Information processing method, information processing device, information processing system, and program

Abstract

The invention provides an information processing method, an information processing device, an information processing system, and a program, which make workshop operation oriented to decarbonization easier. An information processing method of an information processing device having a control unit includes: a step in which the control unit acquires a measured value of a physical quantity related to the discharge of greenhouse gas measured by a sensor in a plant used in process manufacturing; a greenhouse effect gas discharge amount acquisition unit that acquires, on the basis of the acquired measurement value, the greenhouse effect gas discharge amount accumulated during a predetermined period; a prediction unit that predicts a future transition on the basis of a previous transition with respect to the discharge amount of the greenhouse gas; and causing a display unit to display an image indicating the past transition and the predicted future transition relating to the discharge amount of greenhouse gas.

Description

[0001] Cross-references of related applications

[0002] This application claims the benefit of priority based on Japanese Patent Application No. 2023-137610 filed in Japan on August 25, 2023, the disclosure of which is hereby incorporated by reference in its entirety. Technical Field

[0003] The present invention relates to an information processing method, an information processing device, an information processing system and a program. Background Art

[0004] An information management system is known that collects and aggregates various information related to the operating status of each device constituting a plant and provides it to users such as operators and engineers. For example, Patent Document 1 describes a technology related to the management of operation and maintenance of a waste treatment plant.

[0005] Patent Document 1: Japanese Patent Application Publication No. 2003-308118

[0006] However, from the perspective of facilitating plant operations toward achieving decarbonization, there is room for improvement in current plant information management systems. Summary of the invention

[0007] The object of the present invention is to facilitate plant operation towards achieving decarbonization.

[0008] According to the present invention, it relates to an information processing method.

[0009] (1) An information processing method is an information processing method of an information processing device having a control unit, wherein:

[0010] The information processing method comprises the following steps:

[0011] The control unit acquires a measured value of a physical quantity related to the emission of greenhouse gas measured by a sensor in a workshop for process manufacturing;

[0012] Based on the acquired measurement value, acquiring the emission amount of the greenhouse gas accumulated during a predetermined period;

[0013] Regarding the emission of the greenhouse gas, predicting future trends based on past trends; and

[0014] The display unit is caused to display an image showing past changes and predicted future changes in the amount of greenhouse gas emissions.

[0015] In this way, the information processing method displays an image that not only shows the past changes related to the emission of greenhouse gases, but also shows the predicted future changes. Therefore, in the case where the emission of greenhouse gases is likely to exceed the reference value, users (such as on-site operators and system engineers, etc.) can be informed of the situation in advance and can take necessary countermeasures in advance in daily operations. For example, users can reduce waste caused by excessive operation, leakage and loss of equipment, and respond to performance degradation caused by deterioration of equipment. Therefore, according to the information processing method, even if the user is inexperienced, it is possible to make workshop operations for the realization of decarbonization easier.

[0016] (2) The information processing method according to (1) can be formed as follows:

[0017] The control unit calculates the energy consumption of the workshop for each manufacturing batch, each manufacturing line or each instrument in the workshop based on the acquired measurement value,

[0018] Based on the calculated energy consumption, the greenhouse gas emission accumulated during the predetermined period is acquired.

[0019] In this way, the information processing method calculates the energy consumption of the workshop for each manufacturing batch, each manufacturing line or each instrument in the workshop, and obtains the emission of greenhouse gases based on the energy consumption. Therefore, the information processing method can accurately calculate the emission of greenhouse gases.

[0020] (3) The information processing method according to (1) or (2) may be formed as follows:

[0021] The control unit issues a warning when the predicted future change in the amount of greenhouse gas emission is larger than a reference value.

[0022] Therefore, the user can know in advance that the future change in the emission amount of greenhouse gases is predicted to be greater than the reference value, and can take necessary measures in advance.

[0023] (4) The information processing method according to any one of (1) to (3) may be configured as follows:

[0024] The control unit causes the display unit to display an image in which past changes and predicted future changes related to the emission of the greenhouse gas are organized for each energy flow or each range category.

[0025] Therefore, the user can browse the information on greenhouse gas emissions organized in a desired format and take necessary measures.

[0026] (5) The information processing method according to any one of (1) to (4) may be configured as follows:

[0027] The control unit estimates the measured value of the physical quantity of a portion not measured by the sensor, using the measured value of the physical quantity measured by the sensor.

[0028] The emission amount of the greenhouse gas accumulated during the predetermined period is acquired based on the measurement value of the physical quantity measured by the sensor and the estimated measurement value of the physical quantity.

[0029] In this way, the information processing method estimates the measured value of the physical quantity of the part not measured by the sensor to obtain the emission of greenhouse gas. Therefore, the information processing method can provide information related to the emission of greenhouse gas even if the sensors are not fully configured or all sensors are not operating normally.

[0030] (6) The information processing method according to any one of (1) to (5) may be configured as follows:

[0031] The control unit calculates a diagnostic KPI related to the emission of the greenhouse gas of an instrument used in the workshop based on the acquired measurement value,

[0032] The display unit is further caused to display an image representing the calculated diagnosis KPI.

[0033] In this way, with regard to the information processing method, the diagnostic KPI related to the emission of greenhouse gases is calculated and displayed, so that the user can identify the cause of the generation of greenhouse gases and easily take necessary countermeasures.

[0034] (7) The information processing method according to any one of (1) to (6) may be configured as follows:

[0035] The control unit causes the display unit to display an image showing past changes and predicted future changes in the amount of greenhouse gas emissions so that energy consumption and loss can be distinguished.

[0036] In this way, the information processing method displays information related to greenhouse gas emissions in a manner that allows for distinction between energy consumption and loss, and thus it becomes easy for the user to appropriately select a necessary measure for decarbonization.

[0037] According to the present invention, there is provided an information processing device,

[0038] (8) An information processing device capable of communicating with a client device, wherein:

[0039] The information processing device includes a control unit.

[0040] The control unit acquires a measurement value of a physical quantity related to greenhouse gas emission measured by a sensor in a workshop for process manufacturing,

[0041] Based on the acquired measurement value, the emission amount of the greenhouse gas accumulated during a predetermined period is acquired;

[0042] Regarding the emission of greenhouse gases, the future trend is predicted based on the past trend.

[0043] An image showing past changes and predicted future changes in the amount of greenhouse gas emissions is transmitted to the client device via a communication unit.

[0044] In this way, the information processing device displays an image showing not only the past changes related to the emission of greenhouse gases, but also the predicted future changes. Therefore, when the emission of greenhouse gases is likely to exceed the reference value, the user can know the situation in advance and take necessary measures in advance. Therefore, according to the information processing device, it is possible to make workshop operations for the realization of decarbonization easier.

[0045] According to the present invention, there is provided an information processing system.

[0046] (9) An information processing system comprising: a client device; and an information processing device capable of communicating with the client device, wherein:

[0047] The information processing device includes a control unit.

[0048] The control unit acquires a measurement value of a physical quantity related to greenhouse gas emission measured by a sensor in a workshop for process manufacturing,

[0049] Based on the acquired measurement value, the emission amount of the greenhouse gas accumulated during a predetermined period is acquired;

[0050] Regarding the emission of greenhouse gases, the future trend is predicted based on the past trend.

[0051] An image showing past changes and predicted future changes in the amount of greenhouse gas emissions is transmitted to the client device via a communication unit.

[0052] In this way, the information processing system displays an image showing not only the past changes related to the emission of greenhouse gases, but also the predicted future changes. Therefore, when the emission of greenhouse gases is likely to exceed the reference value, the user can know the situation in advance and take necessary measures in advance. Therefore, according to the information processing system, it is possible to make workshop operations for the realization of decarbonization easier.

[0053] According to the present invention, there is provided a program,

[0054] (10) A program for controlling an information processing device having a control unit capable of communicating with a client device, wherein:

[0055] The program causes the control unit to execute the following steps:

[0056] Acquiring a measured value of a physical quantity related to greenhouse gas emissions measured by a sensor in a workshop for process manufacturing;

[0057] Based on the acquired measurement value, acquiring the emission amount of the greenhouse gas accumulated during a predetermined period;

[0058] Regarding the emission of the greenhouse gas, predicting future trends based on past trends; and

[0059] An image showing past changes and predicted future changes in the amount of greenhouse gas emissions is transmitted to the client device via a communication unit.

[0060] In this way, the information processing device that executes processing based on the program displays an image that not only shows the past changes related to the emission of greenhouse gases, but also shows the predicted future changes. Therefore, when the emission of greenhouse gases is likely to exceed the reference value, the user can know the situation in advance and take necessary measures in advance.

[0061] The program will make it easier to operate a workshop towards decarbonization.

[0062] Effects of the Invention

[0063] According to one embodiment of the present invention, it is possible to facilitate workshop operation towards decarbonization. BRIEF DESCRIPTION OF THE DRAWINGS

[0064] Figure 1 This is a diagram showing a configuration example of an information processing system according to one embodiment.

[0065] Figure 2 Yes means Figure 1 A block diagram of a structural example of the first server device.

[0066] Figure 3 Yes means Figure 1 A block diagram of a structural example of a second server device.

[0067] Figure 4 Yes means Figure 1 A block diagram of an example structure of a client device.

[0068] Figure 5 This is a flowchart showing an example of the operation of the second server device.

[0069] Figure 6 This is a flowchart showing an example of the operation of the first server device.

[0070] Figure 7 This is a flowchart showing an example of the operation of the first server device.

[0071] Figure 8 This is a diagram showing an example of a screen showing the carbon dioxide emission amount of a workshop.

[0072] Fig. 9A This is a diagram showing an example of a trend graph related to the emission of carbon dioxide.

[0073] Fig. 9B This is a diagram showing an example of a trend graph related to the emission of carbon dioxide.

[0074] Fig. 10A This is a diagram showing an example of a graph related to rise detection / fall detection.

[0075] Fig. 10B This is a diagram showing an example of a graph related to rise detection / fall detection.

[0076] Fig.11 This is a diagram showing an example of a differential alarm graph.

[0077] Fig.12 This is a diagram showing an example of a graph for performing area monitoring.

[0078] Fig.13 This is a diagram showing an example of a curve graph related to a variable polygonal line function.

[0079] Fig.14 This is a diagram showing an example of an editing screen related to graph display.

[0080] Fig.15 This is a diagram showing an example of an editing screen related to graph display.

[0081] Fig.16This is a diagram showing an example of a graph showing details of steam loss in a workshop.

[0082] Fig.17 This is a diagram showing an example of a screen that displays steam consumption and loss in association with the flow path of steam in a plant.

[0083] Fig.18 This is a diagram showing an example of a screen that displays steam consumption and loss in association with the flow path of steam in a plant. DETAILED DESCRIPTION

[0084] <Comparative Example>

[0085] As a structure involved in a comparative example, Patent Document 1 (Claim 1) records the following content, namely, "A method for operating and managing multiple workshops, wherein multiple workshops are connected to a computer in a management center to realize networking, and is characterized in that it includes the following steps: a data collection step, in which various operating data of the workshop is collected from a data storage device in each workshop to a computer in a management center by using a communication unit; a diagnosis step, in which the collected operating data is used to diagnose the status of each part in the workshop when the data is collected; a remaining life calculation step, in which the obtained diagnostic results are compared with the diagnostic results of other workshops accumulated in the computer in the management center, thereby calculating the remaining life of each part in the workshop; and an operating condition notification step, in which, based on the remaining life of each part obtained, the increase or decrease of the various operating data required to extend the remaining life is determined, and the increase or decrease is notified to the control mechanism of the workshop."

[0086] In recent years, due to climate change caused by global warming and the increase in greenhouse gases such as carbon dioxide, as well as the increased risk of depletion of fossil fuel resources, it has become important to solve the problem of decarbonization in the operation of factories and a series of business activities using factories. For example, efficient use of fossil fuel resources, reduction of carbon dioxide emissions, use of renewable energy (such as solar power generation and wind power generation), and use of emissions trading are equivalent to such decarbonization solutions.

[0087] Specifically, for example, in workshops such as manufacturing and power plants (including factories), manufacturers burn fossil fuels such as oil and coal to form heat sources. In addition, in power plants, heavy oil is burned to generate electricity and steam, and steam turbines are rotated to generate electricity. In addition, trucks and ships used to transport products manufactured by manufacturing practitioners also use fossil fuels such as oil. Fossil fuels are also used when employees move on business trips. In this way, fossil fuels are consumed not only in the operation of the workshop, but also in a series of activities related to the operation of the workshop, such as the transportation of raw materials and products and the movement of related personnel. Therefore, the managers of the workshop, on the basis of making the workshop operate safely and stably, also seek to operate the workshop in a way that reduces the emission of greenhouse gases for the realization of decarbonization.

[0088] However, for users on site, such as operators and engineers, it is sometimes unclear whether any action of each device in the workshop is related to the emission of carbon dioxide and the consumption of fossil fuels, and whether any workshop operation policy is conducive to decarbonization. Therefore, it is sometimes difficult for users on site to manage the workshop in a way that each device performs actions appropriately for the realization of decarbonization based only on the information provided by the information management system involved in the comparison. Thus, from the perspective of making it easier to operate the workshop for the realization of decarbonization, there is room for improvement in the information management system of the workshop involved in the comparison.

[0089] The object of the present invention is to facilitate plant operation towards achieving decarbonization.

[0090] <Implementation Method>

[0091] Hereinafter, an embodiment of the present invention will be described with reference to the accompanying drawings. In each of the drawings, the same reference numerals are used for parts having the same structure or function. In the description of this embodiment, the repeated description of the same parts may be appropriately omitted or simplified.

[0092] (Information Processing System)

[0093] Figure 1 1 is a diagram showing a configuration example of an information processing system 1 according to an embodiment. In this embodiment, an example of using the information processing system 1 in a workshop for process manufacturing using fluid as a raw material is described. The workshop for such process manufacturing may include, for example, a chemical workshop and an oil refinery. The information processing system 1 may also be used in workshops other than such process manufacturing.

[0094] like Figure 1As shown, the information processing system 1 has a first server device 10, a second server device 20, a sensor 30 (30a, 30b), a gateway 40, and a client device 50. The sensor 30 (30a, 30b) is connected to the second server device 20 in a manner that can communicate with each other. The first server device 10, the second server device 20, and the gateway 40 are connected via a network 61 in a manner that can communicate with each other. The gateway 40 and the client device 50 are connected via a network 62 in a manner that can communicate with each other. The networks 61 and 62 can be, for example, an intranet, a dedicated network, the Internet, a mobile line, or a combination thereof. The first server device 10 and the client device 50 can be formed to be able to communicate with each other via the same network (for example, the network 61).

[0095] The sensor 30 (30a, 30b) is a device that obtains the measured value of a physical quantity related to the emission of greenhouse gases (such as carbon dioxide) in the workshop, and performs at least one of the operations of the workshop. The sensor 30 (30a, 30b) can be, for example, a temperature sensor, a flow meter, or a transmitter such as a sensor 30a, and an actuator 30b such as a valve instrument, a fan, or a motor. Below, the sensors 30a and 30b are sometimes collectively referred to as "sensors 30". The sensor 30 sends the measured value to the second server device 20, and controls the action based on the control signal received from the second server device 20. Figure 1 In the example of FIG. 1 , the information processing system 1 includes two sensors 30 a and 30 b , but the number of sensors 30 is arbitrary.

[0096] The second server device 20 is connected to the sensor 30 and functions as an interface between the sensor 30 and the first server device 10. That is, the second server device 20 collects the measured values ​​of the physical quantity from the sensor 30 at a constant period (for example, every 1 second). The second server device 20 stores the collected measured data in the storage unit 22 (see Figure 3 ). The second server device 20 sends the measurement value of the sensor 30 to the first server device 10 at a constant period (for example, every 1 second). The second server device 20 is connected to the network 61 and can communicate with the first server device 10 via the network 61. Figure 1 In the example of , the information processing system 1 includes one second server device 20, but the number of second server devices 20 is arbitrary. The number of sensors 30 connected to each second server device 20 is arbitrary.

[0097] The first server device 10 as the information processing device according to the present embodiment calculates information related to the emission of greenhouse gases related to the operation of the plant based on the measured value of the physical quantity received from the second server device 20, organizes the information into information that is easy for the user on site to understand, and provides it to the client device 50. The first server device 10 is connected to the network 61 and can communicate with the second server device 20 via the network 61. The first server device 10 can communicate with the client device 50 via the gateway 40 and the network 62. The information processing system 1 has one first server device 10, but the number of first server devices 10 is arbitrary.

[0098] The gateway 40 performs necessary processing such as protocol conversion and access control so that devices connected to the network 61 and devices connected to the network 62 can communicate with each other.

[0099] The client device 50 is a device operated by users such as operators and engineers at the site. The client device 50 receives information on the emission amount of greenhouse gases related to the operation of the plant from the first server device 10 and displays the information.

[0100] Regarding the above structure, the first server device 10 obtains the measurement value related to the emission of greenhouse gases in the workshop measured by the sensor 30 in the workshop. The first server device 10 calculates the energy consumption of the workshop for each manufacturing batch, each manufacturing production line or each instrument in the workshop based on the obtained measurement value. The first server device 10 obtains the greenhouse gas emission accumulated in a predetermined period based on the calculated energy consumption. The first server device 10 predicts the future change of greenhouse gas emission based on the past change of greenhouse gas emission. The first server device 10 sends an image showing the energy consumption, the past change of greenhouse gas emission and the predicted future change to the client device 50 and displays it. When the predicted future greenhouse gas emission exceeds the reference value, the first server device 10 notifies the client device 50 of a warning (alarm).

[0101] In this way, the first server device 10 not only transmits the past changes in the energy consumption and greenhouse gas emissions of the workshop to the client device 50, but also transmits an image showing the predicted future changes to the client device 50. Therefore, when the greenhouse gas emissions are likely to exceed the reference value, the user can be informed of the situation in advance and take necessary countermeasures.

[0102] In addition, when displaying the energy consumption of the workshop, the first server device 10 distinguishes between energy consumed by use and energy consumed by loss (waste energy). Therefore, the user can easily and accurately understand the energy usage status of the workshop and take necessary measures for more efficient energy utilization.

[0103] In addition, the first server device 10 displays not only information such as the change in the amount of greenhouse gas emissions, but also displays diagnostic KPIs (Key Performance Indicators) related to greenhouse gas emissions. Diagnostic KPIs are information used to make it easier to identify the cause of a device failure. Users can easily identify the cause of a device failure by referring to the diagnostic KPIs and take measures such as necessary component replacement and repair.

[0104] In addition, the first server device 10 not only provides the energy flow of the workshop to the client device 50, but also organizes information related to the emission of greenhouse gases for each product supply chain and provides it to the client device 50. At this time, the first server device 10 also appropriately displays the trend of carbon dioxide emissions based on Scope 1-2-3 for the emission upper limit value, and displays the amount corresponding to the carbon price and energy price. Therefore, the user can not only grasp the emission of greenhouse gases in the workshop, but also grasp the emission of greenhouse gases in a series of activities related to the operation of the workshop, such as the transportation of raw materials and products, and the movement of relevant personnel, and can take the necessary countermeasures. In order to achieve this processing, the first server device 10 can not only obtain the measured values ​​measured in a specific workshop, but also obtain information related to the emission of carbon dioxide in each process of the front and back sections of the workshop. Specifically, the first server device 10 can calculate the carbon dioxide emissions in real time and comprehensively based on the accumulation of data related to various business formats, products and supply chain networks collected from all over the world, regardless of products, business formats and regions. Furthermore, the first server device 10 can visualize the carbon dioxide emissions from various perspectives such as product units or factory units, and can also predict and visualize the future carbon dioxide emissions, thereby enabling users to study and implement measures for decarbonization from various perspectives.

[0105] (First server device)

[0106] Figure 2 Yes means Figure 1The first server device 10 is a block diagram of a configuration example of the first server device 10. The first server device 10 is one or a plurality of computer devices that can communicate with each other. The first server device 10 is, for example, any general-purpose electronic device such as a WS (Work Station) or a PC (Personal Computer), but may also be other dedicated electronic devices. Figure 2 As shown, the first server device 10 includes a control unit 11 , a storage unit 12 , and a communication unit 13 .

[0107] The control unit 11 includes one or more processors. In one embodiment, the "processor" is a general-purpose processor or a dedicated processor that performs specific processing, but is not limited to this. The control unit 11 is connected to each component constituting the first server device 10 in a communicable manner to control the overall operation of the first server device 10.

[0108] The storage unit 12 includes, for example, any storage module such as a HDD (Hard Disk Drive), an SSD (Solid State Drive), a ROM (Read-Only Memory), and a RAM (Random Access Memory). The storage unit 12 can function as, for example, a main storage device, an auxiliary storage device, or a cache. The storage unit 12 stores any information used for the operation of the first server device 10. For example, the storage unit 12 can store system programs, application programs, and various information received by the communication unit 13. The storage unit 12 is not limited to being built into the first server device 10, and can also be an external database or an external storage module.

[0109] The communication unit 13 includes any communication module that can communicate with other devices such as scanners through any communication technology. The communication unit 13 may also include a communication control module for controlling communication with other devices and a storage module for storing communication data such as identification information required for communication with other devices.

[0110] The functions of the first server device 10 can be realized by executing the computer program (program) involved in the present embodiment by the processor included in the control unit 11. That is, the functions of the first server device 10 can be realized by software. The computer program enables the computer to realize the functions corresponding to the processing of each step by causing the computer to execute the processing of the steps included in the action of the first server device 10. That is, the computer program is a program for causing the computer to function as the first server device 10 involved in the present embodiment. The computer program can be recorded in a recording medium that can be read by a computer. The program contains information for processing by an electronic computer and is based on the program. For example, data that is not a direct instruction to the computer but has the property of specifying the processing of the computer is equivalent to "data based on the program."

[0111] A part or all of the functions of the first server device 10 may be realized by a dedicated circuit included in the control unit 11. That is, a part or all of the functions of the first server device 10 may be realized by hardware. In addition, the first server device 10 may be realized by a single computer or by the coordinated operation of a plurality of computers.

[0112] (Second Server Device)

[0113] Figure 3 Yes means Figure 1 The second server device 20 is a block diagram of a configuration example of the second server device 20. The second server device 20 is one or a plurality of computer devices that can communicate with each other. The second server device 20 is, for example, any general-purpose electronic device such as a WS or a PC, but may also be other dedicated electronic devices. Figure 2 As shown, the second server device 20 includes a control unit 21, a storage unit 22, and a communication unit 23. The control unit 21, the storage unit 22, and the communication unit 23 of the second server device 20 are connected to the reference Figure 2 The control unit 11, storage unit 12 and communication unit 13 of the first server device 10 described are the same, so detailed description is omitted. In this embodiment, an example in which the first server device 10 and the second server device 20 are configured as different devices is described, but the first server device 10 and the second server device 20 can also be configured as the same device.

[0114] Similar to the first server device 10, the functions of the second server device 20 may also be realized by software. In addition, a part or all of the functions of the second server device 20 may be realized by a dedicated circuit included in the control unit 21. That is, a part or all of the functions of the second server device 20 may be realized by hardware. In addition, the second server device 20 may be realized by a single computer or by the coordinated operation of a plurality of computers.

[0115] (Client Device)

[0116] Figure 4 Yes means Figure 1 The client device 50 is a block diagram of a structural example of a client device 50. The client device 50 is one or more computer devices that can communicate with each other. The client device 50 is, for example, any general electronic device such as a PC, a tablet terminal, or a smart phone, but may also be other dedicated electronic devices. Figure 4 As shown, the client device 50 includes a control unit 51, a storage unit 52, a communication unit 53, an input unit 54, and an output unit 55. The control unit 51, the storage unit 52, and the communication unit 53 of the client device 50 are similar to the reference Figure 2 The control unit 11 , the storage unit 12 , and the communication unit 13 of the first server device 10 described above are the same, and thus detailed descriptions thereof are omitted.

[0117] The input unit 54 includes one or more input interfaces for accepting user input operations and obtaining input information based on the user operations. For example, the input unit 54 is a physical key, a capacitive key, a pointing device, a touch screen integrated with the display of the output unit 55, or a microphone for accepting voice input, but is not limited thereto.

[0118] The output unit 55 includes one or more output interfaces for outputting information to the user and notifying the user. For example, the output unit 55 is a display that outputs information as an image, or a speaker that outputs information in the form of voice, but is not limited thereto. Such a display may be, for example, a liquid crystal panel display or an organic EL (Electro Luminescence) display. In addition, at least one of the input unit 54 and the output unit 55 may be integrally formed with the client device 50, or may be separately provided.

[0119] In the present embodiment, an example in which the first server device 10 and the client device 50 are configured as different devices has been described. However, the first server device 10 and the client device 50 may be configured as the same device.

[0120] Similar to the first server device 10, the functions of the client device 50 may be implemented by software. In addition, part or all of the functions of the client device 50 may be implemented by a dedicated circuit included in the control unit 51. That is, part or all of the functions of the client device 50 may be implemented by hardware. In addition, the client device 50 may be implemented by a single computer or by the coordinated action of a plurality of computers.

[0121] (Action Example)

[0122] Figure 5 2 is a flowchart showing an example of the operation of the second server device 20. Figure 5The operation of the second server device 20 described above may correspond to one of the information processing methods of the second server device 20 . Figure 5 The actions of each step can be executed based on the control of the control unit 21 of the second server device 20. The second server device 20 can repeatedly execute the steps at any cycle (for example, every 1 second, every 1 minute, or every 1 hour). Figure 5 The second server device 20 executes a series of processes in a cycle corresponding to the operating status of the factory equipment, so that the user can easily notice waste such as over-operation, omission and loss. When a plurality of second server devices 20 are provided in the information processing system 1, the second server devices 20 can execute Figure 5 Flowchart of the process.

[0123] exist Figure 5 In step S1, the control unit 21 obtains the measured value of the physical quantity from each sensor 30 connected to the second server device 20. Specifically, the control unit 21 can receive and obtain the measured value of the physical quantity from each sensor 30. The control unit 21 can obtain the measured value of the physical quantity not only from the sensor 30 directly connected to the second server device 20, but also from a wired or wireless communication unit and a sensor 30 connected via an arbitrary network.

[0124] In step S2, the control unit 21 transmits the measured value of the physical quantity received in step S1 to the first server device 10. Then, the control unit 21 ends Figure 5 Flowchart of the process.

[0125] also, Figure 5 The example in which the timing at which the second server device 20 acquires the measured value of the physical quantity from the sensor 30 is synchronized with the timing at which the second server device 20 transmits the measured value of the physical quantity to the first server device 10 is shown, but they may not be synchronized. For example, the second server device 20 may transmit the measured value of the physical quantity to the first server device 10 in response to receiving a request from the first server device 10.

[0126] Figure 6 and Figure 7 2 is a flowchart showing an example of the operation of the first server device 10. Figure 6 and Figure 7 The operation of the first server device 10 described above may correspond to one of the information processing methods of the first server device 10 . Figure 6 and Figure 7 The actions of each step can be executed based on the control of the control unit 11 of the first server device 10.

[0127] Figure 6The first server device 10 calculates the energy consumption and greenhouse gas emission based on the measured value of the physical quantity. The first server device 10 can repeatedly execute the calculation at any period (for example, every minute, every hour, every day, every month, or every year). Figure 6 A series of processing.

[0128] exist Figure 6 In step S11, the control unit 11 receives the measured value of the physical quantity from the second server device 20. Thus, the control unit 11 acquires the measured value of each sensor 30.

[0129] In step S12, the control unit 11 calculates the energy consumption for each manufacturing batch, each manufacturing production line, or each instrument based on the measured value of the physical quantity obtained in step S12. Specifically, the control unit 11 converts the measured value of the physical quantity into the energy consumption using a predetermined conversion formula according to the type of the physical quantity. The control unit 11 can calculate the energy consumption separately for the amount consumed by the operation of the instruments that actually constitute the workshop and the amount lost (loss) due to exhaust gas, etc.

[0130] In step S13, the control unit 11 accumulates the energy consumption calculated in step S12. Specifically, the control unit 11 calculates the accumulated value of the energy consumption for each first period predetermined in minutes, hours, days, weeks, months or years. As described above, the control unit 11 repeatedly executes the operation at a constant cycle. Figure 6 The control unit 11 can save the energy consumption and add the energy consumption calculated in step S12 to the cumulative value to update the cumulative value. The control unit 11 can enter step S14 when the cumulative value reaches the cumulative value of the first period representing the energy consumption through the update of the cumulative value, and then initialize the cumulative value of the energy consumption to a value of 0. Thus, the control unit 11 can calculate the cumulative value of the energy consumption in each first period. The control unit 11 can perform the processing after step S14 in each first period. Specifically, the control unit 11 can enter step S14 only when the cumulative value reaches the cumulative value of the first period representing the energy consumption through the processing of step S13, and terminate the loop if this is not the case. Figure 6 Flowchart of the process.

[0131] In step S14, the control unit 11 converts the integrated value of energy consumption calculated for each predetermined period in step S13 into greenhouse gas emissions. Specifically, the control unit 11 converts the integrated value of energy consumption into greenhouse gas emissions using a predetermined conversion formula.

[0132] In step S15, the control unit 11 totals the emission of greenhouse gas in a predetermined period. Specifically, the control unit 11 totals the emission of greenhouse gas acquired in step S14 in each second period predetermined in a day, week, month or year. The second period is a period longer than the first period or the same period. In the same way as calculating the cumulative value of energy consumption in each first period, the control unit 11 can save the cumulative value of greenhouse gas emission, add the greenhouse gas emission acquired in step S14 to the cumulative value, and update the cumulative value. The control unit 11 can enter step S16 when the cumulative value reaches the cumulative value of the second period in which the cumulative value represents the emission of greenhouse gas through the update of the cumulative value, and then initialize the cumulative value of greenhouse gas emission to a value of 0. Thus, the control unit 11 can calculate the cumulative value of greenhouse gas emission in each second period. The control unit 11 can perform the processing of step S16 in each second period. Specifically, the control unit 11 may proceed to step S16 only when the integrated value reaches the integrated value of the second period indicating the emission amount of greenhouse gas through the processing of step S15, and terminate the loop if this is not the case. Figure 6 Flowchart of the process.

[0133] In step S16, the control unit 11 stores the greenhouse gas emissions calculated in step S15 in the storage unit 12. When the process of step S16 is completed, the control unit 11 ends. Figure 6 Flowchart of the process.

[0134] Figure 7 The first server device 10 transmits information related to the emission of greenhouse gases to the client device 50 and displays the information. The first server device 10 can perform Figure 7 In addition, the first server device 10 can repeatedly execute the process at any period (for example, every minute, every hour, every day, every month, or every year) even after the client device 50 displays the screen, and update the information at any time.

[0135] First, through Figure 7 The processing is described with reference to an outline of a screen displayed on the client device 50. Figure 8 1 is a diagram showing an example of a screen 100 showing the carbon dioxide emission amount of a plant. The screen 100 shows the carbon dioxide (CO 2 ) emission amount based on steam of a plant that is a management target of the information processing system 1 .

[0136] exist Figure 8In the figure, the patterns 101 to 112 of "F" indicate the installation positions of sensors 30 (such as flow sensors, temperature sensors, and pressure sensors) for measuring physical quantities related to steam that can be converted into carbon dioxide emissions. The arrows 121 to 132 indicate the flow paths of steam. Next, the case where the sensors 30 represented by the patterns 101 to 112 all measure the flow rate of steam is described. Figure 8 In the example, the location of the sensor 30 with pattern 101 indicates the most upstream position of the steam flow path. The flow path extending downstream from the position of pattern 101 is branched into three flow paths indicated by marks 122 to 124. The flow path indicated by mark 123 branches into five flow paths indicated by marks 125 to 129. The flow path indicated by mark 124 branches into three flow paths indicated by marks 130 to 132. Figure 8 In the diagram, reference numerals 1011 to 1041 represent energy consumption obtained by converting the measured values ​​of the physical quantities measured by the sensors 30 of the patterns 101 to 104. In addition, the energy consumption is measured at a plurality of locations on the energy flow. When it is desired to correct the measurement error of the sensor 30, the first server device 10 may use data reconstruction calculation.

[0137] "A-101", "A-201", "A-202", ..., "A-303" respectively indicate objects (equipment) to which steam is supplied via the flow paths indicated by labels 121 to 132. Label 141 indicates the energy consumption of each object. Label 142 indicates the amount of energy wasted (loss) in each object. Label 143 indicates a diagnostic KPI showing important information related to the energy consumption and loss of each object. The diagnostic KPI is used to determine the cause of energy consumption and loss. The details of the information displayed in labels 141 to 143 are described later.

[0138] exist Figure 8 In the example, “measurement”, “estimation”, and “estimation + working state” shown near patterns 101 to 112 represent three states of the sensor 30. “Measurement” means that the physical quantity is actually measured by the sensor 30. “Estimation” means that the physical quantity is not actually measured by the sensor 30, but the measured values ​​of the surrounding sensors 30 are distributed with the proportional distribution values ​​pre-set for each branch of the flow path to estimate the physical quantity. The proportional distribution value can be expressed by a ratio or proportion, for example. “Estimation + working state” means that the physical quantity is actually measured by the sensor 30 under certain conditions, and in other cases, the physical quantity is estimated based on the measured values ​​of the surrounding sensors 30.

[0139] For example, the five flow paths indicated by the marks 125 to 129 branch off the flow path indicated by the mark 123, so the total value of the flow rate of the steam flowing in the five flow paths is consistent with the measured value of the flow rate of the sensor 30 based on the pattern 103. That is, if the flow rate of the sensor 30 indicated by the patterns 101, 102, ... is set to Q 101 , Q 102 , ..., then Q 103 =Q 105 +Q 106 +Q 107 +Q 108 +Q 109 Here, the flow rate Q 103 , Q 105 The measured value I 103 ,I 105 The sensor 30 represented by the patterns 103 and 105 performs the measurement. Therefore, when the sensor 30 represented by the patterns 107 and 109 does not perform the measurement, the control unit 11 performs the measurement at a predetermined ratio. 103 -I 105 ) to allocate and obtain Q 106 , Q 107 , Q 108 , Q 109 In addition, it is assumed that the sensor 30 represented by the pattern 107 performs measurement and obtains the measurement value I 107 , the sensor 30 represented by the pattern 109 does not perform measurement. In this case, the control unit 11 performs measurement at a predetermined ratio (I 103 -I 105 -I 107 ) to allocate and obtain Q 106 , Q 108 , Q 109 In addition, it is assumed that the sensor 30 represented by the pattern 109 performs measurement and obtains the measurement value I 109 , the sensor 30 represented by the pattern 107 does not perform measurement. In this case, the control unit 11 performs measurement at a predetermined ratio (I 103 -I 105 -I 109 ) to allocate and obtain Q 106 , Q 107 , Q 108 In addition, the sensor 30 represented by the patterns 107 and 109 performs measurement and obtains the measured value I 107 ,I 109 In the case of 103 -I 105 -I 107 -I 109 ) to allocate and obtain Q106 , Q 108 The estimated value of .

[0140] In this way, the control unit 11 uses the measured value of the sensor 30 to estimate the measured value of the physical quantity of the part where the measurement based on the sensor 30 is not performed. In addition, the measured value of the physical quantity of the flow path that is not measured can be estimated by a method other than the above method according to the type of physical quantity of the measured object. For example, the control unit 11 can estimate the measured value of the physical quantity by correction based on data reconstruction calculation, material balance (material balance) calculation, or heat balance (heat balance) calculation. Regarding the object that is not measured based on the sensor 30, in Figure 6 In step S12, the control unit 11 can calculate the energy consumption through such estimation.

[0141] Back to Figure 7 In step S21, the control unit 11 predicts the future change based on the past change related to the emission of greenhouse gases. The prediction of the future change related to the emission of greenhouse gases can be performed based on any method. For example, the control unit 11 can perform regression analysis on the past change related to the emission of greenhouse gases and predict the future change based on the regression curve.

[0142] In step S22, the control unit 11 calculates the diagnostic KPI associated with the emission of greenhouse gases. For example, pump performance, heat exchanger comprehensive thermal conductivity, heating furnace load, distillation tower reflux ratio, and reboiler load can be associated with the emission of greenhouse gases. Therefore, a sensor 30 for measuring such physical quantities can be provided, and the control unit 11 calculates the diagnostic KPI based on the measured value. The user can use such diagnostic KPI to determine the cause of excessive carbon dioxide emission.

[0143] In step S23, the control unit 11 can cause the client device 50 to display the past and future changes related to the greenhouse gas emissions obtained in step S21 and the diagnostic KPI obtained in step S22. Specifically, the control unit 11 generates an image representing this information and sends it to the client device 50, which is displayed on the display unit of the output unit 55 of the client device 50.

[0144] In step S24, the control unit 11 issues a warning for the item exceeding the reference value. The control unit 11 may issue such a warning by highlighting an image or notifying with voice.

[0145] Fig. 9A and Fig. 9B This is a diagram showing an example of a trend graph related to the emission of carbon dioxide. Fig. 9A and Fig. 9B An example of the past changes and the predicted values ​​of the future changes related to the emission of greenhouse gases is shown. Fig. 9B This shows an example in which an image is highlighted when it is predicted that the emission of greenhouse gases exceeds a reference value.

[0146] exist Fig. 9A In the image 151, the horizontal axis represents time and the vertical axis represents the emission of carbon dioxide. The emission on the vertical axis is displayed, for example, as a cumulative value of emitted carbon dioxide, but it can also be displayed using energy consumption or an amount corresponding to a carbon price or an energy price, etc., according to the user's instructions. Graph 152 shows the past changes related to the emission of carbon dioxide from the start of measurement to the current time t1. Graph 153 shows the change in future emissions estimated based on the past changes related to the emission of carbon dioxide. Graph 154 shows the planned value of carbon dioxide emissions (golden line), and is the change in carbon dioxide emissions that serves as a benchmark. Mark 155 shows information related to each element of graph 152.

[0147] exist Fig. 9A In FIG. 1 , the graph 153 indicates that the emission of carbon dioxide is expected to reach the reference value A at a stage of time t2 earlier than the reference graph 154 . Therefore, the control unit 11 issues a warning. Fig. 9B The image 157 is shown to notify a warning by highlighting the image. Specifically, the image 157 adds a display frame 158 and a pattern 159 to the image 151 to notify a warning. The method of notifying a warning is not limited to Fig. 9B The method is shown by example.

[0148] The control unit 11 may display the same information as that for each sensor 30 (for example, the indicators 1011 to 1041) or each object (the indicators 141 and 142). Fig. 9A and Fig. 9B This is an example of a trend chart showing the amount of carbon dioxide emitted. Figure 8 In the figure, "Consumption" (labeled 141) indicates the amount of carbon dioxide emitted corresponding to the energy consumed. "Loss" (labeled 142) indicates the amount of carbon dioxide emitted corresponding to the energy wasted in the workshop. "Loss" is generated, for example, when gas or steam is forcibly discharged from the equipment and piping in the workshop for some reason. Figure 6 In the processing following step S12, the measured value of the physical quantity measured by the sensor 30 is converted into energy or carbon dioxide emission using a preset conversion formula and conversion factor, thereby performing calculation.

[0149] In addition, Figure 8In the example, the control unit 11 displays a trend graph related to the emission of carbon dioxide for each sensor 30 and each object, but the control unit 11 can also display a trend graph summed up based on different criteria. For example, the control unit 11 can sum up the emission of carbon dioxide relative to the emission upper limit of the product batch for each type of energy such as electricity, steam, and fuel, and display a trend graph. Alternatively, as described later, the control unit 11 can display the trend of the emission of carbon dioxide in Scope 1-2-3 relative to the emission upper limit for each product supply chain.

[0150] like Figure 8 As shown, in this embodiment, the control unit 11 displays "consumption" and "loss" separately. Therefore, the user can select appropriate measures according to the energy consumption of the workshop. For example, when the proportion of "loss" is large, the user can take measures to reduce "loss" by installing a steam trap, etc.

[0151] Next, refer to Figures 10A to 13 An example of a diagnostic KPI is described. Fig. 10A and Fig. 10B This is a diagram showing an example of a graph related to rise detection / fall detection. Fig. 10A and Fig. 10B This shows an example of notifying a warning when the measured value of the monitored object is less than the lower limit or greater than the upper limit. The graph related to rise detection / fall detection is suitable for detecting phenomena related to the decline in performance (such as safety, availability, maintainability, and efficiency) associated with the deterioration of equipment in the long-term use of workshop equipment.

[0152] For example, regarding a heat exchanger, as the heat exchanger is used for several months, the tubes gradually become dirty. As the dirt on the tubes develops, the trend of energy consumption gradually worsens. Therefore, a sensor 30 for the steam temperature, the temperature of the raw material, and the flow rate can be provided, and the control unit 11 can calculate the dirt on the heat exchanger tubes based on the measured values ​​of the above sensors 30. By confirming the calculated dirt, the user can understand that the cause of the increase in the emission of greenhouse gases is the dirt on the tubes. When the dirt is significant, the user can take measures to clean or replace the parts.

[0153] Alternatively, the control unit 11 can monitor the degradation of the distillation tower. The distillation tower is a device that heats the raw material and diverts it. The control unit 11 can obtain and display the diversion ratio, that is, the trend of the diversion ratio of the upper and lower flow rates, with respect to the distillation tower using the sensor 30. The user can understand that the increase in the emission of greenhouse gases is caused by the degradation of the distillation tower by confirming the calculated diversion ratio. The on-site operator can refer to the display of the distillation tower diversion ratio and heat it when the ratio is poor. In addition, when the capacity of the distillation tower indicated by the diversion ratio deteriorates significantly, the operator can replace the necessary parts, etc.

[0154] exist Fig. 10A In the image 161, the horizontal axis represents time and the vertical axis represents the split ratio of the distillation column. The graph 162 represents the temporal change of the split ratio of the split flow, etc. The mark 163 represents information related to each element of the graph 162. "B" represents the upper limit value of the split ratio, and "C" represents the lower limit value of the split ratio.

[0155] exist Fig. 10A In FIG. 1 , the graph 162 shows that at time t3 the distillation tower split ratio reaches the upper limit value B. Therefore, the control unit 11 issues a warning. Fig. 10B The image 165 is shown to notify a warning by highlighting the image. Specifically, the image 165 adds a display frame 166 and a pattern 167 to the image 161 to notify a warning. The method of notifying a warning is not limited to Fig. 10B By notifying such a warning, the user can be informed of the deterioration of the performance of the distillation column and can take necessary measures such as replacing parts.

[0156] Fig.11 : is a diagram showing an example of a differential alarm graph. The differential alarm graph is used to compare two measured values. For example, the differential alarm graph can be used to compare the performance of the design aspects of the equipment constituting the workshop and the measured values ​​related to the actual performance of the equipment performing the action. Specifically, if a constant amount of voltage is applied to the pump, it is known that there is a constant relationship between the discharge pressure and the current value. Therefore, the current value applied to the pump and the discharge pressure are measured using the sensor 30. When the measured pressure is lower than the value corresponding to the current value, it can be known that the pump is deteriorated.

[0157] exist Fig.11In the image 171, the horizontal axis represents the current value and the vertical axis represents the discharge pressure based on the pump. The curve graph 172 represents the relationship between the current value of the monitored pump and the measured value of the actual discharge pressure. The curve graph 173 represents the relationship between the current value of the monitored pump and the value of the designed discharge pressure. The mark 174 represents the information related to each element of the curve graph 172. By checking the curve graphs 172 and 173, the user can understand that the reason for the reduction in the utilization efficiency of greenhouse gases is the reduction in the performance of the pump. When the performance of the pump is significantly reduced, the user can take measures to clean or replace the parts.

[0158] exist Fig.11 In the example of FIG. 1 , between the curves 172 and 173, at the current value I1, the pressure has a difference of value D. When this difference is greater than a predetermined threshold, the control unit 11 can notify the user of a warning. By notifying such a warning, the user can be informed of the deterioration of the performance of the pump and can take necessary measures such as replacing parts. As a result, the user can take appropriate measures for the reduction of greenhouse gases.

[0159] Fig.12 : is a diagram showing an example of a graph for performing area monitoring. The graph for area monitoring is used to confirm that the relationship between two parameters related to the object exists in a constant area occupied in a two-dimensional plane. For example, with respect to a control valve that performs an action normally, it is known that the indication signal (indication value) X for the valve and the actual measurement value Y of the amount of action of the valve that moves in accordance with the signal take values ​​within a constant area on the XY plane. However, if the valve deteriorates, the indication signal X and the actual measurement value Y take values ​​that deviate from the constant area. As a result, sometimes the valve of the fuel flow is not fully opened when it should be opened, or is not fully closed when it should be closed. Therefore, the control unit 11 displays the degradation of the valve as a graph for area monitoring, thereby being able to notify the user of abnormalities based on the degradation of the valve in an easily understandable manner.

[0160] exist Fig.12 In the image 181, the horizontal axis represents the indication value for the valve, and the vertical axis represents the actual measured value of the actual movement amount of the valve. The curve graph 182 represents a constant area for determining the normal movement of the valve. The plotted points 183 and 184 represent the measured values ​​of the indication value of the valve to be measured and the actual measured value. The user can confirm whether the valve is performing the operation normally by confirming the plotted points 183 and 184 and the constant area represented by the curve graph 182. In the case where the plotted points 183 and 184 are out of the constant area, the user can take necessary measures such as replacing the valve. In addition, in the case where the plotted points are out of the constant area, the control unit 11 can notify the user of a warning and promote the replacement of the valve.

[0161] Fig.131 is a diagram showing an example of a graph 192 related to a variable broken line function. A variable broken line graph is used to compare two parameters. For example, a variable broken line graph can be used to compare the performance X of the design of the equipment constituting the workshop and the measured value Y related to the actual performance of the equipment performing the action. The control unit 11, for example, sets the measured value of the current value applied to the pump as the value of the X-axis and the measured value of the discharge pressure as the value of the Y-axis to depict, so that the user can understand the relationship between the two in detail. As a result, the user can take appropriate measures for the reduction of greenhouse gases.

[0162] Reference Figures 10A to 13 Although the example of the diagnosis KPI has been described, the control unit 11 may provide information other than the above information to the client device 50 as the diagnosis KPI.

[0163] In step S25, the control unit 11 causes the client device 50 to display the greenhouse gas emissions organized in a specified format. Specifically, the control unit 11 can, for example, organize the carbon dioxide emissions for each energy flow and display the trend. Alternatively, the control unit 11 can, for example, organize the carbon dioxide emissions for each type of energy in the factory (such as electricity, steam, fuel, etc.), each manufacturing batch, each manufacturing process, each factory equipment, or each Scope1-2-3 category (range category) and display the trend. The control unit 11 can organize the greenhouse gas emissions in the form desired by the user according to the user's instructions. If the processing of step S25 is completed, the control unit 11 ends. Figure 7 Flowchart of the process.

[0164] As described above, the first server device 10 obtains the measured value of the physical quantity related to the emission of greenhouse gases measured by the sensor 30 in the workshop for process manufacturing. The first server device 10 obtains the greenhouse gas emission accumulated in a predetermined period based on the obtained measured value. The first server device 10 predicts the future change of the greenhouse gas emission based on the past change. The first server device 10 uses the communication unit 13 to send an image related to the greenhouse gas emission, which shows the past change and the predicted future change, to the client device 50. Therefore, when the greenhouse gas emission may exceed the reference value, the user can know the situation in advance and can take the necessary countermeasures in advance. Therefore, according to the first server device 10, workshop operations for the realization of decarbonization can be carried out more easily.

[0165] In addition, the first server device 10 can calculate the carbon dioxide emissions in real time and comprehensively based on the accumulation of data related to various industries, products, and supply chain networks collected from all over the world, regardless of products, industries, regions, etc. Furthermore, the first server device 10 can make the carbon dioxide emissions visible from various perspectives such as product units or factory units, and predict and visualize the future carbon dioxide emissions. As a result, users can study and implement measures for decarbonization based on various viewpoints. In addition, the first server device 10 can calculate the carbon dioxide emissions based on various viewpoints such as product units and factory units. Figure 8 Which of the graphs 141 to 143 in the screen 100 is displayed is selected by the user via the client device 50. Figures 9A to 13 Enlarged view of the graph shown in the example.

[0166] Furthermore, the first server device 10 may provide the client device 50 with an editing screen for information such as the carbon dioxide emission amount calculated based on the measurement value of the sensor 30 and the diagnostic KPI, and allow the user to edit the information. Fig.14 and Fig.15 This is a diagram showing an example of an editing screen related to graph display.

[0167] Fig.14 An example of a screen 201 for setting a graph for performing area monitoring is shown. In screen 201, input field 202 is an area for setting the initial and final periods of data for calculating the diagnostic KPI. Input field 203 is an area for setting the type, lower limit value, and upper limit value of the parameter set as the X-axis and Y-axis. Input field 204 is an area for setting an alarm (warning). Input field 205 is an area for setting the cycle for sampling data, the number of previous data, etc. Input field 206 is an area for setting a constant area in a two-dimensional plane. Indicator 207 is an area for displaying a preview screen of the graph for area monitoring.

[0168] Fig.15 An example of a screen 211 for defining a variable broken line function is shown. In screen 211, input field 212 is an area for setting a name given to a broken line graph. Input field 213 is an area for selecting a function of a broken line graph. Input field 214 is an area for selecting labels set for the X-axis and Y-axis, etc. Input field 215 is an area for setting a display ratio, display period, calculation / display cycle, threshold, upper and lower limits, etc. Area 216 is an area for setting the coordinate values ​​of the broken line function. Indicator 217 is an area for displaying a preview screen of the curve graph of the variable broken line function.

[0169] In this way, the first server device 10 can provide Fig.14 , Fig.15This example shows a screen for editing a graph display. This allows the user to easily edit a screen for displaying information such as carbon dioxide emissions and diagnostic KPIs.

[0170] As described above, the first server device 10 displays energy consumption and energy loss separately. Energy loss can be calculated by various methods. In addition, the first server device 10 can display information related to greenhouse gas emissions of a workshop including energy loss in various forms. Therefore, as an example, a method for calculating energy loss of a workshop that transfers energy by steam heated by a boiler and displaying information related to greenhouse gas emissions will be further described. Fig.16 This is a diagram showing an example of a graph showing details of steam loss in a workshop. Fig.17 and Fig.18 This is a diagram showing an example of a screen that displays steam consumption and loss in association with the flow path of steam in a plant.

[0171] In the case where a steam flow meter is provided as a sensor 30 installed in such a workshop, the information processing system 1 can calculate the consumption and loss of water vapor using the actual measurement value of the steam flow meter. In the case where a steam flow meter is not provided, the consumption and loss of water vapor can be calculated based on the measurement value of other sensors 30. As a method for calculating the consumption and loss based on the measurement value of such other sensors 30, for example, a method of calculating based on a predetermined constant ratio, a method of calculating based on heat balance, and a method of calculating based on a relationship between the cause of the loss and the loss amount can be considered. In addition, the energy consumption is measured on the energy flow and at multiple locations. In the case of correcting the measurement error of the sensor 30, the first server device 10 can use data reconstruction calculation.

[0172] The method of calculating based on a predetermined constant ratio may be as follows, that is, Figure 8 As described above, when the first flow path for determining the flow rate of steam branches into a plurality of second flow paths, the flow rate of the first flow path is distributed at a predetermined ratio to obtain the flow rates of the respective second flow paths.

[0173] The method based on heat balance is a method for measuring the loss based on the heat balance of the object to be measured. Usually, the heat P1 of the object to be measured is given as the value obtained by subtracting the heat loss P4 from the sum of the heat P2 applied from the outside and the heat P3 originally possessed by the object to be measured. That is, the following formula (1) holds.

[0174] P1=P2+P3-P4 (1)

[0175] Therefore, the first server device 10 can calculate the remaining values ​​using the equation (1) by using the determined values ​​among P1 to P4.

[0176] The method of calculating based on the relationship between the cause of the loss and the loss amount is as follows: the relationship between the measured value of the sensor 30 related to the cause of the loss and the loss amount is measured in advance, and the loss amount is measured using the relationship expressing the relationship. Such loss amount may include, for example, boiler loss, transmission loss, and emission loss, but is not limited to these. The user can set the reference Fig.15 The editing screen of the variable polygonal function definition described above enables the first server device 10 to obtain a variable polygonal function that represents the relationship between the cause of the loss and the amount of loss. The first server device 10 can use the variable polygonal function to calculate the amount of loss based on the cause of the loss. An example of a method of using this relationship is described in detail below.

[0177] Boiler loss refers to the heat lost in the boiler due to decreased efficiency. When the latent heat of water vapor contained in the exhaust gas is not recovered sufficiently, when the amount of latent heat is measured by the sensor 30, the first server device 10 can calculate the boiler loss using the actual measured value. When the amount of latent heat is not measured, the first server device 10 can calculate the boiler loss by mathematically formulating the relationship between the opening of the damper and the amount of heat. In order to perform this calculation, the user can set a reference value. Fig.15 The editing screen for the variable polygonal line function definition described above allows the first server device 10 to acquire a variable polygonal line function representing the relationship between the damper opening and the amount of heat. The first server device 10 can calculate the boiler loss according to the damper opening using the variable polygonal line function.

[0178] In addition, when the amount of latent heat is not measured, the first server device 10 can calculate the loss of the boiler based on the measurement value of the other type of sensor 30. For example, when fuel is burned in a boiler to generate water vapor, it is known that there is a constant relationship between the air ratio, which is the ratio of fuel to air, and the loss amount. Therefore, the first server device 10 can mathematically formulate the relationship between the air ratio and the loss amount in advance, and calculate the loss amount based on the air ratio using the mathematical formula. In addition, it is known that the heat loss caused by the high flow rate of the boiler tank water is in a constant relationship with the boiler tank water. Therefore, the first server device 10 can mathematically formulate the relationship between the boiler tank water and the loss amount in advance, and calculate the loss amount based on the boiler tank water using the mathematical formula. In addition, it is known that the loss due to insufficient air preheating is in a constant relationship with the preheating temperature. Therefore, the first server device 10 can mathematically formulate the relationship between the preheating temperature and the loss amount in advance, and calculate the loss amount based on the preheating temperature using the mathematical formula. In addition, it is known that the loss caused by the fouling of the burner installed in the boiler is in a constant relationship with the degree of the fouling. Therefore, the first server device 10 may formulate the relationship between the degree of burner fouling and the amount of loss relative to the elapse of the operating time in advance, and calculate the amount of loss based on the degree of fouling using the formula.

[0179] Transmission loss refers to the heat lost in piping, valves, etc. For example, regarding the heat dissipation loss from piping, it is known that there is a constant relationship between the degree of peeling of the thermal insulation material relative to the elapsed operating time and the amount of loss. Therefore, the first server device 10 can mathematically formulate the relationship between the degree of peeling of the thermal insulation material of the piping and the amount of loss in advance, and use this mathematical formula to calculate the amount of loss in the piping based on the degree of peeling. In addition, regarding the heat dissipation loss from the valve, it is also known that there is a constant relationship between the degree of peeling of the thermal insulation material relative to the elapsed operating time and the amount of loss. Therefore, the first server device 10 can mathematically formulate the relationship between the degree of peeling of the thermal insulation material of the valve and the amount of loss in advance, and use this mathematical formula to calculate the amount of loss in the valve based on the degree of peeling.

[0180] The discharge loss refers to the loss from the steam trap. The discharge loss is caused by steam leakage from valves, piping connections, and steam traps. It is known that the loss caused by steam leakage from the above parts increases as the operating time becomes longer. Therefore, the first server device 10 can mathematically express the relationship between the passage of operating time and the loss amount for each valve, piping connection, and steam trap in advance, and calculate the loss amount of the steam trap according to the operating time using the mathematical formula.

[0181] Furthermore, regarding each terminal device (eg Figure 8The first server device 10 can determine the cause of the increase or decrease in consumption as a KPI by measuring the steam (or heat) consumption of the first server device 10 (A-101, A-201, ...). The first server device 10 can pre-formulate the relationship between the KPI and the steam consumption, and calculate the steam consumption of each terminal device based on the KPI using the mathematical formula. For example, in the case where there is a constant relationship between the increase or decrease in the production of the product of the manufacturing object and the increase or decrease in heat, the first server device 10 can pre-determine this relationship through a mathematical formula. The first server device 10 can use this mathematical formula to calculate the increase or decrease in heat according to the increase or decrease in the production of the product. Alternatively, in the case where the heat of the steam decreases, the first server device 10 can use the aforementioned boiler loss calculation formula to calculate the impact on the boiler loss. In addition, in the case where there is a constant relationship between the measured value related to external interference such as the outside temperature, the indoor temperature, and the pipe fouling and the loss, the first server device 10 can pre-determine this relationship through a mathematical formula. The first server device 10 can use this mathematical formula to calculate the impact on the loss amount based on the measured value related to the external interference. In addition, the first server device 10 can mathematically formulate and determine the relationship between the idle operating state (the switch of the equipment, etc.) and the loss amount in advance. In this idle operating state, for example, steam is supplied when it is not necessary, such as when the production line is stopped. The first server device 10 can use this mathematical formula to analyze how the idle operating state affects the loss amount.

[0182] The first server device 10 can visually display the energy consumption and loss status of each area of ​​the water vapor flow path calculated in the above-mentioned manner. Fig.16 An example of a screen 221 showing the energy consumption and loss status of each area of ​​the flow path is shown. Screen 221 shows the total amount of energy input to the workshop and the amount of energy consumed or lost in the workshop in the form of a waterfall chart. Fig.16 , the height of the graph 222 represents the total amount of energy input to the plant.

[0183] exist Fig.16 In the example of FIG. 221 , the screen 221 shows the energy consumed in each of the four regions of the water vapor flow path and its details. Fig.16In FIG. 1 , images 223 to 225 represent energy consumed in the first region of the flow path. The height of image 223 represents the amount of boiler loss. The height of image 224 represents the amount of energy consumed by the process in the first region. The height of image 225 represents the amount of transmission loss generated when steam is transferred from the first region to the second region. Images 226 and 227 represent energy consumed in the second region of the flow path. The height of image 226 represents the amount of energy consumed by the process in the second region. The height of image 227 represents the amount of transmission loss generated when steam is transferred from the second region to the third region. Images 228 and 229 represent energy consumed in the third region of the flow path. The height of image 228 represents the amount of energy consumed by the process in the third region. The height of image 229 represents the amount of transmission loss generated when steam is transferred from the third region to the fourth region. Images 230 and 231 represent energy consumed in the fourth region of the flow path. The height of image 230 represents the amount of energy consumed by the process in the fourth region. The height of the image 229 indicates the amount of transmission loss generated when draining water from the fourth region. The image 232 indicates the amount of discharge loss caused by draining water. Fig.16 As shown, the first server device 10 can display the details of energy consumed in each area of ​​the water vapor flow path. This allows the user to confirm the distribution of losses in each area and select appropriate measures for decarbonization.

[0184] Fig.17 and Fig.18 An example of a screen showing steam consumption and loss in association with the flow path of steam in a workshop is shown. Fig.17 and Fig.18 In the workshop showing the consumption and loss of steam, the first flow path at the most upstream branches into the second flow path and the fourth flow path. The second flow path is connected to the third flow path. The fourth flow path branches into the fifth flow path and the sixth flow path.

[0185] exist Fig.17In the figure, screen 241 includes images 242 to 253. Image 242 shows the temporal change of the heat of steam consumed in the first flow path. Image 243 shows the temporal change of the amount of transmission loss generated when steam is transmitted from the first flow path to the second flow path and the fourth flow path. Image 244 shows the temporal change of the heat of steam consumed in the second flow path. Image 245 shows the temporal change of the amount of transmission loss generated when steam is transmitted from the second flow path to the third flow path. Image 246 shows the temporal change of the heat of steam consumed in the third flow path. Image 247 shows the temporal change of the loss amount caused by steam discarded in the third flow path. Image 248 shows the temporal change of the heat of steam consumed in the fourth flow path. Image 249 shows the temporal change of the amount of transmission loss generated when steam is transmitted from the fourth flow path to the fifth flow path and the sixth flow path. Image 250 shows the temporal change of the heat of steam consumed in the fifth flow path. An image 251 shows the temporal change of the amount of loss due to the steam discarded in the fifth flow path. An image 252 shows the temporal change of the amount of heat of the steam consumed in the sixth flow path. An image 253 shows the temporal change of the amount of loss due to the steam discarded in the sixth flow path.

[0186] The graphs 242 to 253 all show the relationship between the lower limit and upper limit of the measured value of the steam consumption or loss and the measured value. Fig. 10B As described above, when the measured value of the steam consumption or loss is less than the lower limit or greater than the upper limit, the first server device 10 may notify the user of a warning. Fig.17 Instead of displaying it in a way that can be compared with both the upper and lower limits, Fig. 9A and Fig. 9B The first server device 10 can communicate with the user selected via the client device 50. Fig.17 In response to any of the graphs in the images 242 to 253 in the screen 241, the display Figures 9A to 13 Enlarged view of the graph shown in the example.

[0187] exist Fig.18In the figure, screen 261 includes images 262 to 274. As described above, there are multiple methods for calculating the consumption and loss of water vapor. Images 262 to 274 all represent the consumption or loss of water vapor measured by any of the multiple methods, and the consumption or loss of water vapor measured by other methods. For example, image 262 represents the temporal transition of the heat of steam consumed in the first flow path. For example, image 262 can represent the measured value of the heat of steam consumed in the first flow path, the measured value of the method calculated based on the heat balance, and the measured value of the method calculated based on the relationship between the cause of the loss and the loss. When the difference between the values ​​of the consumption or loss of water vapor measured by multiple methods is greater than a predetermined threshold, the first server device 10 can notify a warning. Thus, when the error between the methods for calculating the consumption and loss of water vapor exceeds a constant value, the user can recognize the situation, verify the cause and deal with it appropriately.

[0188] exist Fig.18 , image 263 shows the temporal change of the amount of transmission loss generated when steam is transmitted from the first flow path to the second flow path and the fourth flow path. Image 264 shows the temporal change of the amount of heat of steam consumed in the second flow path. Image 265 shows the temporal change of the amount of transmission loss generated when steam is transmitted from the second flow path to the third flow path. Image 266 shows the temporal change of the amount of heat of steam consumed in the third flow path. Image 267 shows the temporal change of the amount of loss caused by steam discarded in the third flow path. Image 268 shows the temporal change of the amount of heat of steam consumed in the fourth flow path. Image 269 shows the temporal change of the amount of transmission loss generated when steam is transmitted from the fourth flow path to the fifth flow path and the sixth flow path. Image 270 shows the temporal change of the amount of heat of steam consumed in the fifth flow path. Image 271 shows the temporal change of the amount of loss caused by steam discarded in the fifth flow path. Image 272 shows the temporal change of the heat amount of the steam consumed in the sixth flow path. Image 273 shows the temporal change of the loss amount due to the steam discarded in the sixth flow path. Image 274 shows the temporal change of the loss amount of the steam in the boiler.

[0189] Images 263 to 274, like image 262, all display the amount of water vapor consumption or loss measured by any one of the plurality of methods and the amount of water vapor consumption or loss measured by other methods. In addition, in any of images 263 to 274, when the difference between the values ​​of the amount of water vapor consumption or loss measured by the plurality of methods is greater than a predetermined threshold, the first server device 10 may issue a warning. The first server device 10 may communicate with the user selected via the client device 50. Fig.18In response to any of the graphs in the images 262 to 274 in the screen 261, the display Figures 9A to 13 Enlarged view of the graph shown in the example.

[0190] As described above, the first server device 10 displays a trend graph showing the cumulative value and the predicted value of energy consumption. The trend graph is updated at a fixed period and displays the cumulative value in real time. Therefore, the user can predict the emission of greenhouse gases and take necessary measures. In addition, the first server device 10 displays the "planned value (golden line)" and "actual measured value" of the carbon dioxide emission of each energy source during the specified period. The first server device 10 displays the predicted line and the planned upper limit value based on the actual measured value, and displays a warning when the predicted value exceeds the planned upper limit value. Therefore, when it is predicted that the emission of greenhouse gases exceeds the planned upper limit value, the user can be informed of the situation in advance and can take necessary measures.

[0191] In addition, the first server device 10 displays diagnostic KPIs useful for determining the cause of energy consumption. The diagnostic KPIs may include, for example, rise / fall detection, area monitoring, variable broken line functions, and differential alarm curves. When all values ​​deviate from the reference value, the first server device 10 issues a warning, so that the user can reliably grasp the cause of greenhouse gas emissions and take necessary measures.

[0192] In addition, the first server device 10 distinguishes between excessive energy use ("consumption") and energy waste ("loss"), so that the user can distinguish between consumption and loss and take appropriate measures according to the causes of each.

[0193] As described above, according to the present embodiment, even if they are inexperienced in solving the decarbonization problem, field operators and engineers in the manufacturing industry can easily achieve decarbonization in their daily work.

[0194] The present invention is not limited to the above-mentioned embodiments. For example, multiple modules recorded in the block diagram may be integrated, or one module may be divided. Multiple steps recorded in the flowchart may be executed in parallel or in different orders according to the processing capacity of the device executing each step, or as needed, instead of the manner of executing in time series according to the description. In addition, changes may be made within the scope of the main purpose of the present invention.

[0195] In addition, for example, the configuration and operation of the first server device 10 may be distributed to a plurality of computers that can communicate with each other. In addition, for example, a part or all of the components of the first server device 10 may be provided in another device such as the second server device 20.

[0196] Description of the label

[0197] 1 Information Processing System

[0198] 10First server device

[0199] 11. Control Unit

[0200] 12 Storage unit

[0201] 13Ministry of Communications

[0202] 20 Second server device

[0203] 21 Control Department

[0204] 22 Storage

[0205] 23 Ministry of Communications

[0206] 30 sensors

[0207] 40Gateway

[0208] 50 client devices

[0209] 51 Control Department

[0210] 52 Storage

[0211] 53 Ministry of Communications

[0212] 54 Input unit

[0213] 55 Output

[0214] 61, 62 Network

[0215] 100 screens

[0216] 101~112 Pattern

[0217] 121~132 mark

[0218] 141~143 mark

[0219] 151 pictures

[0220] 152~154 curve graph

[0221] 155 Mark

[0222] 157 pictures

[0223] 158, 159 Marking

[0224] 161 pictures

[0225] 162 Graph

[0226] 163 Marking

[0227] 165 pictures

[0228] 166, 167 marking

[0229] 171 pictures

[0230] 172, 173 curve graph

[0231] 174 Marking

[0232] 181 pictures

[0233] 182 Graph

[0234] 183, 184 drawing points

[0235] 185 Marking

[0236] 191 pictures

[0237] 192 Graph

[0238] 201 screen

[0239] 202~206 Input field

[0240] 207 Mark

[0241] 211 pictures

[0242] 212~216 Input area

[0243] 217 Mark

[0244] 221 pictures

[0245] 222~232 images

[0246] 241 pictures

[0247] 242~253 images

[0248] 261 pictures

[0249] 262~274 images

Claims

1. An information processing method, which is an information processing method of an information processing device having a control unit, wherein: The information processing method comprises the following steps: The control unit acquires a measured value of a physical quantity related to the emission of greenhouse gas measured by a sensor in a workshop for process manufacturing; Based on the acquired measurement value, acquiring the emission amount of the greenhouse gas accumulated during a predetermined period; Regarding the emission of the greenhouse gas, predicting future trends based on past trends; as well as The display unit is caused to display an image showing past changes and predicted future changes in the amount of greenhouse gas emissions.

2. The information processing method according to claim 1, wherein: The control unit calculates the energy consumption of the workshop for each manufacturing batch, each manufacturing line or each instrument in the workshop based on the acquired measurement value, Based on the calculated energy consumption, the greenhouse gas emission accumulated during the predetermined period is acquired.

3. The information processing method according to claim 1 or 2, wherein: The control unit issues a warning when the predicted future change in the amount of greenhouse gas emission is larger than a reference value.

4. The information processing method according to any one of claims 1 to 3, wherein: The control unit causes the display unit to display an image in which past changes and predicted future changes related to the emission of the greenhouse gas are organized for each energy flow or each range category.

5. The information processing method according to any one of claims 1 to 4, wherein: The control unit estimates the measured value of the physical quantity of a portion not measured by the sensor, using the measured value of the physical quantity measured by the sensor. The emission amount of the greenhouse gas accumulated during the predetermined period is acquired based on the measurement value of the physical quantity measured by the sensor and the estimated measurement value of the physical quantity.

6. The information processing method according to any one of claims 1 to 5, wherein: The control unit calculates a diagnostic KPI related to the emission of the greenhouse gas of an instrument used in the workshop based on the acquired measurement value, The display unit is further caused to display an image representing the calculated diagnosis KPI.

7. The information processing method according to any one of claims 1 to 6, wherein: The control unit causes the display unit to display an image showing past changes and predicted future changes in the amount of greenhouse gas emissions so that energy consumption and loss can be distinguished.

8. An information processing device capable of communicating with a client device, wherein: The information processing device includes a control unit. The control unit acquires a measurement value of a physical quantity related to greenhouse gas emission measured by a sensor in a workshop for process manufacturing, Based on the acquired measurement value, the emission amount of the greenhouse gas accumulated during a predetermined period is acquired; Regarding the emission of greenhouse gases, the future trend is predicted based on the past trend. An image showing past changes and predicted future changes in the amount of greenhouse gas emissions is transmitted to the client device via a communication unit.

9. An information processing system comprising: a client device; and an information processing device capable of communicating with the client device, wherein: The information processing device includes a control unit. The control unit acquires a measurement value of a physical quantity related to greenhouse gas emission measured by a sensor in a workshop for process manufacturing, Based on the acquired measurement value, the emission amount of the greenhouse gas accumulated during a predetermined period is acquired; Regarding the emission of greenhouse gases, the future trend is predicted based on the past trend. An image showing past changes and predicted future changes in the amount of greenhouse gas emissions is transmitted to the client device via a communication unit.

10. A program for controlling an information processing device having a control unit capable of communicating with a client device, wherein: The program causes the control unit to execute the following steps: Acquiring a measured value of a physical quantity related to greenhouse gas emissions measured by a sensor in a workshop for process manufacturing; Based on the acquired measurement value, acquiring the emission amount of the greenhouse gas accumulated during a predetermined period; Regarding the emission of the greenhouse gas, predicting future trends based on past trends; as well as An image showing past changes and predicted future changes in the amount of greenhouse gas emissions is transmitted to the client device via a communication unit.

Images