Driving plan generation method, driving plan generation program, and driving plan generation device

Abstract

To automatically create an operation scheme.SOLUTION: A control device 1 that automatically executes an operation scheme creating process includes: an information managing unit that stores device standard information; an information receiving unit that receives an input of facility information including device information, connection information representing a connection relation between devices, and parent-child information representing a parent-child relation between the devices; a creation rule predicting unit that identifies, for each device, a first creation rule corresponding to each device by inputting information created by, for each device, utilizing any one of connection node information corresponding to the kind of each device, the device information on each device, the connection information on each device, and the parent-child information on each device to a learning model that has undergone a machine learning on teacher data including information created by utilizing any one of the connection node information corresponding to the kind of the device for learning, the device information on the device for learning, the connection information on the device for learning, and the parent-child information on the device for learning, and information representing a creation rule corresponding to the device for learning; and an operation scheme creating unit that creates a first operation scheme corresponding to the device based on the identified first creation rule.SELECTED DRAWING: Figure 3

Description

Technical Field

[0001] The present disclosure relates to an operation plan generation method, an operation plan generation program, and an operation plan generation device.

Background Art

[0002] In the design work of various plants (hereinafter also referred to as plant design work), for example, information on the specifications of each device constituting the plant obtained from a plant designer and the connection relationship such as the plant flow (hereinafter also referred to as equipment information) and a draft of an operation plan are interpreted by an operation plan designer, and the operation plan design work (hereinafter also referred to as operation plan design work) for designing an operation plan in the plant is performed.

[0003] Although the above design work is, for example, made more efficient by a design support system for each business, there is no cooperation between multiple design support systems. Therefore, in the operation plan design work, for example, the operation plan designer may interpret the information obtained from the plant designer and manually input it into the design support system (see Patent Document 1).

Prior Art Documents

Patent Documents

[0004]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0005] However, in the operation plan design work as described above, for example, depending on the scale of the plant, the drawings on which the operation plan is described become enormous. Therefore, in the operation plan design work, for example, it takes time to design the operation plan, and there is a possibility of human errors such as omission of updates due to design changes in the upstream process. Therefore, in the operation plan design work, for example, a method that enables automatic generation of an operation plan is desired.

Means for Solving the Problems

[0006] The operation plan generation method in this disclosure stores equipment standard information in a storage unit, which includes, for each type of equipment, a generation rule for operation plans corresponding to each type and connection point information indicating the attributes of connection points between each type of equipment and other equipment; receives input of equipment information which includes equipment information indicating one or more equipment, connection information indicating the connection relationship between the one or more equipment, and parent-child information indicating the parent-child relationship between the one or more equipment; and at least of the connection point information corresponding to the type of learning equipment, the equipment information corresponding to the learning equipment, the connection information corresponding to the learning equipment, and the parent-child information corresponding to the learning equipment. The computer performs a process to input information generated using at least one of the following for each of the one or more devices: connection point information corresponding to the type of device, device information corresponding to each device, connection information corresponding to each device, and parent-child information corresponding to each device, to a learning model that has been machine-trained on training data including information generated using a shift and information indicating the generation rules corresponding to the learning device. The computer then identifies a first generation rule corresponding to each of the one or more devices and generates a first operation plan corresponding to each of the one or more devices based on each of the identified first generation rules. [Effects of the Invention]

[0007] The driving plan generation method described in this disclosure makes it possible to automatically generate a driving plan. [Brief explanation of the drawing]

[0008] [Figure 1] Figure 1 is a diagram illustrating the configuration of the driving plan generation system 1000 in the first embodiment. [Figure 2] Figure 2 is a diagram illustrating the hardware configuration of the control device 1 in the first embodiment. [Figure 3] Figure 3 is a block diagram of the functions of the control device 1 in the first embodiment. [Figure 4]Figure 4 is a block diagram of the information stored in the information storage area 130 in the first embodiment. [Figure 5] Figure 5 is a flowchart illustrating the information preparation process in the first embodiment. [Figure 6] Figure 6 is a flowchart illustrating the model generation process in the first embodiment. [Figure 7] Figure 7 is a flowchart illustrating the equipment information generation process in the first embodiment. [Figure 8] Figure 8 is a flowchart illustrating the main process for generating the driving plan in the first embodiment. [Figure 9] Figure 9 illustrates a specific example of equipment standard information 131. [Figure 10] Figure 10 is a diagram illustrating a specific example of equipment standard information 131. [Figure 11] Figure 11 is a diagram illustrating a specific example of equipment standard information 131. [Figure 12] Figure 12 illustrates a specific example of equipment standard information 131. [Figure 13] Figure 13 illustrates a specific example of equipment standard information 131. [Figure 14] Figure 14 is a diagram illustrating a specific example of the driving plan rule information 132. [Figure 15] Figure 15 is a diagram illustrating a specific example of the driving plan rule information 132. [Figure 16] Figure 16 is a diagram illustrating the details of the operation plan generation process in the first embodiment. [Figure 17] Figure 17 is a diagram illustrating a specific example of equipment information 141. [Figure 18] Figure 18 is a diagram illustrating a specific example of equipment information 141. [Figure 19] Figure 19 is a diagram illustrating a specific example of equipment information 141. [Figure 20] Figure 20 is a diagram illustrating a specific example of device parent-child information 142. [Figure 21] FIG. 21 is a diagram for explaining details of the operation plan generation process in the first embodiment. [Figure 22] FIG. 22 is a diagram for explaining a specific example of step S24. [Figure 23] FIG. 23 is a diagram for explaining a specific example of step S24. [Figure 24] FIG. 24 is a diagram for explaining a specific example of the operation plan information 151. [Figure 25] FIG. 25 is a diagram for explaining a specific example of the operation plan information 151. [Figure 26] FIG. 26 is a diagram for explaining a specific example of the output screen OP for the operation plan information 151 on the operation terminal 5. [Figure 27] FIG. 27 is a diagram for explaining a specific example of the teacher data DT. [Figure 28] FIG. 28 is a diagram for explaining a specific example of the teacher data DT. [Figure 29] FIG. 29 is a diagram for explaining a specific example of the teacher data DT. [Figure 30] FIG. 30 is a block diagram of the functions of the control device 1 in the second embodiment. [Figure 31] FIG. 31 is a block diagram of the information stored in the information storage area 130 in the second embodiment. [Figure 32] FIG. 32 is a flowchart for explaining the main operation plan generation process in the second embodiment. [Figure 33] FIG. 33 is a diagram for explaining a specific example of step S45. [Figure 34] FIG. 34 is a diagram for explaining a specific example of step S45. [Figure 35] FIG. 35 is a diagram for explaining a specific example of the input data DT0.

Embodiments for Carrying Out the Invention

[0009] Embodiments of this disclosure will be described below with reference to the drawings. However, this description should not be interpreted as limiting, and will not limit the subject matter described in the claims. Furthermore, various changes, substitutions, and modifications can be made without departing from the spirit and scope of this disclosure. Different embodiments can also be combined as appropriate.

[0010] [Driving plan generation system 1000 in the first embodiment] First, the configuration of the driving plan generation system 1000 in the first embodiment will be described. Figure 1 is a diagram illustrating the configuration of the driving plan generation system 1000 in the first embodiment.

[0011] The operation plan generation system 1000 is, for example, a system that automatically generates operation plans for a plant. Specifically, the operation plan generation system 1000 has, for example, a control device 1 and an operation terminal 5 that can access each other via a network NW such as the Internet. The following description will focus on the generation of operation plans used in a water treatment plant that includes sludge storage tanks and transfer pumps, but the operation plan generation system 1000 may also generate operation plans used in other plants such as power plants and chemical plants.

[0012] The operation terminal 5 is, for example, a PC (Personal Computer) and is a terminal used by the operator of the driving plan generation system 1000 (hereinafter also simply referred to as the operator) to input necessary information to the control device 1.

[0013] Furthermore, the control device 1 is, for example, a physical machine or a virtual machine, and is a device that performs a process to automatically generate a digitized driving plan (hereinafter also referred to as the driving plan generation process).

[0014] Specifically, the control device 1 in this embodiment stores in its memory, for example, information (hereinafter also called equipment standard information) that associates generation rules for operation plans corresponding to each type of equipment (hereinafter also simply called generation rules) with information indicating the attributes of connection points between each type of equipment and other equipment (hereinafter also called connection point information). The control device 1 then receives input of equipment information that includes, for example, information indicating one or more pieces of equipment (hereinafter also simply called one or more pieces of equipment) that are the target of operation plan generation (hereinafter also called equipment information or equipment list information), information indicating the connection relationships between those one or more pieces of equipment (hereinafter also called connection information or connection list information), and information indicating the parent-child relationships between those one or more pieces of equipment (hereinafter also called parent-child information or equipment parent-child information). Subsequently, the control device 1, for example, refers to the equipment standard information stored in its memory and identifies equipment standard information (hereinafter also called first equipment standard information) corresponding to the type of equipment (hereinafter also called first type) for each of the one or more pieces of equipment.

[0015] Subsequently, the control device 1 identifies a first generation rule for each of the following for each of the following: for example, information generated using at least one of the following: connection point information corresponding to the type of equipment used to train the learning model (hereinafter also simply called learning equipment), equipment list information corresponding to the learning equipment, connection list information corresponding to the learning equipment, and equipment parent-child information corresponding to the learning equipment, and information indicating the generation rules for operation plans corresponding to the learning equipment (hereinafter also called first generation rules). The control device 1 then identifies a first generation rule for each of the following for each of the one or more pieces of equipment: connection point information corresponding to the type of equipment, equipment list information corresponding to each piece of equipment, connection list information corresponding to each piece of equipment, and equipment parent-child information corresponding to each piece of equipment. The control device 1 then generates an operation plan corresponding to one or more pieces of equipment (hereinafter also called a first operation plan) based on each of the identified first generation rules. The learning equipment is, for example, one or more pieces of equipment different from the one or more pieces of equipment that generate the operation plans (for example, one or more pieces of equipment installed in a different plant from the one or more pieces of equipment that generate the operation plans).

[0016] As a result, the control device 1 in this embodiment can automatically and easily generate operating plans corresponding to one or more devices that are the target of operating plan generation, for example, by using the generated learning model. Therefore, the control device 1 can reduce the workload of the operator associated with generating operating plans.

[0017] Furthermore, the control device 1 in this embodiment can automatically generate driving plans, for example, thereby preventing human errors such as omissions in creation or updates, compared to when an operator manually generates driving plans.

[0018] [Hardware configuration of control device 1] Next, the hardware configuration of the control device 1 will be described. Figure 2 is a diagram illustrating the hardware configuration of the control device 1 in the first embodiment.

[0019] The control device 1 is, for example, an electronic device having an electronic circuit. Specifically, as shown in Figure 2, the control device 1 is a computer device having, for example, a CPU (Central Computing Unit) 101 which is a processor, memory 102, a communication device 103, and a storage medium 104. Each part is connected to the others, for example, via a bus 105.

[0020] The storage medium 104 has, for example, a program storage area (not shown) for storing a program 110 for performing the driving plan generation process. The storage medium 104 also has, for example, a storage unit 130 (hereinafter also referred to as the information storage area 130) for storing information used when performing the driving plan generation process. The storage medium 104 may be, for example, an HDD (Hard Disk Drive) or an SSD (Solid State Drive).

[0021] The CPU 101 performs the driving plan generation process, for example, by executing a program 110 loaded into memory 102 from the storage medium 104.

[0022] The communication device 103 accesses the operating terminal 5 via a network NW, such as the Internet.

[0023] Furthermore, the electronic circuitry of the control device 1 may be, for example, an FPGA (Field Programmable Gate Array) or an ASIC (Application Specific Integrated Circuit). The operation plan generation process may also be performed, for example, on the FPGA or ASIC.

[0024] [Functions of Control Device 1] Next, the functions of the control device 1 will be described. Figure 3 is a block diagram of the functions of the control device 1 in the first embodiment. Figure 4 is a block diagram of the information stored in the information storage area 130 in the first embodiment.

[0025] As shown in Figure 3, the control device 1 implements various functions, including an information receiving unit 111, an information management unit 112, an equipment information generation unit 113, an information identification unit 114, a generation rule prediction unit 115, an operation plan generation unit 116, an operation plan output unit 117, and a model learning unit 118, through the organic cooperation of hardware such as the CPU 101 and memory 102 and a program.

[0026] Furthermore, as shown in Figure 4, the control device 1 stores, for example, equipment standard information 131, operation plan rule information 132, connection point information 133, equipment information 141, equipment parent-child information 142, operation plan information 151, and learning model MD in the information storage area 130. Specifically, the equipment standard information 131 includes, for example, type parent-child information 131a and type detailed information 131b. Also, the equipment information 141 includes, for example, equipment list information 141a and connection list information 141b.

[0027] The following explanation assumes that the driving plan generation system 1000 has one control device 1, but it is not limited to this. Specifically, the driving plan generation system 1000 may have, for example, multiple control devices 1. In this case, the multiple control devices 1 may, for example, perform each process in a distributed manner.

[0028] First, we will explain the functions in the process of associating the necessary information with the equipment standard information 131 (hereinafter also referred to as the information preparation process). The following explanation assumes that the equipment standard information 131 is pre-stored in the information storage area 130. The equipment standard information 131 includes, for example, information such as attributes and symbols for each type of equipment (hereinafter also referred to as a class).

[0029] The information receiving unit 111 receives, for example, the operation plan rule information 132 entered by the operator via the operation terminal 5. The operation plan rule information 132 is, for example, information for each type of equipment, and is information that shows the generation rules for operation plan information 151 for the corresponding equipment for each type. Specifically, the operation plan rule information 132 is, for example, information generated based on the standard operation plan information for each piece of equipment, and is information that includes variables (hereinafter simply referred to as variables) consisting of conversion rules enclosed in "%" at both ends. The information management unit 112 then stores, for example, the operation plan rule information 132 received by the information receiving unit 111 in the information storage area 130. Note that, for example, there may be multiple pieces of operation plan rule information 132 for each type. That is, the operation plan rule information 132 may exist for each more subdivided unit of equipment type.

[0030] Furthermore, the information receiving unit 111 receives connection point information 133, for example, input by the operator via the operation terminal 5. The connection point information 133 is, for example, information for each type of equipment, and indicates the attributes of the connection points between the corresponding equipment and other equipment. In other words, the connection point information 133 is, for example, information that indicates attributes used to search for (identify) other equipment located upstream or downstream of the corresponding equipment. The information management unit 112 then stores the connection point information 133 received by the information receiving unit 111 in the information storage area 130.

[0031] Subsequently, as shown in Figure 4, the information management unit 112 associates, for example, the information for each type of equipment contained in the equipment standard information 131 stored in the information storage area 130 with the corresponding operation plan rule information 132 and connection point information 133. Hereafter, the explanation will assume that the operation plan rule information 132 and connection point information 133 are included in the equipment standard information 131. In other words, hereafter, the equipment standard information 131, the operation plan rule information 132 and the connection point information 133 will be collectively referred to simply as equipment standard information 131.

[0032] Next, we will explain the functions of the process that generates a learning model for estimating the operating plan rule information 132 corresponding to each device (hereinafter also referred to as the model learning process).

[0033] The model learning unit 118 generates a learning model by performing machine learning on training data, for example, which includes equipment standard information 131 corresponding to the learning device and facility information 141 corresponding to the learning device.

[0034] Specifically, the model learning unit 118 generates a learning model by performing machine learning on training data that includes, for example, information generated using at least one of the following: connection point information 133 corresponding to the type of learning device, device list information 141a corresponding to the learning device, connection list information 141b corresponding to the learning device, and device parent-child information 142 corresponding to the learning device, as well as information indicating driving plan rule information 132 corresponding to the learning device. The information management unit 112 then stores the generated learning model in the information storage area 130, for example.

[0035] Next, we will explain the functions of the process that generates equipment information 141 (hereinafter also referred to as the equipment information generation process).

[0036] The equipment information generation unit 113 receives, for example, a specification from the operator on a generation screen (not shown) displayed on the operation terminal 5, which includes information indicating one or more pieces of equipment and information indicating the connection relationships between one or more pieces of equipment.

[0037] Specifically, the equipment information generation unit 113 accepts, for example, the specification of a symbol corresponding to the type of equipment (i.e., an icon corresponding to the type of equipment) and the attributes of the symbol corresponding to the type of equipment, on a pre-prepared generation screen. In this case, the equipment information generation unit 113 also accepts, for example, the specification of information indicating the connection relationships of each symbol.

[0038] The equipment information generation unit 113 then generates equipment information 141 from the information specified via the generation screen, for example. Specifically, the equipment information generation unit 113 generates equipment list information 141a, which is information about each piece of equipment included in the equipment information 141, and connection list information 141b, which is information about the connection status of each piece of equipment included in the equipment information 141, from the information specified via the generation screen. Subsequently, the information management unit 112 stores the equipment information 141 generated by the equipment information generation unit 113 in the information storage area 130, for example.

[0039] Furthermore, the equipment information generation unit 113 accepts, for example, the operator's specification of information indicating the parent-child relationship of one or more pieces of equipment on the generation screen. The equipment information generation unit 113 then generates equipment parent-child information 142, which indicates the parent-child relationship of each piece of equipment included in the equipment information 141, from the information specified via the generation screen. Subsequently, the information management unit 112 stores, for example, the equipment parent-child information 142 generated by the equipment information generation unit 113 in the information storage area 130. Hereafter, the explanation will assume that the equipment parent-child information 142 is included in the equipment information 141. That is, hereafter, the equipment information 141 and the equipment parent-child information 142 will be collectively referred to simply as equipment information 141.

[0040] Next, we will explain the functions of the process that generates the driving plan information 151 (hereinafter also referred to as the driving plan generation main process).

[0041] The information identification unit 114, for example, refers to the equipment standard information 131 stored in the information storage area 130 and identifies the equipment standard information 131 (first equipment standard information 131) corresponding to the type (first type) in which each piece of equipment is included in the equipment information 141 generated by the equipment information generation unit 113.

[0042] Specifically, the information identification unit 114, for example, refers to the type parent-child information 131a contained in the equipment standard information 131 stored in the information storage area 130, and identifies the type of each piece of equipment for each of the one or more pieces of equipment contained in the equipment information 141. The type parent-child information 131a is, for example, information that shows the parent-child relationship between different types, and the type that corresponds to the child inherits the attributes of the type that corresponds to the parent.

[0043] The generation rule prediction unit 115, for example, uses the learning model MD stored in the information storage area 130 to identify, for each of the one or more devices included in the equipment information 141 stored in the information storage area 130, the operation plan rule information 132 corresponding to each device (hereinafter also referred to as the first operation plan rule information 132) from the operation plan rule information 132 included in the equipment standard information 131 stored in the information storage area 130.

[0044] Specifically, the generation rule prediction unit 115 inputs information into the learning model, for example, for each of the one or more devices included in the equipment information 141, using at least one of the following: connection point information 133 corresponding to the type of each device, device list information 141a corresponding to each device, connection list information 141b corresponding to each device, and device parent-child information 142 corresponding to each device. The generation rule prediction unit 115 then identifies, for example, the first operation plan rule information 132 indicated by the information output from the learning model MD.

[0045] More specifically, the generation rule prediction unit 115 identifies, for example, among the operation plan rule information 132 included in the first equipment standard information 131 corresponding to each piece of equipment, the operation plan rule information 132 for which the value indicating the likelihood that it is the first operation plan rule information 132 corresponding to each piece of equipment (the value output by the learning model MD) is greater than or equal to a threshold, as the first operation plan rule information 132 corresponding to each piece of equipment.

[0046] The operation plan generation unit 116 generates operation plan information 151 corresponding to each of the one or more pieces of equipment included in the equipment information 141, based on each of the first operation plan rule information 132 identified by the generation rule prediction unit 115.

[0047] Specifically, the operation plan generation unit 116, for example, if a variable exists in the operation plan rule information 132 corresponding to each piece of equipment, refers to at least one of the connection point information 133, equipment list information 141a, connection list information 141b, and equipment parent-child information 142 to identify the equipment corresponding to the variable (hereinafter also referred to as the first equipment) for each piece of equipment included in the equipment information 141. Subsequently, the operation plan generation unit 116 generates operation plan information 151 corresponding to one or more pieces of equipment by associating the first equipment corresponding to each piece of equipment with the variable corresponding to each piece of equipment for each piece of equipment included in the equipment information 141.

[0048] In other words, the operation plan generation unit 116 generates operation plan information 151 corresponding to one or more devices by, for example, converting the variables in the operation plan rule information 132 corresponding to each device into information indicating the first device corresponding to each device (for example, the name of the first device) for each of the one or more devices included in the equipment information 141.

[0049] The operation plan rule information 132 may include a program (hereinafter also referred to as the expansion program) that automatically generates operation plan information 151 from the operation plan rule information 132 by referring to at least one of the following: connection point information 133, equipment list information 141a, connection list information 141b, and equipment parent-child information 142. The operation plan generation unit 116 may generate the operation plan information 151 by executing the expansion program, for example.

[0050] The driving plan output unit 117 outputs, for example, the driving plan information 151 generated by the driving plan generation unit 116. Specifically, the driving plan output unit 117 outputs the driving plan information 151 to, for example, the operation terminal 5.

[0051] [Driving plan generation process in the first embodiment] Next, the operation plan generation process in the first embodiment will be described. Figures 5 to 8 are flowcharts illustrating the operation plan generation process in the first embodiment. Figures 9 to 29 are diagrams illustrating the details of the operation plan generation process in the first embodiment.

[0052] In the following explanation, we will assume that the equipment standard information 131 is information for each type of equipment managed by Intelligent P&ID (Intelligent Piping & Instrument Diagram). Furthermore, in the following explanation, we will assume that the equipment information generation unit 113 is a function that generates equipment information 141 using the functions of Intelligent P&ID.

[0053] [Information preparation process] First, we will explain the information preparation process within the driving plan generation process. Figure 5 is a flowchart illustrating the information preparation process in the first embodiment.

[0054] As shown in Figure 5, the information management unit 112 associates, for example, the information for each type of equipment contained in the equipment standard information 131 stored in the information storage area 130 with the corresponding operating plan rule information 132 (step S1 in Figure 5).

[0055] Furthermore, the information management unit 112 further associates the connection point information 133 corresponding to each type of equipment with the equipment standard information 131 stored in the information storage area 130 (step S2 in Figure 5). In other words, steps S1 and S2 are processes that add information for automatically generating the operation plan information 151 to the equipment standard information 131 in the intelligent P&ID. A specific example of the equipment standard information 131 will be described below.

[0056] [Specific examples of equipment standard information 131] Figures 9 to 12 illustrate specific examples of equipment standard information 131. Specifically, Figure 9 illustrates a specific example of type parent-child information 131a. Figure 10 illustrates information about the type of equipment (hereinafter also referred to as equipment type information 131b1) from the type details information 131b. Figure 11 illustrates information about the type of connection between equipment (hereinafter also referred to as connection type information 131b2) from the type details information 131b. Figure 12 illustrates a specific example of equipment type information 131b1 after the operation plan rule information 132 and connection point information 133 have been associated in steps S1 and S2. Figure 13 illustrates a specific example of symbols in intelligent P&ID.

[0057] Furthermore, the equipment standard information 131, the operation plan rule information 132, and the connection point information 133 may be generated for each plant that is the target of the generation of the operation plan information 151 (for example, for each of multiple plants such as a water treatment plant, a power plant, and a chemical plant).

[0058] [Specific example of type parent-child information 131a] First, we will explain a specific example of type parent-child information 131a.

[0059] The parent-child type information 131a shown in Figure 9 indicates that, for example, "volute pump," "submersible pump," and "single-screw eccentric pump" belong to the "pump" category. In other words, the parent-child type information 131a shown in Figure 9 indicates that, for example, a parent-child relationship exists where "pump" is the parent type and "volute pump," "submersible pump," and "single-screw eccentric pump" are the child types, and that the attributes of the parent type "pump" are inherited by the child types "volute pump," "submersible pump," and "single-screw eccentric pump."

[0060] Furthermore, the parent-child type information 131a shown in Figure 9 indicates that, for example, "Level Meter (Electrode Rod Type)", "Level Meter (Paddle Type)", and "Level Meter (Photocell Type)" belong to "Level Meter". In other words, the parent-child type information 131a shown in Figure 9 indicates that, for example, "Level Meter" is the parent type and "Level Meter (Electrode Rod Type)", "Level Meter (Paddle Type)", and "Level Meter (Photocell Type)" are the child types, and that the attributes of the parent type "Level Meter" are inherited by the child types "Level Meter (Electrode Rod Type)", "Level Meter (Paddle Type)", and "Level Meter (Photocell Type)".

[0061] [Specific example of equipment type information 131b1 (1)] Next, we will explain a specific example of equipment type information 131b1.

[0062] The equipment type information 131b1 shown in Figure 10 has the following items: "Type" where various types are set, "Parent Type" where the type corresponding to the parent of each type is set, "Attribute Item" where the attribute items of the equipment corresponding to each type are set, and "Symbol" where the identification information of the symbol corresponding to the type in which each equipment is included is set. The "Attribute Item" includes, for example, the name of each equipment, the identification information of each equipment, the number of each equipment, information indicating the manufacturer of each equipment, and information indicating the model number of each equipment. In other words, the "Parent Type" column in Figure 10 is a table representation of the content explained in Figure 9. Hereafter, the explanation will assume that "-" is set for items where no information is set.

[0063] Specifically, in the equipment type information 131b1 shown in Figure 10, the information in the first row includes, for example, "Pump" as the "Type", "-" as the "Parent Type", "A1" as the "Attribute Item", and "C011" as the "Symbol".

[0064] Furthermore, in the equipment type information 131b1 shown in Figure 10, the information in the second row includes, for example, "Centrifugal pump" as the "Type," "Pump" as the "Parent Type," "A11" as the "Attribute Item," and "C012" as the "Symbol."

[0065] Furthermore, in the equipment type information 131b1 shown in Figure 10, the information in the third row includes, for example, "Submersible Pump" as the "Type," "Pump" as the "Parent Type," "A12" as the "Attribute Item," and "C013" as the "Symbol." Explanations of other information included in Figure 10 are omitted.

[0066] [Specific example of connection type information 131b2] Next, we will explain a specific example of connection type information 131b2.

[0067] The connection type information 131b2 shown in Figure 11 includes the following items: "Type," which sets the various types of connection devices such as pipes and wiring (hereinafter also referred to as connection devices); "Parent Type," which sets the type that corresponds to the parent of each type; "Attribute Item," which sets the attribute items of the connection devices corresponding to each type; and "Symbol," which sets the identification information of the symbol corresponding to the type in which each device is included. The "Attribute Item" includes, for example, the identification information of each connection device, the type of each connection device, the material of each connection device, and the size of each connection device.

[0068] Specifically, in the connection type information 131b2 shown in Figure 11, the information in the first row includes, for example, "Piping" as the "Type", "-" as the "Parent Type", "C1" as the "Attribute Item", and "C031" as the "Symbol".

[0069] Furthermore, in the connection type information 131b2 shown in Figure 11, the information in the second row includes, for example, "Wiring" as the "Type," "-" as the "Parent Type," "D1" as the "Attribute Item," and "C041" as the "Symbol." Explanation of the other information included in Figure 11 is omitted.

[0070] [Specific example of equipment type information 131b1 (2)] Next, we will explain other specific examples of the equipment type information 131b1. Specifically, we will explain specific examples of the equipment type information 131b1 after the operation plan rule information 132 and connection point information 133 have been associated in steps S1 and S2.

[0071] The equipment type information 131b1 shown in Figure 12 includes, for example, the items described in Figure 10, as well as "operation plan rule information," which contains the identification information of the operation plan rule information 132 associated in step S1, and "connection point information," which contains the contents of the connection point information 133 associated in step S2.

[0072] Specifically, in the equipment type information 131b1 shown in Figure 12, the information in the first row includes, for example, "Pump" as the "Type", "-" as the "Parent Type", "A1" as the "Attribute Item", "C011" as the "Symbol", and "132a" as the "Operation Plan Rule Information". Also, in the equipment type information 131b1 shown in Figure 12, the information in the first row includes, for example, "Connection Point Information", which includes "First Connection Point: upstream", indicating that the first connection point of equipment whose "Type" is "Pump" (hereinafter also referred to as the first connection point) is a connection point to other equipment located upstream, and "Second Connection Point: downstream", indicating that the second connection point of equipment whose "Type" is "Pump" (hereinafter also referred to as the second connection point) is a connection point to other equipment located downstream.

[0073] In other words, the equipment type information 131b1 shown in Figure 12 indicates, for example, that the "attribute item" corresponding to the pump is "A1", the "symbol" corresponding to the pump is "C011", the "operation plan rule information" corresponding to the pump is "132a", and the "connection point information" corresponding to the pump is "first connection point: upstream" and "second connection point: downstream".

[0074] Furthermore, in the equipment type information 131b1 shown in Figure 12, the information in the second row includes, for example, "Centrifugal pump" as the "Type", "Pump" as the "Parent Type", "A11" as the "Attribute Item", "C012" as the "Symbol", and "-" as the "Operation Plan Rule Information". Also, in the equipment type information 131b1 shown in Figure 12, the information in the second row includes, for example, "Third connection point: sealwater" as the "Connection point information", indicating that the third connection point (hereinafter also referred to as the third connection point) of the equipment whose "Type" is "Centrifugal pump" is the connection point to the piping (not shown) into which the shaft seal water is injected.

[0075] Here, the parent-child type information 131a shown in Figure 9 indicates, for example, that "volute pump" is a type that is a child of "pump". Therefore, "volute pump" inherits, for example, the information in the first row of the equipment type information 131b1 shown in Figure 12 (information about "pump"). That is, the equipment type information 131b1 shown in Figure 12 indicates, for example, that the "operation plan rule information" corresponding to the volute pump is "132a", and the "connection point information" corresponding to the volute pump is "first connection point: upstream", "second connection point: downstream", and "third connection point: sealwater".

[0076] Furthermore, in the equipment type information 131b1 shown in Figure 12, the information in the third row is set as follows: for example, "Type" is set to "Submersible Pump", "Parent Type" is set to "Pump", "Attribute Item" is set to "A12", "Symbol" is set to "C013", and "Operation Plan Rule Information" is set to "-". Also, in the equipment type information 131b1 shown in Figure 10, the information in the third row is set as follows: for example, "Connection Point Information" is set to "-".

[0077] Here, the parent-child type information 131a shown in Figure 9 indicates, for example, that "submersible pump" is a type that is a child of "pump". Therefore, "submersible pump" inherits, for example, the information in the first line of the equipment type information 131b1 shown in Figure 12 (information about "pump"). That is, the equipment type information 131b1 shown in Figure 12 indicates, for example, that the "operation plan rule information" corresponding to the submersible pump is "132a", and the "connection point information" corresponding to the submersible pump is "first connection point: upstream" and "second connection point: downstream". Explanation of other information included in Figure 12 is omitted.

[0078] [Specific examples of symbols in intelligent P&ID] Next, we will explain specific examples of symbols in Intelligent P&ID. Specifically, Figure 13 is a diagram illustrating the symbol S corresponding to a centrifugal pump in the equipment type information 131b1 (equipment type information 131b1 after the operation plan rule information 132 and connection point information 133 have been associated) as explained in Figure 12.

[0079] Specifically, the equipment type information 131b1 (connection point information 133) explained in Figure 12 indicates, for example, that the connection points corresponding to the centrifugal pump are "first connection point: upstream," "second connection point: downstream," and "third connection point: sealwater."

[0080] Therefore, as shown in Figure 13, the symbol S corresponding to the centrifugal pump is associated with information indicating that the connection attribute corresponding to the first connection point (the connection point on the left in Figure 13) is "upstream", information indicating that the connection attribute corresponding to the second connection point (the connection point on the right in Figure 13) is "downstream", and information indicating that the connection attribute corresponding to the third connection point (the upper connection point in Figure 13) is "sealwater".

[0081] [Specific examples of Driving Plan Rule Information 132] Next, we will explain specific examples of the operation plan rule information 132. Figures 14 and 15 illustrate specific examples of the operation plan rule information 132. Specifically, Figure 14 illustrates a specific example of the operation plan rule information 132 (hereinafter also referred to as operation plan rule information 132a) corresponding to each piece of equipment of type pump. Figure 15 also illustrates a specific example of the operation plan rule information 132 (hereinafter also referred to as operation plan rule information 132b) corresponding to each piece of equipment of type level meter. Below, we will explain the case where there is one operation plan rule information 132 corresponding to each type. Specific examples of cases where there are multiple operation plan rule information 132 corresponding to each type will be described later.

[0082] The conversion rules included in the variables in the operation plan rule information 132 shown in Figure 14, etc., include, for example, "Me" which indicates the controlled device, "Parent" which indicates a device whose parent-child relationship is that of the controlled device, "Upstream" which indicates a device located upstream of the controlled device, and "Downstream" which indicates a device located downstream of the controlled device. In addition, the conversion rules included in the variables in the operation plan rule information 132 shown in Figure 14, etc., include, for example, "Pump" which indicates a device of type pump, "Switch" which indicates a device of type switch, "Ls" which indicates a device of type level meter, and "Ts" which indicates a device of type thermometer. Furthermore, the conversion rules included in the variables in the operation plan rule information 132 shown in Figure 14, etc., include, for example, "Run" indicating the operating status of the equipment, "H" indicating that the measured value of the equipment has become above the first upper threshold, "HH" indicating that the measured value of the equipment has become above the second upper threshold which is greater than the first upper threshold, "L" indicating that the measured value of the equipment has become below the first lower threshold, "LL" indicating that the measured value of the equipment has become below the second lower threshold which is smaller than the first lower threshold, and "H to L" indicating that the measured value of the equipment has progressed from above the first upper threshold to the first lower threshold.

[0083] Specifically, the operation plan rule information 132a shown in Figure 14 indicates, for example, the provision of an isolated operation circuit that outputs an operation signal in response to the input of a mode signal, an operation signal, an automatic operation signal, and an interlock signal. The mode signal is a signal output from the mode switch that indicates "automatic" or "manual". The operation signal is a signal output from the operation switch that indicates "operate" or "stop". The automatic operation signal is expressed as "%Me%.automatic operation command" and indicates an automatic operation command for the controlled pump. The interlock signal is expressed as "%Upstream.Ls%.LL" and indicates that the level meter installed on the equipment upstream of the controlled pump has fallen below the second lower threshold.

[0084] Furthermore, the operation plan rule information 132a shown in Figure 14 indicates the provision of an AND circuit that takes as input what is expressed as "%Me%.Automatic Mode", what is expressed as "%Upstream.Ls%.H to L", and what is expressed as "%Downstream.Ls%.H", and outputs what is expressed as "%Me%.Automatic Operation Command". "%Me%.Automatic Mode" indicates that the mode signal of the controlled object is "Automatic". "%Upstream.Ls%.H to L" indicates that the value of the level meter installed on the upstream equipment of the controlled object has progressed from above the first upper threshold to below the first lower threshold. "%Downstream.Ls%.H" indicates that the value of the level meter installed on the downstream equipment has fallen below the first lower threshold.

[0085] Furthermore, the operation plan rule information 132b shown in Figure 15 indicates the provision of a standard logic circuit that takes something expressed as "%Me%" as input and outputs something expressed as "%Parent.Name%.HH", "%Parent.Name%.H", "%Parent.Name%.L", "%Parent.Name%.LL", and "%Parent.Name%.H to L". "Me" indicates the measured value of the controlled object. "%Parent.Name%.HH" indicates that the water level of the device whose parent-child relationship is that of the controlled object has reached or exceeded the second upper limit threshold. "%Parent.Name%.H" indicates that the water level of the device whose parent-child relationship is that of the controlled object has reached or exceeded the first upper limit threshold. "%Parent.Name%.L" indicates that the water level of the device whose parent-child relationship is that of the controlled object has reached or exceeded the first lower limit threshold. Furthermore, "%Parent.Name%.LL" indicates that the water level of the device whose parent relationship corresponds to the controlled device has fallen below the second lower threshold. Also, "%Parent.Name%.H to L" indicates that the water level of the device whose parent relationship corresponds to the controlled device has progressed from above the first upper threshold to down to the first lower threshold.

[0086] [Model generation process] Next, we will explain the model generation process, which is part of the driving plan generation process. Figure 6 is a flowchart illustrating the model generation process in the first embodiment.

[0087] As shown in Figure 6, the model learning unit 118 generates training data DT (multiple training data DT) which includes information generated using at least one of the following: connection point information 133 corresponding to the type of learning device, device list information 141a corresponding to the learning device, connection list information 141b corresponding to the learning device, and device parent-child information 142 corresponding to the learning device, as well as information indicating the driving plan rule information 132 corresponding to the learning device (step S101 in Figure 6).

[0088] Specifically, as shown in Figure 16, the operator inputs, for example, connection point information 133 corresponding to the type of learning device, device list information 141a corresponding to the learning device, connection list information 141b corresponding to the learning device, device parent-child information 142 corresponding to the learning device, and information indicating the driving plan rule information 132 corresponding to the learning device (for example, identification information for the driving plan rule information 132) to the control device 1. The model learning unit 118 then generates training data DT which includes, for example, information generated using at least one of the connection point information 133 corresponding to the type of learning device, device list information 141a corresponding to the learning device, connection list information 141b corresponding to the learning device, and device parent-child information 142 corresponding to the learning device, as well as information indicating the driving plan rule information 132 corresponding to the learning device. Subsequently, the information management unit 112 stores the generated training data DT in the information storage area 130.

[0089] The operator may, for example, input the generated training data DT into the control device 1. The information management unit 112 may, for example, store the input generated training data DT in the information storage area 130. A specific example of the training data DT will be described below.

[0090] [Specific examples of training data (DT)] Figures 27 to 29 illustrate specific examples of training data DT. Each of Figures 27 to 29 is a specific example of one of several training data sets DT used to train the learning model MD.

[0091] The training data DT shown in Figure 27, etc., has the following items: a "parent-child connection vector" which contains vectors indicating the parent-child relationship and connection relationship of each device identified from the connection point information 133 corresponding to the type of device, the connection list information 141b corresponding to each device, and the device parent-child information 142 corresponding to each device; a "type vector" which contains vectors indicating the type of each device identified from the device list information 141a corresponding to each device; and a "name vector" which contains vectors indicating the name of each device identified from the device list information 141a corresponding to each device. The training data DT shown in Figure 27, etc., also has the following items: a "number" which contains the number of each device identified from the device list information 141a corresponding to each device; and "operation plan rule information" which contains identification information of the operation plan rule information 132 corresponding to each device.

[0092] Specifically, in the training data DT shown in Figure 27, etc., the "parent-child connection vector" is set to a vector (hereinafter also called the first vector) that indicates the parent-child relationship between each device and other devices. Specifically, the "parent-child connection vector" is set to a value such as "1" as the first value, which is the first vector corresponding to the other device that is the parent of each device, or "0" as the first vector corresponding to a device other than the other device that is the parent of each device.

[0093] Furthermore, the "parent-child connection vector" in the training data DT shown in Figure 27, etc., is set to a two-dimensional vector (hereinafter also called the second vector) that indicates the connection relationship between each device and other devices (for example, the placement position of other devices relative to the placement position of each device). Specifically, the "parent-child connection vector" is set to, for example, "1,0", which is the second vector corresponding to other devices connected to each device at the upstream connection point of each device, "-1,0", which is the second vector corresponding to other devices connected to each device at the downstream connection point of each device, and "0,1", which is the second vector corresponding to other devices connected to each device at other connection points of each device. Other connection points are, for example, connection points other than the upstream and downstream connection points of each device (e.g., sealwater).

[0094] Furthermore, in the training data DT shown in Figure 27, etc., the "type vector" is set to a vector indicating the type of each piece of equipment. Specifically, the "type vector" is set to "Km", which indicates the type of pump for a transfer pump. The "type vector" is also set to "Kn1", which indicates the type of tank for a sludge storage tank. The "type vector" is also set to "Kn2", which indicates the type of hopper for a sludge hopper. The "type vector" is also set to "Kn3", which indicates the type of level meter for a sludge storage tank level meter or a sludge hopper level meter.

[0095] Furthermore, in the training data DT shown in Figure 27, etc., the "name vector" is set to a vector indicating the name of each piece of equipment. Specifically, the "name vector" is set to "Nm", for example, to indicate the name of the transfer pump. The "name vector" is also set to "Nn1", for example, to indicate the name of the sludge storage tank. The "name vector" is also set to "Nn2", for example, to indicate the name of the sludge hopper. The "name vector" is also set to "Nn3", for example, to indicate the name of the sludge storage tank level gauge. The "name vector" is also set to "Nn4", for example, to indicate the name of the sludge hopper level gauge.

[0096] More specifically, in the training data DT shown in Figure 27, for example, in the first row, "0" is set as the first vector in the "parent-child connection vector," "0,0" is set as the second vector in the "parent-child connection vector," "Km" is set as the "type vector," "Nm" is set as the "name vector," and "1" is set as the "number of units." Also, in the training data DT shown in Figure 27, for example, in the second row, "0" is set as the first vector in the "parent-child connection vector," "-1,0" is set as the second vector in the "parent-child connection vector," "Kn1" is set as the "type vector," "Nn1" is set as the "name vector," and "1" is set as the "number of units." Also, in the training data DT shown in Figure 27, for example, in the third row, "0" is set as the first vector in the "parent-child connection vector," "1,0" is set as the second vector in the "parent-child connection vector," "Kn2" is set as the "type vector," "Nn2" is set as the "name vector," and "1" is set as the "number of units." Furthermore, the training data DT shown in Figure 27 includes, for example, "132c" as "driving plan rule information," which represents the driving plan rule information 132c (described later) shown in Figures 22 and 23.

[0097] Furthermore, in the training data DT shown in Figure 28, for example, in the first row, "0" is set as the first vector in the "parent-child connection vector," "0,0" is set as the second vector in the "parent-child connection vector," "Km" is set as the "type vector," "Nm" is set as the "name vector," and "2" is set as the "number of units." In addition, in the training data DT shown in Figure 28, for example, "L11" is set as the "driving plan rule information," which represents the part included in the equipment symbol L11 shown in Figure 23 (described later).

[0098] Furthermore, in the training data DT shown in Figure 29, for example, in the first row, "0" is set as the first vector in the "parent-child connection vector," "0,0" is set as the second vector in the "parent-child connection vector," "Km" is set as the "type vector," "Nm" is set as the "name vector," and "3" is set as the "number of units." In addition, in the training data DT shown in Figure 29, for example, "L12" is set as the "driving plan rule information," which represents the part included in the equipment symbol L12 shown in Figure 23 (described later).

[0099] In the example shown in Figure 27, etc., the connection point information 133, device list information 141a, connection list information 141b, and device parent-child information 142 may each be converted into vectors (numerical values) using, for example, Word2Vec.

[0100] Furthermore, while the example shown in Figure 27 and others describes training data DT that includes vectors identified from connection point information 133, device list information 141a, connection list information 141b, and device parent-child information 142, the explanation is not limited to this. Specifically, the training data DT may, for example, include the information contained in connection point information 133, device list information 141a, connection list information 141b, and device parent-child information 142 as is.

[0101] Returning to Figure 6, the model learning unit 118 generates a learning model MD by, for example, performing machine learning on the training data DT (multiple training data DT) generated in step S101 (step S102 in Figure 6).

[0102] Specifically, as shown in Figure 16, the model learning unit 118 generates a learning model MD by, for example, using the training data DT stored in the information storage area 130.

[0103] In other words, the model learning unit 118 generates a learning model MD capable of identifying a first operating plan rule information 132 suitable for generating operating plan information 151 corresponding to each piece of equipment included in the equipment information 141.

[0104] As a result, the control device 1 in this embodiment can automatically and easily generate operation plan information 151 corresponding to each piece of equipment by, for example, using a learning model MD. Therefore, the control device 1 can reduce the workload on operators associated with generating the operation plan information 151.

[0105] [Equipment Information Generation Process] Next, we will explain the equipment information generation process, which is part of the operation plan generation process. Figure 7 is a flowchart illustrating the equipment information generation process in the first embodiment.

[0106] As shown in Figure 7, the equipment information generation unit 113 accepts, for example, the operator's selection of one or more symbols (for example, by dragging and dropping each symbol from a list not shown) and the selection of attributes for one or more symbols on the generation screen (step S11 in Figure 7).

[0107] Specifically, the attributes of one or more symbols are substantive information corresponding to the "attribute items" of the equipment type information 131b1 explained in Figure 10. Specifically, the attributes of one or more symbols include, for example, the name of each piece of equipment, the identification information of each piece of equipment, the number of each piece of equipment, information indicating the manufacturer of each piece of equipment, and information indicating the model number of each piece of equipment. Therefore, for example, if the "attribute item" corresponding to the type that includes each symbol is "name of equipment," the worker will specify, as the attribute of each symbol, the name of the equipment represented by each symbol, such as "transfer pump."

[0108] In other words, in step S11, the operator specifies the attributes of each symbol along with the symbol itself, thereby making the equipment represented by each symbol identifiable from other equipment.

[0109] Furthermore, the equipment information generation unit 113 accepts, for example, the operator's specification of information indicating the connection relationship of one or more symbols on the generation screen displayed on the operation terminal 5 (step S12 in Figure 7).

[0110] The equipment information generation unit 113 then generates equipment information 141 from the information specified in steps S11 and S12, for example. The information management unit 112 then stores the generated equipment information 141 in the information storage area 130, for example.

[0111] Furthermore, the equipment information generation unit 113 accepts, for example, the specification of information indicating the parent-child relationship of one or more symbols specified by the operator on the generation screen (step S13 in Figure 7).

[0112] Then, in step S13, the equipment information generation unit 113 generates equipment parent-child information 142 from the information specified, for example, via the generation screen. After that, the information management unit 112 stores the generated equipment parent-child information 142 in the information storage area 130, for example.Specific examples of equipment information 141 and equipment parent-child information 142 will be described below.

[0113] [Specific example of equipment information 141 (1)] First, we will explain specific examples of equipment information 141. Figures 17 to 19 are diagrams illustrating specific examples of equipment information 141.

[0114] Steps S11 and S12 can be achieved, for example, through normal design work using Intelligent P&ID. Specifically, Figure 17 is a flowchart of the equipment created using Intelligent P&ID.

[0115] The equipment information 141 shown in Figure 17 includes, for example, information about the sludge storage tank OB1, the transfer pump OB2, and the sludge hopper OB3. Specifically, the equipment information 141 shown in Figure 17 indicates, for example, that the sludge storage tank OB1 and the transfer pump OB2 are connected. Also, the equipment information 141 shown in Figure 17 indicates, for example, that the transfer pump OB2 and the sludge hopper OB3 are connected. Furthermore, the equipment information 141 shown in Figure 17 indicates, for example, that a level meter OB11 (hereinafter also referred to as the sludge storage tank level meter OB11) is installed in the sludge storage tank OB1, and that a level meter OB31 (hereinafter also referred to as the sludge hopper level meter OB31) is installed in the sludge hopper OB3.

[0116] [Specific example of equipment information 141 (2)] Next, we will explain specific examples of equipment information 141. Figures 18 and 19 illustrate specific examples of equipment information 141. Specifically, Figure 18 illustrates a specific example of representing the equipment list information 141a, which is part of the equipment information 141 explained in Figure 17, in table format. Figure 19 also illustrates a specific example of representing the connection list information 141b, which is part of the equipment information 141 explained in Figure 17, in table format. In the following explanation, each piece of equipment will be assumed to belong to a group of other pieces of equipment that is its parent (hereinafter also referred to as an equipment group).

[0117] First, we will explain a specific example of equipment list information 141a.

[0118] The equipment list information 141a shown in Figure 18 includes, for example, the following items: "Type" which sets the type of each piece of equipment, "Equipment Name" which sets the name of each piece of equipment, "Attributes" which sets the attributes of each piece of equipment (attributes specified in step S11 of Figure 7), and "Equipment Group" which sets the equipment group to which each piece of equipment belongs.

[0119] Specifically, in the equipment list information 141a shown in Figure 18, the first row of information includes, for example, "Centrifugal pump" as the "Type," "Transfer pump" as the "Equipment name," and "Wastewater treatment facility" as the "Equipment group."

[0120] Furthermore, in the equipment list information 141a shown in Figure 18, the information in the second row includes, for example, "Level meter (electrode rod type)" as the "Type," "Sludge storage tank level meter" as the "Equipment name," and "Sludge storage tank" as the "Equipment group." Explanation of the other information included in Figure 18 is omitted.

[0121] Next, we will explain a specific example of connection list information 141b.

[0122] The connection list information 141b shown in Figure 19 includes, for example, the following items: "Type" which sets the type of each connected device; "Device Name 1. Connection Point" which sets the name of the first device connected by each connected device and the connection point of the first device; "Device Name 2. Connection Point" which sets the name of the second device connected by each connected device and the connection point of the second device; and "Connection Attributes" which sets the attributes of each connected device.

[0123] Specifically, in the connection list information 141b shown in Figure 19, the information in the first row includes, for example, "Piping" as the "Type," "Transfer Pump.Connection Point 1" as the "Equipment Name 1.Connection Point," and "Sludge Storage Tank.Connection Point 2" as the "Equipment Name 2.Connection Point."

[0124] Furthermore, in the connection list information 141b shown in Figure 19, the information in the second row includes, for example, "Piping" as the "Type," "Sludge Hopper.Connection Point 1" as the "Equipment Name 1.Connection Point," and "Transfer Pump.Connection Point 2" as the "Equipment Name 2.Connection Point." Explanation of other information included in Figure 19 is omitted.

[0125] [Specific example of device parent-child information 142] Next, we will explain a specific example of device parent-child information 142. Figure 20 is a diagram illustrating a specific example of device parent-child information 142.

[0126] The equipment parent-child information 142 shown in Figure 20 indicates, for example, that "water intake facilities," "pretreatment facilities," "membrane filtration facilities," "chemical injection facilities," "water supply facilities," and "wastewater treatment facilities" exist at a level one level below "AA Water Treatment Plant." In other words, the equipment parent-child information 142 shown in Figure 20 indicates that, for example, "AA Water Treatment Plant" is the parent and "water intake facilities," "pretreatment facilities," "membrane filtration facilities," "chemical injection facilities," "water supply facilities," and "wastewater treatment facilities" are the children, indicating that a parent-child relationship exists.

[0127] Furthermore, the equipment parent-child information 142 shown in Figure 20 indicates, for example, that the "sludge storage tank," "transfer pump," and "sludge hopper" exist at a level one level below the "wastewater treatment facility." In other words, the equipment parent-child information 142 shown in Figure 20 indicates that, for example, a parent-child relationship exists where the "wastewater treatment facility" is the parent and the "sludge storage tank," "transfer pump," and "sludge hopper" are the children.

[0128] Furthermore, the device parent-child information 142 shown in Figure 20 indicates, for example, that a "sludge storage tank level gauge" exists at a level one level below the "sludge storage tank." In other words, the device parent-child information 142 shown in Figure 20 indicates that, for example, a parent-child relationship exists where the "sludge storage tank" is the parent and the "sludge storage tank level gauge" is the child.

[0129] Furthermore, the device parent-child information 142 shown in Figure 20 indicates, for example, that a "sludge hopper level gauge" exists at a level one level below the "sludge hopper." In other words, the device parent-child information 142 shown in Figure 20 indicates that, for example, a parent-child relationship exists where the "sludge hopper" is the parent and the "sludge hopper level gauge" is the child. Explanations of other information included in Figure 20 are omitted.

[0130] The device parent-child information 142 can be edited on a screen like the one shown in Figure 20, for example, and is stored in the "device group" field in the device list information 141a described in Figure 18.

[0131] [Main process for generating driving plans] Next, we will explain the main process for generating the driving plan. Figure 8 is a flowchart illustrating the main process for generating the driving plan in the first embodiment.

[0132] The information identification unit 114 identifies, for example, one piece of equipment included in the equipment information 141 stored in the information storage area 130 (step S21 in Figure 8). Specifically, the information identification unit 114 identifies, for example, one piece of equipment included in the equipment information 141 generated in the equipment information generation process.

[0133] Then, the information identification unit 114 refers to, for example, the type parent-child information 131a contained in the device standard information 131 stored in the information storage area 130, and identifies the type to which the device identified in step S21 belongs (step S22 in Figure 8).

[0134] Next, the information identification unit 114 refers to, for example, the equipment standard information 131 stored in the information storage area 130 and identifies the first equipment standard information 131 corresponding to the type identified in step S22 (step S23 in Figure 8).

[0135] Then, the generation rule prediction unit 115, for example, uses the learning model MD stored in the information storage area 130 to identify the first operation plan rule information 132 corresponding to the equipment identified in step S21 from among the operation plan rule information 132 stored in the information storage area 130 (step S24 in Figure 8).

[0136] Specifically, as shown in Figure 21, the generation rule prediction unit 115 generates input data DT0 from at least one of the following: connection point information 133 corresponding to the first equipment standard information 131 identified in step S23, equipment list information 141a corresponding to the equipment identified in step S21, connection list information 141b corresponding to the equipment identified in step S21, and equipment parent-child information 142 corresponding to the equipment identified in step S21. The generation rule prediction unit 115 then stores the generated input data DT0 in the information storage area 130. Subsequently, the generation rule prediction unit 115 inputs the input data DT0 stored in the information storage area 130 to the learning model MD. The generation rule prediction unit 115 then identifies the first operation plan rule information 132 indicated by the information output from the learning model MD in response to the input of the input data DT0. A specific example of the input data DT0 will be described below.

[0137] [Specific example of input data DT0] Next, we will explain a specific example of input data DT0. Figure 35 is a diagram illustrating a specific example of input data DT0.

[0138] The input data DT0 shown in Figure 35 has the following items: "parent-child connection vector," "type vector," "name vector," and "number of units," similar to the training data DT described in Figure 27, for example. In other words, the input data DT0 shown in Figure 35 is data that has all the items of the training data DT described in Figure 27, for example, except for "driving plan rule information."

[0139] Specifically, the input data DT0 shown in Figure 35 has, for example, "0,-1,0" set as the "parent-child connection vector", "Ki" set as the "type vector", "Ni" set as the "name vector", and "1" set as the "number of units".

[0140] [Specific example of the process in step S24] Next, we will explain specific examples of the processing in step S24. Figures 22 and 23 illustrate specific examples of step S24. Specifically, Figure 22 is a diagram illustrating a specific example of the operation plan rule information 132 (hereinafter also referred to as conditional operation plan rule information 132) that includes the part corresponding to the equipment symbol L1. Figure 23 is a diagram illustrating another specific example of the conditional operation plan rule information 132 that includes the part corresponding to the equipment symbol L1. Note that in the conditional operation plan rule information 132 shown in Figure 23, unlike the conditional operation plan rule information 132 shown in Figure 22, the notation for parts other than the equipment symbol L1 is omitted.

[0141] In the examples shown in Figure 14, etc., the case where there is one corresponding driving plan rule information 132 for each type was explained. In contrast, the examples shown in Figures 22 and 23 explain the case where there are multiple corresponding driving plan rule information 132 for each type. That is, the examples shown in Figures 22 and 23 explain the case where each driving plan rule information 132 exists for units that are more finely subdivided by type.

[0142] Specifically, the operation plan rule information 132 shown in Figures 22 and 23 (hereinafter also referred to as operation plan rule information 132c) includes, for example, operation plan rule information 132 that does not include the part corresponding to equipment symbol L1 (hereinafter also referred to as normal operation plan rule information 132), as well as one or more conditional operation plan rule information 132. Then, in step S24 of Figure 8, the learning model MD, for example, uses the learning model MD to identify either the normal operation plan rule information 132 or one or more conditional operation plan rule information 132 as the operation plan rule information 132 corresponding to the equipment identified in step S21.

[0143] More specifically, in step S24 of Figure 8, if the name of the equipment corresponding to the equipment identified in step S21 (for example, the name of the equipment included in the information set in the "attributes" of equipment list information 141a) is not a transfer pump, the learning model MD outputs information indicating the normal operation plan rule information 132 (operation plan rule information 132 that does not include the part corresponding to equipment symbol L1) from the operation plan rule information 132 shown in Figure 22, as information indicating the operation plan rule information 132 corresponding to the equipment identified in step S21.

[0144] Furthermore, in step S24 of Figure 8, if, for example, the name of the equipment corresponding to the equipment identified in step S21 is a transfer pump, the learning model MD outputs information indicating the conditional operation plan rule information 132 (operation plan rule information 132 including the part corresponding to equipment symbol L1) from the operation plan rule information 132 shown in Figure 22 as information indicating the operation plan rule information 132 corresponding to the equipment identified in step S21.

[0145] Here, for example, if the name of the equipment corresponding to the equipment identified in step S21 is a transfer pump, and the number of transfer pumps (for example, the number included in the information set in the "attributes" of equipment list information 141a) is multiple, the learning model MD outputs information indicating the transfer pump and the conditional operation plan rule information 132 corresponding to the number of transfer pumps as information indicating the operation plan rule information 132 corresponding to the equipment identified in step S21.

[0146] In other words, for example, if there are two transfer pumps, the learning model MD outputs information indicating a conditional operation rule information 132 that includes the part corresponding to equipment symbol L11 in addition to the part corresponding to equipment symbol L11 of the operation rule information 132 shown in Figure 23 (in other words, a conditional operation rule information 132 that does not include the part corresponding to equipment symbol L12).

[0147] Furthermore, the learning model MD outputs information that, for example, when there are three transfer pumps, includes a conditional operation plan rule information 132 that includes not only the part corresponding to equipment symbol L1 but also the part corresponding to equipment symbol L12 (in other words, a conditional operation plan rule information 132 that does not include the part corresponding to equipment symbol L11) from the operation plan rule information 132 shown in Figure 23.

[0148] Returning to Figure 8, the operation plan generation unit 116, for example, takes at least one of the connection point information 133, equipment list information 141a, connection list information 141b, and equipment parent-child information 142 as input and converts the variables included in the operation plan rule information 132 identified in step S24 by executing an expansion program (not shown), thereby generating operation plan information 151 corresponding to the equipment identified in step S21 from the operation plan rule information 132 identified in step S24 (step S25 in Figure 8). Then, the information management unit 112 stores the operation plan information 151 generated by the operation plan generation unit 116 in the information storage area 130. A specific example of the operation plan information 151 will be described below.

[0149] [Specific example of Driving Plan Information 151] Figures 24 and 25 illustrate specific examples of the driving plan information 151. Specifically, Figure 24 illustrates a specific example of the driving plan information 151 (hereinafter also referred to as driving plan information 151a) generated from the driving plan rule information 132a described in Figure 14. Figure 25 also illustrates a specific example of the driving plan information 151 (hereinafter also referred to as driving plan information 151b) generated from the driving plan rule information 132b described in Figure 15.

[0150] Specifically, for example, when generating operation plan information 151a for the transfer pump OB2 in the equipment information 141 explained in Figure 17, the information identification unit 114 refers to the type parent-child information 131a explained in Figure 9, for example, and identifies "Pump," which is the parent of the "Centrifugal Pump" corresponding to the type of transfer pump OB2, as the "Type" of the transfer pump OB2. Then, the information identification unit 114 refers to the equipment type information 131b1 explained in Figure 10, for example, and identifies the operation plan rule information 132a (operation plan rule information 132a explained in Figure 14) corresponding to "132a" set in the "Operation Plan Rule Information" in the information (first row information) where "Pump" is set as the "Type".

[0151] Next, in the equipment type information 131b1 explained in Figure 10, the "connection point information" for the information where "type" is set to "pump" is set to "first connection point: upstream" and "second connection point: downstream". Then, the equipment information 141 explained in Figure 17 shows, for example, that the sludge storage tank OB1 and the transfer pump OB2 are connected, and the transfer pump OB2 and the sludge hopper OB3 are connected.

[0152] Therefore, for example, if the left connection point of the transfer pump OB2 shown in Figure 17 is the first connection point, the operation plan generation unit 116 determines that the sludge storage tank OB1 connected at the left connection point of the transfer pump OB2 is an upstream device of the transfer pump OB2. Also, for example, if the right connection point of the transfer pump OB2 shown in Figure 17 is the second connection point, the operation plan generation unit 116 determines that the sludge hopper OB3 connected at the right connection point of the transfer pump OB2 is an downstream device of the transfer pump OB2.

[0153] Therefore, in this case, the operation plan generation unit 116 executes the expansion program included in the operation plan rule information 132a shown in Figure 14, and as shown in Figure 24, for example, it interprets "%Upstream.Ls%" in the operation plan rule information 132a shown in Figure 14 as "a level meter installed in the upstream sludge storage tank" and sets the "sludge storage tank level meter", and interprets "%Downstream.Ls%" in the operation plan rule information 132a shown in Figure 14 as "a level meter installed in the downstream sludge hopper" and sets the "sludge hopper level meter". Explanation of other information included in Figure 24 is omitted.

[0154] Furthermore, for example, when generating operation plan information 151b for the sludge storage tank level meter OB11 in the equipment information 141 described in Figure 17, the information identification unit 114 refers to, for example, the type parent-child information 131a described in Figure 9, and identifies the "level meter" which is the parent of the "level meter (electrode rod type)" corresponding to the type of sludge storage tank level meter OB11. Then, the information identification unit 114 refers to, for example, the equipment type information 131b1 described in Figure 10, and identifies the operation plan rule information 132b (operation plan rule information 132b described in Figure 15) corresponding to "132b" set in the "operation plan rule information" in the information where "level meter" is set as the "type".

[0155] Next, the device parent-child information 142 explained in Figure 20 indicates that the parent of the sludge storage tank level gauge OB11 is the sludge storage tank OB1. Therefore, in this case, the operation plan generation unit 116 executes the expansion program included in the operation plan rule information 132b shown in Figure 15, and sets "Sludge Storage Tank" to "%Parent.Name%" in the operation plan rule information 132b shown in Figure 25, for example. Explanation of other information included in Figure 25 is omitted.

[0156] Returning to Figure 8, the information identification unit 114 determines, for example, whether all the equipment included in the equipment information 141 has been identified in step S21 (step S26 in Figure 8).

[0157] If, as a result, it is determined that not all devices have been identified (NO in step S26), the information identification unit 114 repeats, for example, steps S21 onwards.

[0158] On the other hand, if it is determined that all equipment has been identified (YES in step S26), the operation plan output unit 117 outputs each of the operation plan information 151 generated in step S25 (step S27 in Figure 8).

[0159] Specifically, the driving plan output unit 117 outputs each of the driving plan information 151 generated in step S25 to the operation terminal 5.

[0160] Furthermore, the operator may, for example, after step S27, input to the control device 1 the result of their judgment on whether the driving plan information 151 generated in step S25 (i.e., the driving plan information 151 generated from the driving plan rule information 132 identified by the learning model MD) is appropriate driving plan information 151. In this case, the model learning unit 118 may, for example, generate other training data (not shown) based on the operator's judgment on whether the driving plan information 151 generated in step S25 is appropriate, and further train the learning model MD using the generated other training data. Specifically, in this case, the model learning unit 118 may, for example, generate other training data including the input data DT0 input to the learning model MD in step S24 and the first driving plan rule information 132 indicated by the information output from the learning model MD in step S24, and further train the learning model MD using the generated other training data.

[0161] This makes it possible for the control device 1 to further improve the judgment accuracy of the learning model MD, for example.

[0162] [Specific example of output screen OP] Next, we will explain a specific example of the output screen OP for the driving plan information 151 on the operation terminal 5. Figure 26 is a diagram illustrating a specific example of the output screen OP for the driving plan information 151 on the operation terminal 5.

[0163] As shown in Figure 26, the operation plan output unit 117 may output, for example, equipment parent-child information 142 in addition to the operation plan information 151. Furthermore, the operation plan output unit 117 may have a function that allows editing of the equipment parent-child information 142.

[0164] Specifically, in this case, the operation plan output unit 117 may, for example, output the equipment parent-child information 142 to the output screen OP, and then accept the specification of equipment included in the equipment parent-child information 142 (specification by the operator). The operation plan output unit 117 may then, for example, output the operation plan information 151 corresponding to the specified equipment from among the generated operation plan information 151 (operation plan information 151 stored in the information storage area 130).

[0165] This allows operators viewing the output screen OP to also view, for example, the equipment parent-child information 142, thereby improving the readability of the operation plan information 151.

[0166] Furthermore, as shown in Figure 26, the operation plan output unit 117 may also output a component information IM to the output screen OP, which shows a list of components that can be added to the operation plan information 151. Specifically, in the example shown in Figure 26, the component information IM is displayed, which includes components such as "Isolation Operation" indicating the addition of an isolated operation circuit, and "Number of Units Control" indicating the addition of a control circuit for the number of units of equipment.

[0167] This allows an operator viewing the output screen OP to easily add content corresponding to a specified part to the driving plan information 151 by specifying a part included in the parts information IM, for example, if they determine that there is something missing in the driving plan information 151.

[0168] Furthermore, the driving plan output unit 117 may have a function that allows editing not only the driving plan information 151 but also the driving plan rule information 132.

[0169] The equipment information generation unit 113 may, for example, reflect information such as the operation plan information 151 generated in step S25 into the equipment information 141 stored in the information storage area 130.

[0170] As described above, the control device 1 in this embodiment stores in its storage unit equipment standard information 131, which associates, for each type of equipment, with operation plan rule information 132 corresponding to each type and connection point information 133 indicating the attributes of connection points between each type of equipment and other equipment.The control device 1 then receives input of equipment information 141, which includes, for example, equipment list information 141a indicating one or more equipment that are the target of generating operation plan information 151, connection list information 141b indicating connection relationships between one or more equipment, and equipment parent-child information 142 indicating parent-child relationships between one or more equipment.Next, the control device 1 refers to the equipment standard information 131 stored in the information storage area 130, for example, and identifies the first equipment standard information 131 corresponding to the first type for each of the one or more pieces of equipment.

[0171] Subsequently, the control device 1 identifies the first operation plan rule information 132 for each of the following devices by inputting, for each of the following information: information generated using at least one of the following: connection point information 133 corresponding to the type of learning device, device list information 141a corresponding to the learning device, connection list information 141b corresponding to the learning device, and device parent-child information 142 corresponding to the learning device, along with information indicating the first operation plan rule information 132 corresponding to the learning device, to a learning model MD that has been machine-trained on training data DT, which includes, for example, connection point information 133 corresponding to the type of learning device, device list information 141a corresponding to the learning device, connection list information 141b corresponding to the learning device, and device parent-child information 142 corresponding to the learning device, for each of the one or more devices. Then, the control device 1 generates operation plan information 151 corresponding to one or more devices based on each of the identified first operation plan rule information 132.

[0172] Furthermore, in this embodiment, the control device 1 generates a learning model MD by performing machine learning on training data DT before processing the input of equipment information 141.

[0173] As a result, the control device 1 in this embodiment can automatically and easily generate driving plan information 151 corresponding to one or more devices that are the target of driving plan information generation, for example, by using a learning model MD. Therefore, the control device 1 can reduce the workload of the operator associated with generating the driving plan information 151.

[0174] Furthermore, the control device 1 in this embodiment, for example, automatically generates the driving plan information 151, thereby preventing human errors such as omissions in creation or updates compared to when an operator manually generates the driving plan information 151.

[0175] Furthermore, devices whose information is included in the device list information 141a and the connection list information 141b correspond to devices whose information is included in the parent-child information 142. Therefore, the control device 1 in this embodiment can prevent, for example, the occurrence of omissions in the creation of the device list information 141a, the connection list information 141b, and the parent-child information 142.

[0176] Furthermore, in this embodiment, the control device 1 can, for example, generate device parent-child information 142 for one or more devices, thereby consolidating the operation plan information 151 for each device. As a result, the control device 1 can easily reuse the operation plan information 151 corresponding to each device having a parent-child relationship.

[0177] Furthermore, in this embodiment, the control device 1 generates the operation plan information 151 using, for example, the names of the equipment included in the equipment information 141, thereby preventing variations in the names of the equipment included in the operation plan information 151.

[0178] Furthermore, in this embodiment, the control device 1 generates operation plan information 151 using, for example, the names of equipment included in the equipment information 141, making it easy to generate new operation plan information 151 by reusing previously generated operation plan information 151.

[0179] Furthermore, in this embodiment, if the control device 1 is unable to generate operation plan information 151 from the operation plan rule information 132 corresponding to each piece of equipment (by executing the deployment program), it will be possible to detect that there is insufficient information in the connection point information 133 and equipment information 141.

[0180] Furthermore, in this embodiment, the control device 1 can further improve the judgment accuracy of the learning model MD by, for example, performing further learning on the first operation plan rule information 132 identified by the learning model MD that the operator has determined to be appropriate (for example, new operation plan rule information 132 that the operator was not aware of).

[0181] [Driving plan generation system 1000 in the second embodiment] Next, the configuration of the driving plan generation system 1000 in the second embodiment will be described. The differences from the driving plan generation system 1000 in the first embodiment will be described below.

[0182] [Functions of Control Device 1] First, the functions of the control device 1 in the second embodiment will be described. Figure 30 is a block diagram of the functions of the control device 1 in the second embodiment. Figure 31 is a block diagram of the information stored in the information storage area 130 in the second embodiment.

[0183] As shown in Figure 30, the control device 1 implements various functions, including an information receiving unit 111, an information management unit 112, an equipment information generation unit 113, an information identification unit 114, a generation rule prediction unit 115, an operation plan generation unit 116, an operation plan output unit 117, a model learning unit 118, and a generation rule identification unit 119, through the organic cooperation of hardware such as a CPU 101 and memory 102 with a program.

[0184] Furthermore, as shown in Figure 31, the control device 1 stores, for example, equipment standard information 131, operation plan rule information 132, connection point information 133, equipment information 141, equipment parent-child information 142, operation plan information 151, operation plan information 152, and learning model MD in the information storage area 130. Specifically, the equipment standard information 131 includes, for example, type parent-child information 131a and type detailed information 131b. Also, the equipment information 141 includes, for example, equipment list information 141a and connection list information 141b.

[0185] The following describes the main process for generating the operation plan in the second embodiment. Note that the information preparation process, model generation process, and equipment information generation process in the second embodiment are the same as those in the first embodiment, and therefore will not be described.

[0186] In the main process for generating the driving plan in the second embodiment, for example, the identification of the driving plan rule information 132 is performed by multiple processes. Then, in the main process for generating the driving plan in the second embodiment, for example, the driving plan information 151 and the driving plan information 152 are generated by using each of the driving plan rule information 132 identified by the multiple processes.

[0187] First, we will explain the process of identifying the driving plan rule information 132 using the learning model MD (hereinafter also referred to as the first generation rule identification process) within the main driving plan generation process in the second embodiment.

[0188] The generation rule prediction unit 115, as in the first embodiment, for example, uses a learning model MD stored in the information storage area 130 to identify the first operation plan rule information 132 corresponding to each piece of equipment from the operation plan rule information 132 contained in the equipment standard information 131 stored in the information storage area 130, for each piece of equipment included in the equipment information 141.

[0189] Next, we will explain the process of identifying the driving plan generation rule information 132 without using the learning model MD, which is part of the main driving plan generation process in the second embodiment (hereinafter also referred to as the second generation rule identification process).

[0190] The information identification unit 114, for example, refers to the equipment standard information 131 stored in the information storage area 130 and identifies the equipment standard information 131 (first equipment standard information 131) corresponding to the type (first type) in which each piece of equipment is included in the equipment information 141.

[0191] Specifically, the information identification unit 114, for example, refers to the type parent-child information 131a contained in the equipment standard information 131 stored in the information storage area 130, and identifies the type of each piece of equipment for each of the one or more pieces of equipment contained in the equipment information 141.

[0192] The generation rule identification unit 119 identifies, for example, for each of the one or more pieces of equipment included in the equipment information 141, the operation plan rule information 132 included in the first piece of equipment standard information 131 corresponding to each piece of equipment as the operation plan rule information 132 corresponding to each piece of equipment (hereinafter also referred to as the second operation plan rule information 132).

[0193] As a result, the control device 1 in this embodiment can identify the second operation plan rule information 132 without using, for example, the learning model MD. Therefore, even if, for example, the determination accuracy of the first operation plan rule information 132 identified using the learning model MD is insufficient, the control device 1 can identify the appropriate second operation plan rule information 132 corresponding to each device.

[0194] Furthermore, in this embodiment, the control device 1 also outputs the second driving plan rule information 132 identified without using the learning model MD, for example, eliminating the need to improve the judgment accuracy of the learning model MD as much as possible. Therefore, the control device 1 can suppress the occurrence of overfitting in the learning model MD.

[0195] Furthermore, the connection point information 133, equipment list information 141a, connection list information 141b, and equipment parent-child information 142 corresponding to each operation plan rule information 132 may be stored in the information storage area 130 in a state where they have been converted to data in the same format as the input data DT0 explained in Figure 35 (hereinafter also referred to as vector data). The generation rule identification unit 119 may, for example, convert the connection point information 133, equipment list information 141a, connection list information 141b, and equipment parent-child information 142 corresponding to each piece of equipment included in the equipment information 141 into vector data, and then identify the second operation plan rule information 132 corresponding to each piece of equipment by matching the converted vector data with the vector data stored in the information storage area 130 (vector data corresponding to each operation plan rule information 132).

[0196] Next, we will explain the process of generating and outputting the driving plan information 151 and the driving plan information 152 (hereinafter also referred to as the driving plan output process) within the main driving plan generation process of the second embodiment.

[0197] The operation plan generation unit 116 generates operation plan information 151 corresponding to one or more pieces of equipment included in the equipment information 141, based on the first operation plan rule information 132 (first operation plan rule information 132 corresponding to each of the one or more pieces of equipment included in the equipment information 141) identified by the generation rule prediction unit 115.

[0198] Specifically, the operation plan generation unit 116, for example, refers to connection point information 133 corresponding to equipment standard information 131 stored in the information storage area 130, and identifies connection points corresponding to variables in the first operation plan rule information 132 corresponding to each piece of equipment for each piece of equipment included in the equipment information 141 stored in the information storage area 130. Then, for each piece of equipment included in the equipment information 141, the operation plan generation unit 116 identifies the equipment to be connected at the connection point corresponding to each piece of equipment as the first piece of equipment corresponding to the variables in the first operation plan rule information 132 corresponding to each piece of equipment. Subsequently, the operation plan generation unit 116 generates operation plan information 151 corresponding to one or more pieces of equipment included in the equipment information 141 by setting the values ​​of the variables in the first operation plan rule information 132 corresponding to each piece of equipment to values ​​indicating the first piece of equipment corresponding to the variables in the first operation plan rule information 132 corresponding to each piece of equipment.

[0199] Similarly, the operation plan generation unit 116 generates operation plan information 152 corresponding to one or more pieces of equipment included in the equipment information 141, based on the second operation plan rule information 132 (second operation plan rule information 132 corresponding to each of the one or more pieces of equipment included in the equipment information 141) identified by the generation rule identification unit 119.

[0200] The driving plan output unit 117 outputs, for example, at least one of the driving plan information 151 and driving plan information 152 generated by the driving plan generation unit 116. Specifically, the driving plan output unit 117 outputs, for example, the driving plan information 151 and the driving plan information 152 to the operation terminal 5.

[0201] [Flowchart diagram of the main process for generating driving plans] Next, we will describe the flowchart of the main process for generating the driving plan in the second embodiment. Figure 32 is a flowchart illustrating the main process for generating the driving plan in the second embodiment.

[0202] The information identification unit 114 identifies, for example, one piece of equipment included in the equipment information 141 stored in the information storage area 130 (step S41 in Figure 32). Specifically, the information identification unit 114 identifies, for example, one piece of equipment included in the equipment information 141 generated in the equipment information generation process.

[0203] Then, the information identification unit 114 refers to, for example, the type parent-child information 131a contained in the device standard information 131 stored in the information storage area 130, and identifies the type to which the device identified in step S41 belongs (step S42 in Figure 32).

[0204] Next, the information identification unit 114 refers to, for example, the equipment standard information 131 stored in the information storage area 130 and identifies the first equipment standard information 131 corresponding to the type identified in step S42 (step S43 in Figure 32).

[0205] Subsequently, the generation rule prediction unit 115, for example, uses the learning model MD stored in the information storage area 130 to identify the first operation plan rule information 132 corresponding to the equipment identified in step S41 from the operation plan rule information 132 stored in the information storage area 130 (step S44 in Figure 8).

[0206] Specifically, as shown in Figure 21, the generation rule prediction unit 115 generates input data DT0 from at least one of the following: connection point information 133 corresponding to the first equipment standard information 131 identified in step S43, equipment list information 141a corresponding to the equipment identified in step S41, connection list information 141b corresponding to the equipment identified in step S41, and equipment parent-child information 142 corresponding to the equipment identified in step S41. The generation rule prediction unit 115 then stores the generated input data DT0 in the information storage area 130. Subsequently, the generation rule prediction unit 115 inputs the input data DT0 stored in the information storage area 130 to the learning model MD. The generation rule prediction unit 115 then identifies the first operation plan rule information 132 indicated by the information output from the learning model MD in response to the input of the input data DT0.

[0207] Furthermore, the generation rule identification unit 119 identifies, for example, the second operation plan rule information 132 corresponding to the equipment identified in step S41 from the operation plan rule information 132 stored in the information storage area 130, without using the learning model MD stored in the information storage area 130 (step S45 in Figure 32).

[0208] Specifically, the generation rule identification unit 119 identifies, for example, the operation plan rule information 132 included in the first equipment standard information 131 corresponding to the equipment identified in step S41 as the second operation plan rule information 132 corresponding to the equipment identified in step S41. A specific example of the processing in step S45 will be described below.

[0209] [Specific example of the process in step S45] Figures 33 and 34 illustrate specific examples of step S45. Specifically, Figure 33 illustrates a specific example of conditional operation rule information 132 that includes the portion corresponding to equipment symbol L1a. Figure 34 illustrates another specific example of conditional operation rule information 132 that includes the portion corresponding to equipment symbol L1a. Note that in the conditional operation rule information 132 shown in Figure 34, unlike the conditional operation rule information 132 shown in Figure 33, the notation for portions other than equipment symbol L1 is omitted.

[0210] Specifically, the operation plan rule information 132 (hereinafter also referred to as operation plan rule information 132d) shown in Figures 33 and 34 includes, for example, normal operation plan rule information 132 that does not include the portion corresponding to the equipment symbol L1a, as well as one or more conditional operation plan rule information 132. Then, in step S45 of Figure 32, the generation rule identification unit 119 identifies either the normal operation plan rule information 132 or one or more conditional operation plan rule information 132 as the operation plan rule information 132 corresponding to the equipment identified in step S41, for example, without using the learning model MD.

[0211] More specifically, in step S45 of Figure 32, if the name of the equipment corresponding to the equipment identified in step S41 (for example, the name of the equipment included in the information set in the "attributes" of the equipment list information 141a) is not a transfer pump, the generation rule identification unit 119 identifies the normal operation plan rule information 132 as the operation plan rule information 132 corresponding to the equipment identified in step S41.

[0212] In other words, in this case, the generation rule identification unit 119 determines that, for example, the condition "Me.Name="Transfer Pump" is not met, and identifies the normal operation plan rule information 132 (operation plan rule information 132 that does not include the part corresponding to the equipment symbol L1a) from the operation plan rule information 132 shown in Figure 33.

[0213] On the other hand, in step S45 of Figure 32, the generation rule identification unit 119 identifies conditional operation plan rule information 132 as operation plan rule information 132 corresponding to the equipment identified in step S41, for example, if the name of the equipment corresponding to the equipment identified in step S41 is a transfer pump.

[0214] In other words, in this case, the generation rule identification unit 119 determines that, for example, the condition "Me.Name = "Transfer Pump"" is met, and identifies the conditional operation plan rule information 132 (operation plan rule information 132 including the part corresponding to the equipment symbol L1a) from the operation plan rule information 132 shown in Figure 33.

[0215] Here, in step S45 of Figure 32, the generation rule identification unit 119 identifies, for example, if the name of the equipment corresponding to the equipment identified in step S41 is a transfer pump, and the number of transfer pumps (for example, the number included in the information set in the "attributes" of the equipment list information 141a) is multiple, then it identifies the transfer pump and the conditional operation plan rule information 132 corresponding to the number of transfer pumps as the operation plan rule information 132 corresponding to the equipment identified in step S41.

[0216] In other words, the generation rule identification unit 119 determines, for example, that if there are two transfer pumps, the condition "Me.Number = "2"" is also satisfied, and identifies a conditional operation plan rule information 132 from the operation plan rule information 132 shown in Figure 34 that includes the part corresponding to equipment symbol L11a in addition to the part corresponding to equipment symbol L1a (in other words, a conditional operation plan rule information 132 that does not include the part corresponding to equipment symbol L12a).

[0217] Furthermore, the generation rule identification unit 119 determines, for example, that if the number of transfer pumps is 3, the condition "Me.Number = "3"" is also met, and identifies a conditional operation plan rule information 132 that includes, in addition to the part corresponding to equipment symbol L1a, the part corresponding to equipment symbol L12a in addition to the part corresponding to equipment symbol L1a in the operation plan rule information 132 shown in Figure 34 (in other words, a conditional operation plan rule information 132 that does not include the part corresponding to equipment symbol L11a).

[0218] Returning to Figure 32, the operation plan generation unit 116 generates operation plan information 151 corresponding to the equipment identified in step S41 from the operation plan rule information 132 identified in step S44 by converting the variables contained in the operation plan rule information 132 identified in step S44 by executing an expansion program, for example, taking at least one of the connection point information 133, equipment list information 141a, connection list information 141b, and equipment parent-child information 142 as input. The operation plan generation unit 116 also generates operation plan information 152 corresponding to the equipment identified in step S41 from the operation plan rule information 132 identified in step S45 by converting the variables contained in the operation plan rule information 132 identified in step S45 by executing an expansion program, for example, taking at least one of the connection point information 133, equipment list information 141a, connection list information 141b, and equipment parent-child information 142 as input (step S46 in Figure 32). Subsequently, the information management unit 112 stores, for example, the driving plan information 151 and the driving plan information 152 generated by the driving plan generation unit 116 in the information storage area 130.

[0219] Then, the information identification unit 114 determines, for example, whether or not all the equipment included in the equipment information 141 has been identified in step S41 (step S47 in Figure 32).

[0220] If, as a result, it is determined that not all devices have been identified (NO in step S47), the information identification unit 114 repeats, for example, steps S41 onwards.

[0221] On the other hand, if it is determined that all equipment has been identified (YES in step S47), the operation plan output unit 117 outputs the operation plan information 151 and operation plan information 152 generated in step S46, respectively (step S48 in Figure 32).

[0222] Specifically, the driving plan output unit 117 outputs, for example, the driving plan information 151 and the driving plan information 152 generated in step S46 to the operation terminal 5.

[0223] Thus, in this embodiment, the control device 1, for example, refers to the equipment standard information 131 stored in the information storage area 130 to identify the first equipment standard information 131 corresponding to the first type for each piece of equipment included in the equipment information 141 stored in the information storage area 130, and identifies the second operation plan rule information 132 included in the first equipment standard information 131 corresponding to each piece of equipment for each piece of equipment included in the equipment information 141. Then, for example, the control device 1 refers to the connection point information 133 included in the equipment standard information 131 corresponding to each piece of equipment for each piece of equipment included in the equipment information 141 to identify the connection point corresponding to the variable in the second operation plan rule information 132 corresponding to each piece of equipment. Furthermore, the control device 1 refers to the equipment information 141 stored in the information storage area 130 to identify the equipment to be connected at the connection point corresponding to each piece of equipment as the first equipment corresponding to the variable in the second operation plan rule information 132 corresponding to each piece of equipment for each piece of equipment included in the equipment information 141. Subsequently, the control device 1 generates operation plan information 152 corresponding to one or more devices by, for example, determining the value of a variable in the second operation plan rule information 132 corresponding to each device as a value indicating the first device corresponding to the variable in the second operation plan rule information 132 corresponding to each device, for each of the one or more devices included in the equipment information 141.

[0224] Furthermore, the control device 1 in this embodiment outputs, for example, for each of the one or more pieces of equipment included in the equipment information 141, operation plan information 151 and operation plan information 152 corresponding to each piece of equipment.

[0225] In other words, the control device 1 in this embodiment identifies the operation plan rule information 132 corresponding to each piece of equipment through a plurality of processes (a first generation rule identification process and a second generation rule identification process). Then, the control device 1 generates and outputs operation plan information 151 and operation plan information 152 corresponding to each piece of equipment from each of the operation plan rule information 132 identified by the plurality of processes.

[0226] As a result, the control device 1 in this embodiment can, for example, allow the operator to refer to the operation plan information 151 and operation plan information 152 corresponding to each piece of equipment. Therefore, the operator can, for example, select the more appropriate operation plan information 151 and operation plan information 152 corresponding to each piece of equipment.

[0227] Furthermore, in this embodiment, the control device 1 can further improve the judgment accuracy of the learning model MD by, for example, performing further learning on the operational plan information 151 and operational plan information 152 corresponding to each piece of equipment that the operator deems necessary. [Explanation of symbols]

[0228] 1: Control device 5: Operating terminal 101: CPU 102: Memory 103: Communication device 104: Storage medium 105: Bus 111: Information receiving unit 112: Information management department 113: Equipment information generation department 114: Information identification section 115: Driving plan generation section 116: Operation plan output unit 130: Information storage area 131: Equipment standard information 131a: Type parent-child information 131b: Detailed information on type 132: Driving plan and rule information 132a: Driving procedure rule information 132b: Driving procedure rule information 132c: Driving plan rule information 133: Connection point information 141: Equipment Information 141a: Equipment List Information 141b: Connection list information 142: Device parent / child information 151: Driving plan information 151a: Driving plan information 151b: Driving plan information 152: Driving plan information 1000: Driving plan generation system DT: Training data L1: Equipment symbol L1a: Equipment symbol L11: Equipment symbol L11a: Equipment symbol L12: Equipment symbol L12a: Equipment symbol MD: Learning Model NW: Network OB1: Sludge storage tank OB11: Sludge storage tank level gauge OB2: Transfer pump OB3: Sludge hopper OB31: Sludge hopper level meter S: Symbol

Claims

1. For each type of equipment, the system stores equipment standard information in the storage unit, which includes the generation rules for the corresponding operating procedures and connection point information indicating the attributes of the connection points between the corresponding equipment and other equipment. The system accepts input of equipment information including equipment information indicating one or more devices, connection information indicating the connection relationships between the one or more devices, and parent-child information indicating the parent-child relationships between the one or more devices. For a learning model that has been machine-learned using training data including information generated using at least one of the following: connection point information corresponding to the type of learning device, device information corresponding to the learning device, connection information corresponding to the learning device, and parent-child information corresponding to the learning device, a first generation rule corresponding to each device is identified for each of the one or more devices by inputting information generated using at least one of the following: connection point information corresponding to the type of each device, device information corresponding to each device, connection information corresponding to each device, and parent-child information corresponding to each device. Based on each of the identified first generation rules, a first operating plan corresponding to one or more of the devices is generated. A method for generating a driving plan, characterized in that the processing is performed by a computer.

2. Furthermore, before the process of receiving the input of the equipment information, the learning model is generated by performing machine learning on the training data. The method for generating a driving plan according to claim 1, characterized in that the processing is performed by a computer.

3. Furthermore, for each of the one or more devices, other training data is generated that includes information generated using at least one of the following: connection point information corresponding to the type of device, device information corresponding to each device, connection information corresponding to each device, and parent-child information corresponding to each device, and the first generation rule corresponding to each device. The machine learning of the learning model is further performed by using the other training data corresponding to each of the one or more devices mentioned above. The method for generating a driving plan according to claim 1, characterized in that the processing is performed by a computer.

4. Furthermore, by referring to the aforementioned equipment standard information, for each of the one or more equipment items, first equipment standard information corresponding to the type of equipment is identified. For each of the one or more devices mentioned above, a second generation rule included in the first device standard information corresponding to each device is identified. For each of the one or more devices, the connection point corresponding to the variable in the second generation rule corresponding to each device is identified by referring to the connection point information included in the first device standard information corresponding to each device. By referring to the aforementioned equipment information, for each of the one or more devices, the device to be connected at the connection point corresponding to each device is identified as the first device corresponding to the variable in the second generation rule corresponding to each device. For each of the one or more devices, the value of the variable in the second generation rule corresponding to each device is set to a value that indicates the first device corresponding to the variable in the second generation rule corresponding to each device, thereby generating a second operating plan corresponding to the one or more devices. For each of the one or more devices, the first operating plan and the second operating plan corresponding to each device are output. The method for generating a driving plan according to claim 3, characterized in that the processing is performed by a computer.

5. For each type of equipment, there are rules for generating operation plans corresponding to each type, and corresponding to each type. The device standard information, including connection point information that indicates the attributes of the connection point between the device and other devices, is stored in the storage unit. The system accepts input of equipment information including equipment information indicating one or more devices, connection information indicating the connection relationships between the one or more devices, and parent-child information indicating the parent-child relationships between the one or more devices. For a learning model that has been machine-learned using training data including information generated using at least one of the following: connection point information corresponding to the type of learning device, device information corresponding to the learning device, connection information corresponding to the learning device, and parent-child information corresponding to the learning device, a first generation rule corresponding to each device is identified for each of the one or more devices by inputting information generated using at least one of the following: connection point information corresponding to the type of each device, device information corresponding to each device, connection information corresponding to each device, and parent-child information corresponding to each device. Based on each of the identified first generation rules, a first operating plan corresponding to one or more of the devices is generated. A driving plan generation program characterized by having a computer perform the processing.

6. An information management unit stores equipment standard information in a storage unit, which includes, for each type of equipment, a rule for generating operation plans corresponding to each type, and connection point information indicating the attributes of connection points between each type of equipment and other equipment. An information receiving unit that receives input of equipment information including equipment information indicating one or more devices, connection information indicating the connection relationship between the one or more devices, and parent-child information indicating the parent-child relationship between the one or more devices, A machine learning model of training data including the connection point information corresponding to the type of learning device, the device information corresponding to the learning device, the connection information corresponding to the learning device, the parent-child information corresponding to the learning device, and information indicating the generation rule corresponding to the learning device, is input for each of the one or more devices, and a generation rule prediction unit identifies a first generation rule corresponding to each device by inputting the information generated using at least one of the connection point information corresponding to the type of each device, the device information corresponding to each device, the connection information corresponding to each device, and the parent-child information corresponding to each device. The system includes an operation plan generation unit that generates a first operation plan corresponding to one or more devices based on each of the specified first generation rules, A driving plan generation device characterized by the following features.

Images