 and the second process definition information 220 are similar, the control information generator 20 may generate control information Ic that integrates the first process definition information 220 and the second process definition information 220. When the processing device 200 is controlled by the control information Ic, the processing in the processing device 200 (an experiment in an experimental device in the example of FIG. 2 ) is more likely to be the processing desired by the user 400. This can improve the efficiency of data evaluation in the evaluation device 250.

[0082] The control information generator 20 determines whether the distance d between the first process definition information 220 and the second process definition information 220 is equal to or greater than the threshold distance d ｔｈ, the control information generator 20 may determine that the first process definition information 220 and the second process definition information 220 are not similar. When the control information generator 20 determines that the first process definition information 220 and the second process definition information 220 are not similar, the control information generator 20 does not need to generate control information Ic that integrates the first process definition information 220 and the second process definition information 220. This allows the processing device 200 to avoid processing using the control information Ic that integrates the first process definition information 220 and the second process definition information 220. This can reduce the burden on the processing device 200.

[0083] The control information generator 20 may generate the control information Ic based on the similarity between the first processing temperature under the first processing conditions 222 and the second processing temperature under the second processing conditions 222. For example, the control information generator 20 generates the control information Ic based on the similarity between the preparation temperature Te1 under the processing conditions 222-1 and the preparation temperature Te1 under the processing conditions 222-2. The processing temperature is the temperature at which a substance is processed in the processing apparatus 200. In the example of FIG. 4 , the processing temperature is the preparation temperature Te1 or the drying temperature Te2. When the first processing temperature is the preparation temperature Te1, the second processing temperature is the preparation temperature Te1. When the first processing temperature is the drying temperature Te2, the second processing temperature is the drying temperature Te2. When there is one preparation temperature Te1 under the first processing conditions 222 and one preparation temperature Te1 under the second processing conditions 222, the similarity of the preparation temperature Te1 is the distance d (difference) between the preparation temperature Te1 under the first processing conditions 222 and the preparation temperature Te1 under the second processing conditions 222. The first processing condition 222 is any one of the plurality of processing conditions 222 (e.g., processing condition 222-1), and the second processing condition 222 is any other one of the plurality of processing conditions 222 (e.g., processing condition 222-2).

[0084] The control information generator 20 determines whether the distance d (the difference in this example) is a threshold distance d ｔｈIf the difference is equal to or less than the threshold difference (in this example), it may be determined that the preparation temperature Te1 under the first processing conditions 222 and the preparation temperature Te1 under the second processing conditions 222 are similar. The control information generator 20 may generate control information Ic that integrates the preparation temperature Te1 under the first processing conditions 222 and the preparation temperature Te1 under the second processing conditions 222. This increases the probability that the processing in the processing device 200 (an experiment in the experimental device in the example of FIG. 2) will be the processing desired by the user 400. This may improve the efficiency of data evaluation in the evaluation device 250. This may reduce the burden on the processing device 200.

[0085] The control information generator 20 determines whether the distance d (the difference in this example) between the preparation temperature Te1 under the first processing condition 222 and the preparation temperature Te1 under the second processing condition 222 is equal to or greater than the threshold distance d ｔｈ If the difference is equal to or less than the threshold difference (in this example), the preparation temperature Te1 of the first processing condition 222 and the preparation temperature Te1 of the second processing condition 222 may be determined to be similar. The control information generator 20 may combine a first processing definition information 220 including the first processing condition 222 with a second processing definition information 220 including the second processing condition 222 to generate control information Ic for processing the first processing condition 222 and the second processing condition 222 in parallel in time series, or may generate control information Ic for processing the first processing condition 222 and the second processing condition 222 consecutively in time series. This may improve the processing throughput of the processing device 200. In other words, by processing the first processing condition 222 and the second processing condition 222 in parallel in time series, the operating rate of the processing device 200 may be improved. Furthermore, the number of processes that can be processed per unit time in the processing device 200 may be increased. This may improve the efficiency of data evaluation in the evaluation device 250. Furthermore, since the acquisition unit 10 can acquire the process definition information 220 based on the predicted value Pv (described later) earlier, the processing device 200 can start the next cycle of the processing period T (see FIG. 5) earlier.

[0086] The control information generator 20 determines whether the distance d (the difference in this example) is a threshold distance d ｔｈIf the difference is greater than the threshold difference (in this example), it may be determined that the preparation temperature Te1 under the first processing conditions 222 and the preparation temperature Te1 under the second processing conditions 222 are not similar. The control information generator 20 does not need to generate control information Ic that integrates the preparation temperature Te1 under the first processing conditions 222 and the preparation temperature Te1 under the second processing conditions 222. This prevents the processing device 200 from performing processing using control information Ic that integrates the preparation temperature Te1 under the first processing conditions 222 and the preparation temperature Te1 under the second processing conditions 222. This can reduce the burden on the processing device 200.

[0087] The difference between the first process temperature in the first process definition information 220 and the second process temperature in the second process definition information 220 is equal to or greater than a predetermined threshold value d ｔｈ In the following cases, the control information generator 20 may generate control information Ic for processing a first substance in the first process definition information 220 and a second substance in the second process definition information 220 at a first process temperature, or may generate control information Ic for processing a first substance in the first process definition information 220 and a second substance in the second process definition information 220 at a second process temperature. As described above, in the example of Fig. 4, the process temperature is the preparation temperature Te1 or the drying temperature Te2.

[0088] For example, in the example of FIG. 4 , the preparation temperature Te1 of sample A3 is 65° C., and the preparation temperature Te1 of sample C1 is 60° C. Assume that 60° C. and 65° C. are similar. In this case, the control information generator 20 generates a prepared sample by preparing raw materials A and B of sample A3 and raw materials A and B of sample C1 at 60° C., and then generates control information Ic for generating another prepared sample by preparing raw materials A and B of sample A3 and raw materials A and B of sample C1 at 65° C. By preparing sample C1 at 65° C. and sample A3 at 60° C., reference data for sample A3 and sample C1 can be obtained.

[0089] When the type of substance in the first process definition information 220 and the type of substance in the second process definition information 220 are the same, the control information generator 20 may generate control information Ic for processing the first process definition information 220 and the second process definition information 220 in parallel or successively in time series. In the example of Fig. 4, the types of raw materials in the process definition information 220-1 to 220-4 are two types, raw material A and raw material B. Therefore, as shown in Figs. 6 and 7, the control information generator 20 generates control information Ic for processing the process definition information 220-1, process definition information 220-2, and process definition information 220-4 in parallel in time series, and, after the parallel processing, for processing the process definition information 220-3 in successively in time series.

[0090] As described above, the acquisition and input unit 204 (see FIG. 2 ) acquires one raw material from the raw material storage unit 202 and inputs the acquired raw material into the preparation device 206. If the acquisition and input unit 204 is a pipette, the raw material may remain inside the acquisition and input unit 204 even after input into the preparation device 206. For this reason, it is preferable that the acquisition and input unit 204 continuously acquire and input the same raw material. For this reason, when the type of substance in the first process definition information 220 is the same as the type of substance in the second process definition information 220, it is preferable that the control information generation unit 20 generate control information Ic that processes the first process definition information 220 and the second process definition information 220 in parallel or consecutively in time series.

[0091] FIG. 9 is a diagram showing an example of an evaluation value Ev of a product G generated by processing by the processing device 200. In this example, the processing device 200 is controlled by control information Ic shown in at least one of FIGS. 6, 7, and 8. The processing device 200 may or may not have an evaluation device 250 (see FIG. 1) that evaluates the product G. If the processing device 200 does not have the evaluation device 250, the product G may be evaluated by an evaluation device 250 separate from the processing device 200. In this example, j types of products G (G １ ~G ｊ In this example, j types of products G (G １ ~G ｊ) evaluation value Ev is Ev １ ~Ev ｊ Let us assume that:

[0092] 10 is a diagram showing an example of learning by the control information generating unit 20. In this example, the control information generating unit 20 performs machine learning on the relationship between the evaluation value Ev of the product G and a plurality of parameters Pr including the processing conditions 222 in the processing definition information 220. In the example of FIG. 4, the plurality of parameters Pr are the number u of the preparation device 206, the types and amounts of raw materials A and B, the preparation temperature Te1, the preparation time Tm1, the number v of the furnace 208, the drying temperature Te2, and the drying time Tm2.

[0093] FIG. 11 is a diagram showing an example of inference by the evaluation value inference model 22. When one input parameter Pr in the process definition information 220 is input, the evaluation value inference model 22 outputs a predicted value Pv of the evaluation value Ev. The one input parameter Pr is any one of the multiple input parameters Pr. The control information generator 20 may include the evaluation value inference model 22. The evaluation value inference model 22 performs machine learning on the relationship between the evaluation value Ev and the multiple parameters Pr, and therefore, when one parameter Pr is input, the predicted value Pv of the evaluation value Ev can be inferred. The inferred predicted value Pv may be stored in the storage unit 50 (see FIG. 3).

[0094] FIG. 12 is a conceptual diagram showing an example of the relationship between multiple parameters Pr and the predicted value Pv. For ease of illustration, FIG. 12 shows two of the multiple parameters Pr (parameter Pr1 and parameter Pr2). When there are two or more parameters Pr, the relationship between the multiple parameters Pr and the predicted value Pv is shown in a multidimensional space having axes corresponding to each of the multiple parameters Pr. In FIG. 12, points where processing has been performed are indicated by "X." In FIG. 12, the magnitude of the predicted value Pv is indicated by a different shade. In the data space represented by the multiple parameters Pr, areas with larger predicted values ​​Pv are shown in a darker color.

[0095] The acquisition unit 10 (see FIG. 3 ) may acquire at least one of the plurality of pieces of process definition information 220 based on the predicted value Pv. For example, the acquisition unit 10 may use a genetic algorithm to repeatedly generate a parameter Pr and infer the predicted value Pv by inputting the generated parameter Pr into the evaluation value inference model 22, thereby generating a parameter Pr each time. This process (optimization calculation) allows the acquisition unit 10 to acquire a parameter Pr that satisfies a predetermined goal (e.g., obtaining a high predicted value Pv). This allows the acquisition unit 10 to acquire at least one piece of process definition information 220 that includes the parameter Pr.

[0096] Fig. 13 is a diagram showing another example of the control information Ic. The control information generator 20 (see Fig. 3) generates the control information Ic based on a plurality of pieces of process definition information 220. In this example, the control information generator 20 generates control information Ic1 by integrating or editing the process definition information 220 having a parameter Pr (see Fig. 12) based on the predicted value Pv in addition to the examples in Figs. 6 and 7.

[0097] The control information generator 20 may read at least two pieces of process definition information 220 for each predetermined processing period T (see FIG. 5 ). In the example of FIG. 5 , the control information generator 20 reads each piece of process definition information 220 input by each user 400 for each first cycle and second cycle of the processing period T. The control information generator 20 may generate control information Ic for controlling the processing device 200 for the processing period T based on the read process definition information 220. In the example of FIG. 13 , the control information generator 20 generates control information Ic by integrating or editing the pieces of process definition information 220 input by each user 400 in the first cycle of the processing period T. In the example of FIG. 13 , the control information generator 20 generates control information Ic by integrating or editing the pieces of process definition information 220 input by each user 400 and the process definition information 220 having a parameter Pr based on the predicted value Pv in the second cycle of the processing period T.

[0098] The marginal capacity calculation unit 30 (see FIG. 3) calculates the processing capacity of the processing device 200 during the processing period T (see FIG. 5) when the processing device 200 is controlled using the control information Ic shown in FIGS. 6, 7, and 8. The processing capacity of the processing device 200 may be the processing capacity of the processing device 200 obtained by subtracting the processing capacity when controlled using the control information Ic from the upper limit of the processing capacity of the processing device 200 based on its functions or specifications. In the example of FIG. 13, the marginal capacity calculation unit 30 calculates that there is a marginal capacity to process three more samples with sample number s when the processing device 200 is controlled using the control information Ic shown in FIGS. 6, 7, and 8.

[0099] The control information generating unit 20 may generate additional control information Ic based on the processing reserve capacity calculated by the reserve capacity calculating unit 30. In the example of FIG. 13 , the control information generating unit 20 generates additional control information Ic for three additional sample numbers s. The control information generating unit 20 may generate the control information Ic so that processing reserve capacity is generated. That is, the control information generating unit 20 may generate the control information Ic so as to control the processing device 200 within a processing capacity range obtained by subtracting a predetermined processing reserve capacity from the upper limit of the processing capacity of the processing device 200. The predetermined processing capacity may be predetermined by the user 400.

[0100] When there is processing capacity available in the processing device 200, the control information generation unit 20 may generate control information Ic by integrating or editing the processing definition information 220 having the parameter Pr based on the predicted value Pv. That is, after the control information generation unit 20 generates control information Ic by integrating or editing the respective pieces of processing definition information 220 input by each user 400, the reserve capacity calculation unit 30 may calculate the reserve capacity of the processing device 200. When there is capacity available after the reserve capacity calculation unit 30 calculates the reserve capacity of the processing device 200, the control information generation unit 20 may generate control information Ic by integrating or editing the processing definition information 220 having the parameter Pr based on the predicted value Pv.

[0101] FIG. 14 is a diagram showing an example of a predicted value Pv inferred by the evaluation value inference model 22. The evaluation value inference model 22 performs machine learning on the relationship between the evaluation value Ev and multiple parameters Pr, and thus can infer a predicted value Pv for any combination of the sample number s' and the furnace 208 number in FIG. 13 . The inferred predicted value Pv may be stored in the storage unit 50 (see FIG. 3 ). The acquisition unit 10 (see FIG. 3 ) may acquire at least one of multiple pieces of process definition information 220 based on the predicted value Pv. For example, the acquisition unit 10 may acquire process definition information 220 that is a combination of parameters Pr that results in a predetermined value for the predicted value Pv. The predetermined value for the predicted value Pv is, for example, the predicted value that maximizes the predicted value Pv. In the example of FIG. 14 , for example, the acquisition unit 10 acquires process definition information 220 that combines sample number s' No. 8 and furnace 208 No. 2.

[0102] Fig. 15 is a diagram showing an example of a management system 300 according to an embodiment of the present invention. In this example, owner A owns the management device 100, and owner B owns the processing device 200. In this example, owner A is the administrator of the management device 100, and owner B is, for example, a customer of owner A. In the example of Fig. 15, user 400 may be owner B. Owner B uses management device 100 by paying a usage fee for management device 100 to owner A, for example.

[0103] 16 is a diagram showing another example of a management system 300 according to an embodiment of the present invention. In this example, owner B owns the management system 300. In this example, owner A transfers the management device 100 to owner B, and owner B now owns the management device 100 and the processing device 200. In the example of FIG. 16, user 400 may be owner B.

[0104] FIG. 17 is a diagram showing another example of a management system 300 according to an embodiment of the present invention. Owner A owns a management device 100, and owner C owns a processing device 200. In this example, owner A is the administrator of the management device 100, and owner B is, for example, owner A's customer. In this example, owner C is, for example, a contractor commissioned by owner B, and owns a processing device 200 that performs the processing desired by owner B. Owner B uses the management device 100 by, for example, paying a usage fee for the management device 100 to owner A. Owner B manages owner C's processing device 200 using the management device 100. In the example of FIG. 17 , user 400 may be owner B.

[0105] 18 is a flowchart showing an example of a management method according to an embodiment of the present invention. The management method is a method for managing a processing device 200 for processing a substance. The management method includes an acquisition step S100 and a control information generation step S110. The management method may include a spare capacity calculation step S120, a processing device control step S124, an evaluation step S128, a learning step S132, and a judgment step S136. The management method according to an embodiment of the present invention will be described using the management device 100 shown in FIG. 3 as an example.

[0106] The acquisition step S100 is a step in which the acquisition unit 10 acquires a plurality of pieces of process definition information 220, each of which includes a processing condition 222 to be executed by the processing device 200. The plurality of pieces of process definition information 220 may be process definition information 220 defined by the user 400. The control information generation step S110 is a step in which the control information generation unit 20 generates, based on the plurality of pieces of process definition information 220, control information Ic including time-series information for controlling the processing device 200.

[0107] The acquisition step S100 may be a step in which the acquisition unit 10 acquires restriction information Ir relating to restrictions on the processing device 200. The control information generation step S110 may be a step in which the control information generation unit 20 generates control information Ic based on a plurality of pieces of process definition information 220 and the restriction information Ir.

[0108] The control information generation step S110 may be a step in which the control information generation unit 20 generates control information Ic based on the sum of the number of types of substance in the processing definition information 220 and the sum of the number of types of substance in the restriction information Ir, or may generate control information Ic based on the sum of the amounts of one type of substance in the processing definition information 220 and the sum of the amounts of one type of substance in the restriction information Ir.

[0109] The control information generating step S110 may be a step in which the control information generating unit 20 generates the control information Ic based on the number of processes in the processing conditions 222 and a limiting condition number Nr, which is the number of processes in the processing limiting information Ip. The control information generating step S110 may be a step in which the control information generating unit 20 generates the control information Ic so that the number of processes in the processing conditions 222 is equal to or less than the limiting condition number Nr.

[0110] The processing restriction information Ip may be information regarding the upper limit of the preparation temperature Te1 or the preparation time Tm1 in the preparation device 206. When the predetermined preparation temperature Te1 or the predetermined preparation time Tm1 exceeds the upper limit in the preparation device 206, the control information generator 20 may generate control information Ic that sets the predetermined preparation temperature Te1 or the predetermined preparation time Tm1 as the upper limit in the preparation device 206.

[0111] The acquisition step S100 may be a step in which the acquisition unit 10 acquires common information Iq in the plurality of pieces of process definition information 220. The control information generation step S110 may be a step in which the control information generation unit 20 generates control information Ic based on the common information Iq.

[0112] The control information generating step S110 may be a step in which the control information generating unit 20 generates control information Ic based on the similarity of the process definition information 220. When the type of substance in the first process definition information 220 is the same as the type of substance in the second process definition information 220, the control information generating step S110 may be a step in which the control information generating unit 20 generates control information Ic for processing the first process definition information 220 and the second process definition information 220 in parallel or successively in time series.

[0113] The control information generation step S110 may be a step in which the control information generation unit 20 generates control information Ic based on the similarity between the first processing temperature under the first processing conditions 222 and the second processing temperature under the second processing conditions 222.

[0114] When the difference between the first processing temperature in the first processing definition information 220 and the second processing temperature in the second processing definition information 220 is equal to or less than a predetermined threshold, the control information generation step S110 may be a step in which the control information generation unit 20 generates control information Ic in which the first substance in the first processing definition information 220 and the second substance in the second processing definition information 220 are processed at the first processing temperature, and the first substance in the first processing definition information 220 and the second substance in the second processing definition information 220 are processed at the second processing temperature.

[0115] The control information generation step S110 may be a step in which the control information generation unit 20 reads at least two pieces of processing definition information 220 for each predetermined processing period T, and generates control information Ic that controls the processing device 200 during the processing period T based on the read processing definition information 220.

[0116] In the remaining capacity calculation step S120, the remaining capacity calculation unit 30 calculates the processing capacity of the processing device 200 during the processing period T (see FIG. 5 ) when the processing device 200 is controlled using the control information Ic generated in the control information generation step S110. If it is calculated that there is processing capacity, the management method returns to the acquisition step S100. If it is calculated that there is no processing capacity, the management method proceeds to the processing device control step S124.

[0117] The processing device control step S124 is a step in which the device control unit 40 controls the processing device 200 based on the control information Ic.

[0118] The evaluation step S128 is a step in which the evaluation device 250 evaluates the product G. The learning step S132 is a step in which the control information generation unit 20 performs machine learning on the relationship between the evaluation value Ev of the product G and a plurality of parameters Pr including the processing conditions 222 in the processing definition information 220. The learning step S132 is a step in which the control information generation unit 20 performs machine learning on the relationship between the evaluation value Ev and the plurality of parameters Pr, thereby generating an evaluation value inference model 22 that outputs a predicted value Pv of the evaluation value Ev.

[0119] Determination step S136 is a step in which the processing unit 60 determines whether the management device 100 will end management of the processing device 200. Determination step S136 may be a step in which the processing unit 60 determines whether new process definition information 220 has been input to the management device 100 during the processing period T. If it is determined in determination step S136 that new process definition information 220 has been input, the management method may return to acquisition step S100. If it is not determined in determination step S136 that new process definition information 220 has been input, the management method may end management of the processing device 200.

[0120] When the process returns from the determination step S136 to the acquisition step S100, the acquisition step S100 may be a step in which the acquisition unit 10 acquires at least one of a plurality of pieces of process definition information 220 based on the predicted value Pv. In the acquisition step S100, the acquisition unit 10 may acquire the process definition information 220 input by the user 400 and the process definition information 220 based on the predicted value Pv. In the control information generation step S110, the control information Ic may be generated based on the process definition information 220 input by the user 400 and the process definition information 220 based on the predicted value Pv. In the process assumption control step S124, the device control unit 40 may control the processing device 200 based on the control information Ic.

[0121] 19 is a diagram showing an example of a computer 2200 in which the management device 100 according to an embodiment of the present invention may be embodied, in whole or in part. A program installed on the computer 2200 can cause the computer 2200 to perform operations associated with the management device 100 according to an embodiment of the present invention, or to function as one or more sections of the management device 100, or to execute the operations or one or more sections, or to perform each step of the management method of the present invention (see FIG. 18). The program can be executed by the CPU 2212 to cause the computer 2200 to perform specific operations associated with some or all of the blocks in the flowchart ( FIG. 18 ) and block diagram ( FIG. 3 ) described herein.

[0122] A computer 2200 according to one embodiment of the present invention includes a CPU 2212, a RAM 2214, a graphics controller 2216, and a display device 2218. The CPU 2212, the RAM 2214, the graphics controller 2216, and the display device 2218 are connected to one another by a host controller 2210. The computer 2200 further includes input / output units such as a communication interface 2222, a hard disk drive 2224, a DVD-ROM drive 2226, and an IC card drive. The communication interface 2222, the hard disk drive 2224, the DVD-ROM drive 2226, and the IC card drive are connected to the host controller 2210 via an input / output controller 2220. The computer further includes legacy input / output units such as a ROM 2230 and a keyboard 2242. The ROM 2230, the keyboard 2242, and the like are connected to the input / output controller 2220 via an input / output chip 2240.

[0123] The CPU 2212 controls each unit by operating in accordance with programs stored in the ROM 2230 and the RAM 2214. The graphics controller 2216 acquires image data generated by the CPU 2212 into a frame buffer or the like provided in the RAM 2214, or into the RAM 2214, so that the image data can be displayed on the display device 2218.

[0124] The communication interface 2222 communicates with other electronic devices via a network. The hard disk drive 2224 stores programs and data used by the CPU 2212 in the computer 2200. The DVD-ROM drive 2226 reads programs or data from the DVD-ROM 2201 and provides the read programs or data to the hard disk drive 2224 via the RAM 2214. The IC card drive reads programs and data from an IC card or writes programs and data to an IC card.

[0125] The ROM 2230 stores a boot program or the like that is executed by the computer 2200 upon activation, or a program that depends on the hardware of the computer 2200. The input / output chip 2240 may connect various input / output units to the input / output controller 2220 via a parallel port, a serial port, a keyboard port, a mouse port, or the like.

[0126] The programs are provided by a computer-readable medium such as a DVD-ROM 2201 or an IC card. The programs are read from the computer-readable medium, installed in the hard disk drive 2224, RAM 2214, or ROM 2230, which are also examples of computer-readable media, and executed by the CPU 2212. Information processing described in these programs is read by the computer 2200, and brings about cooperation between the programs and the various types of hardware resources described above. An apparatus or method may be configured by implementing information manipulation or processing in accordance with the use of the computer 2200.

[0127] For example, when communication is performed between computer 2200 and an external device, CPU 2212 may execute a communication program loaded in RAM 2214 and instruct communication interface 2222 to perform communication processing based on the processing described in the communication program. Under the control of CPU 2212, communication interface 2222 reads transmission data stored in a transmission buffer processing area provided in RAM 2214, hard disk drive 2224, DVD-ROM 2201, or a recording medium such as an IC card, and transmits the read transmission data to the network, or writes received data received from the network to a reception buffer processing area or the like provided on the recording medium.

[0128] The CPU 2212 may read all or a necessary portion of a file or database stored on an external recording medium such as the hard disk drive 2224, the DVD-ROM drive 2226 (DVD-ROM 2201), an IC card, etc. into the RAM 2214. The CPU 2212 may perform various types of processing on the data on the RAM 2214. The CPU 2212 may then write the processed data back to the external recording medium.

[0129] Various types of information, such as various types of programs, data, tables, and databases, may be stored on the recording medium and processed. The CPU 2212 may perform various types of processing on data read from the RAM 2214, including various types of operations, information processing, conditional decisions, conditional branches, unconditional branches, information search or replacement, etc., specified by the instruction sequences of the programs described in this disclosure. The CPU 2212 may write the results back to the RAM 2214.

[0130] CPU 2212 may search for information in a file, database, etc. in the recording medium. For example, if a plurality of entries each having an attribute value of a first attribute associated with an attribute value of a second attribute are stored in the recording medium, CPU 2212 may search the plurality of entries for an entry that matches a condition specified by the attribute value of the first attribute, read the attribute value of the second attribute stored in the entry, and by reading the second attribute value, obtain the attribute value of the second attribute associated with the first attribute that satisfies a predetermined condition.

[0131] The above-described programs or software modules may be stored on the computer 2200 or in a computer-readable medium of the computer 2200. A recording medium such as a hard disk or RAM provided in a server system connected to a dedicated communication network or the Internet can be used as the computer-readable medium. The programs may be provided to the computer 2200 by the recording medium.

[0132] Although the present invention has been described above using embodiments, the technical scope of the present invention is not limited to the scope described in the above embodiments. It will be apparent to those skilled in the art that various modifications and improvements can be made to the above embodiments. It is clear from the claims that such modifications and improvements can also be included within the technical scope of the present invention.

[0133] It should be noted that the order of execution of each process, such as operations, procedures, steps, and stages, in the devices, systems, programs, and methods shown in the claims, specifications, and drawings is not specifically stated as "before," "prior to," etc., and that the processes can be performed in any order unless the output of a previous process is used in a subsequent process. Even if the operational flow in the claims, specifications, and drawings is described using "first," "next," etc. for convenience, this does not mean that the processes must be performed in this order.

[0134] 10...acquisition unit, 20...control information generation unit, 22...evaluation value inference model, 30...reserve capacity calculation unit, 40...device control unit, 50...storage unit, 60...processing unit, 100...management device, 200...processing device, 202...raw material storage unit, 204...acquisition and input unit, 206...preparation equipment, 208...furnace, 220...processing definition information, 222...processing conditions, 250...evaluation device, 300...management system, 400...user, 2200...computer, 2201...DVD-ROM, 2210...host controller, 2212...CPU, 2214...RAM, 2216...graphics controller, 2218...display device, 2220...input / output controller, 2222...communication interface, 2224...hard disk drive, 2226...DVD-ROM drive, 2230...ROM, 2240...input / output chip, 2242...keyboard

Claims

1. A control device for managing a processing device that processes substances, An acquisition unit that acquires a plurality of processing definition information, including processing conditions to be executed by the aforementioned processing device, A control information generation unit generates control information including time-series information for controlling the processing apparatus based on the plurality of processing definition information, A control device equipped with the following features.

2. The acquisition unit acquires limitation information relating to the limitations of the processing device, The control information generation unit generates the control information based on the plurality of processing definition information and the restriction information. The control device according to claim 1.

3. The processing definition information includes information on the type of substance processed by the processing apparatus, The aforementioned limitation information includes information on the number of types of substances or the quantity of substances that the processing device can prepare, The control information generation unit generates the control information based on the sum of the number of substance types in the processing definition information and the sum of the number of substance types in the restriction information, or generates the control information based on the sum of the amounts of one type of substance in the processing definition information and the sum of the amounts of one type of substance in the restriction information. The control device according to claim 2.

4. The aforementioned restriction information includes processing restriction information relating to the restrictions on the processing conditions, The control information generation unit generates the control information based on the number of processes in the processing conditions and the number of limiting conditions, which is the number of processes in the processing limiting information. The control device according to claim 2.

5. The control information generation unit generates the control information such that the number of processes in the processing conditions is less than or equal to the number of limiting conditions, as described in claim 4.

6. The aforementioned restriction information includes processing restriction information relating to the restrictions on the processing conditions, The processing apparatus has a preparation device that prepares one or more types of raw materials to be processed by the processing apparatus at a predetermined preparation temperature and preparation time. The processing limitation information is information relating to the upper limit of the preparation temperature or preparation time in the preparation equipment. The control information generation unit generates control information such that the predetermined preparation temperature or predetermined preparation time exceeds the upper limit if the predetermined preparation temperature or predetermined preparation time exceeds the upper limit. The control device according to claim 2.

7. The acquisition unit acquires common information in the plurality of processing definition information, The control information generation unit generates the control information based on the common information. The control device according to claim 1.

8. The control information generation unit generates the control information based on the similarity of the processing definition information, as described in claim 1.

9. The processing definition information includes the type of substance to be processed by the processing apparatus, If the type of substance in the first processing definition information and the type of substance in the second processing definition information are the same, the control information generation unit generates control information that processes the first processing definition information and the second processing definition information in parallel or sequentially in a time series. The control device according to claim 8.

10. The processing conditions include the processing temperature in the processing to be performed by the processing apparatus. The control information generation unit generates the control information based on the similarity between the first processing temperature in the first processing condition and the second processing temperature in the second processing condition. The control device according to claim 8.

11. The control device according to claim 10, wherein if the difference between the first processing temperature in the first processing definition information and the second processing temperature in the second processing definition information is less than or equal to a predetermined threshold, the control information generation unit generates control information which specifies that the first substance in the first processing definition information and the second substance in the second processing definition information should be processed at the first processing temperature, and the first substance in the first processing definition information and the second substance in the second processing definition information should be processed at the second processing temperature.

12. The control information generation unit reads at least two of the processing definition information at predetermined processing intervals, and generates control information for controlling the processing device during the processing interval based on the read processing definition information, according to claim 1.

13. The processing unit is further provided with a surplus capacity calculation unit that calculates the processing capacity of the processing unit during the processing period when the processing unit is controlled with the control information. The control information generation unit generates additional control information based on the processing capacity. The control device according to claim 12.

14. The control information generation unit has an evaluation value inference model that, when one input parameter in the processing definition information is input, outputs a predicted value of the evaluation value by machine learning the relationship between the evaluation value of the product generated by processing by the processing device controlled by the control information and a plurality of parameters in the processing definition information, including the processing conditions. The acquisition unit acquires at least one of the plurality of processing definition information based on the predicted value. The control device according to claim 1.

15. The management device according to claim 1, further comprising a device control unit that controls the processing device based on the control information.

16. The aforementioned processing apparatus is an experimental apparatus, The aforementioned processing conditions are experimental conditions. The aforementioned processing definition information is experimental definition information. The control device according to claim 1.

17. A management system comprising the processing device and the management device according to any one of claims 1 to 16.

18. A management method for managing a processing device that processes substances, The acquisition step involves the acquisition unit acquiring a plurality of processing definition information, including processing conditions to be executed by the processing device, A control information generation step in which a control information generation unit generates control information including time-series information for controlling the processing device based on the plurality of processing definition information, A management method that includes the following features.

19. A management program for causing a computer to function as a management device according to any one of claims 1 to 16.