Method of operating waste liquid facility, method of predicting nature of processed wasted liquid, operation system and prediction system

Abstract

To provide an operation method for waste liquid facility which can flexibly take care of fluctuation of nature of waste liquid.SOLUTION: According to an embodiment of the present invention, a method of operating a waste liquid processing facility for processing waste liquid caused in a product production process is provided. The operation method has a data acquiring process, a waste liquid predication value output process, and an operation condition setting process. In the data acquiring process, first data including product production process data in the product production process in a first period of times is acquired. In the waste liquid prediction value output process, based on the first data and a prediction model for use in prediction of nature of waste liquid, a predication value relating to nature of the waste liquid caused in the product production process in a second period of time after the first period of time is output. The prediction model is one generated by associating past product production process data in the product production process with the data relating to nature of the waste liquid caused in the process. In the operation condition setting process, an operation condition parameter for the waste liquid processing facility is set based on the prediction value relating to the nature of the waste liquid output in the waste liquid prediction value output process.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The present invention relates to a method for operating a waste liquid treatment facility, a method for predicting the properties of treated waste liquid, an operating system, and a prediction system. [Background technology]

[0002] In the production process of a factory, water is used for various purposes such as dissolving raw materials, cleaning the production line, cooling, etc., and this water is usually subjected to specific treatment before disposal. Here, the nature of the water to be treated changes with changes in the raw materials to be treated, and changes in the production items and production volume, so it may be necessary to devise measures for the wastewater treatment process.

[0003] As a related technique, there is known a technique disclosed in Patent Document 1. Patent Document 1 discloses a monitoring target quantity prediction method characterized by including a primary prediction step of calculating a plurality of primary predicted values ​​of a monitoring target quantity of a plant equipment using a plurality of mutually different prediction models, operation record data of the plant equipment, data related to a current operating status, meteorological observation data, and data related to a weather forecast, and a secondary prediction step of assigning a weight to each of the primary predicted values ​​predicted in the primary prediction step according to the execution timing of the secondary prediction step, and calculating a secondary predicted value of the monitoring target quantity of the plant equipment as a predicted value of the monitoring target quantity of the plant equipment using the plurality of weighted primary predicted values. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] JP 2013-161336 A Summary of the Invention [Problem to be solved by the invention]

[0005] However, the inventors' investigations revealed that there is still room for improvement in terms of optimizing the conditions for waste liquid treatment.

[0006] In view of the above circumstances, the present invention provides a method for operating a waste liquid treatment facility that can flexibly respond to changes in the properties of the waste liquid. [Means for solving the problem]

[0007] Specifically, the present invention provides the following: (1) A method for operating a waste liquid treatment facility for treating waste liquid from a product production process, comprising the steps of: The method includes a data acquisition step, a wastewater prediction value output step, and an operating condition setting step, In the data acquisition step, first data including product production process data in the product production process at a first time is acquired; In the wastewater prediction value output step, a prediction value regarding a property of the wastewater from the product production process at a second time after the first time is output based on the first data and a prediction model for predicting a property of the wastewater; Here, the prediction model is a model created by associating past product production process data in the product production process with data on the properties of waste liquid discharged at that time, In the operating condition setting step, operating condition parameters of the waste liquid treatment facility are set based on the predicted value relating to the property of the waste liquid outputted in the waste liquid predicted value output step. (2) In the method for operating the waste liquid treatment facility according to (1), A method for operating a waste liquid treatment facility, wherein the prediction model is a model configured to be updateable before the waste liquid prediction value output step is executed. (3) In the method for operating the waste liquid treatment facility according to (1) or (2), The prediction model is a model created by further associating a predetermined parameter of a product produced in the product production process, A method for operating a waste liquid treatment facility, wherein the first data acquired in the data acquisition step further includes information regarding a predetermined parameter of the product. (4) A method for predicting the properties of wastewater after treatment at a wastewater treatment facility that treats wastewater from a product production process, comprising: The method includes a data acquisition step and a post-treatment wastewater predicted value output step, In the data acquisition step, second data including product production process data in the product production process at a first time and operating condition parameters to be executed by the waste liquid treatment facility are acquired; In the post-treatment wastewater predicted value output step, a predicted value regarding the property of the post-treatment wastewater from the wastewater treatment equipment at a second time after the first time is output based on the second data and a prediction model for predicting the property of the post-treatment wastewater, Here, the method for predicting the properties of treated waste liquid is a model created by associating past product production process data in the product production process, data relating to the properties of the waste liquid discharged at that time, operating condition parameters under which the waste liquid treatment equipment treated the waste liquid discharged at that time, and the properties of the treated waste liquid. (5) (4) A method for predicting the properties of a post-treatment wastewater according to the present invention, The method further includes a data reacquisition step and a post-treatment wastewater predicted value re-output step, In the data reacquisition step, if the predicted value relating to the property of the post-treatment wastewater outputted in the post-treatment wastewater predicted value output step does not fall within a predetermined range, an operating condition parameter to be executed by the wastewater treatment facility is reset, and the second data is acquired; A method for predicting the properties of post-processed waste liquid, in which the post-processed waste liquid predicted value re-output process re-outputs a predicted value regarding the properties of the post-processed waste liquid from the waste liquid treatment equipment at the second time based on the second data acquired in the data re-acquisition process and the prediction model that predicts the properties of the post-processed waste liquid. (6) In the method for predicting the properties of a post-treatment wastewater according to (4) or (5), The method for predicting the properties of a post-treatment effluent, wherein the prediction model is a model configured to be updateable before the post-treatment effluent prediction value output step is executed. (7) The method for predicting the properties of a post-treatment wastewater according to any one of (4) to (6), The prediction model is a model created by further associating the temperature and / or temperature transition of the wastewater with the biological treatment capacity corresponding thereto, A method for predicting the properties of treated effluent, wherein the second data acquired in the data acquisition step further includes information regarding the temperature and / or temperature transition of the effluent. (8) The method for predicting the properties of a post-treatment wastewater according to any one of (4) to (7), The method for predicting the properties of treated wastewater, wherein the data acquisition step is configured so that constraint conditions can be set for some of the operating condition parameters that the wastewater treatment facility is to operate. (9) The method for predicting the properties of a post-treatment wastewater according to any one of (4) to (7), The prediction model is a model created by further associating a predetermined parameter of a product produced in the product production process, A method for predicting a property of a treated effluent, wherein the second data acquired in the data acquisition step further includes information regarding a predetermined parameter of the product. (10) An operation system for waste liquid treatment equipment for treating waste liquid from a product production process, comprising: The apparatus includes a data acquisition unit, a wastewater prediction value output unit, and an operating condition setting unit, the data acquisition unit acquires first data including product production process data in the product production process at a first time; the wastewater prediction value output unit outputs a prediction value regarding a property of the wastewater from the product production process at a second time after the first time based on the first data and a prediction model for predicting a property of the wastewater; Here, the prediction model is a model created by associating past product production process data in the product production process with data on the properties of waste liquid discharged at that time, The operating condition setting unit sets operating condition parameters of the waste liquid treatment facility based on the predicted value relating to the property of the waste liquid outputted by the waste liquid predicted value output unit. (11) A prediction system for predicting the properties of wastewater after treatment at a wastewater treatment facility that treats wastewater from a product production process, comprising: A data acquisition unit and a post-treatment wastewater predicted value output unit are provided, The data acquisition unit acquires second data including product production process data in the product production process at a first time and operating condition parameters to be executed by the waste liquid treatment facility; the post-treatment wastewater predicted value output unit outputs a predicted value regarding the properties of the post-treatment wastewater from the wastewater treatment equipment at a second time after the first time based on the second data and a prediction model for predicting the properties of the post-treatment wastewater; Here, the prediction model is a model created by associating past product production process data in the product production process, data relating to the properties of the waste liquid discharged at that time, operating condition parameters when the waste liquid treatment equipment treated the discharged waste liquid at that time, and the properties of the waste liquid after treatment, in this prediction system.

[0008] The technology disclosed in the aforementioned Patent Document 1 focuses only on the operating conditions of the plant itself that treats wastewater. In contrast, the operating method of the wastewater treatment facility of the present application utilizes data on the product production process located upstream of the wastewater generation, thereby making it possible to optimize the operating conditions of the wastewater treatment facility. More specifically, by linking product production process data with waste liquid treatment data, it is possible to predict fluctuations in the properties of waste liquid and optimize the operating conditions of waste liquid treatment equipment, thereby minimizing the operating costs and environmental load of waste liquid treatment equipment. Furthermore, even within the limited processing capacity of the waste liquid treatment equipment, it is possible to achieve the target waste liquid properties (wastewater quality standards, etc.) without making additional capital investments by adjusting parameters related to the waste liquid treatment data linked to the product production process.

[0009] From this, it can be said that the above-mentioned embodiment provides a method for operating a waste liquid treatment facility that can flexibly respond to changes in the properties of the waste liquid. [Brief description of the drawings]

[0010] [Figure 1] 1 is a diagram showing an overall configuration of an information processing system 100. [Diagram 2] 1 is a diagram illustrating a hardware configuration of an information processing device 1. [Diagram 3] 2 is a functional block diagram showing functions of the information processing device 1. FIG. [Figure 4] 1 is an activity diagram showing the flow of information processing using the information processing device 1 and the like. [Diagram 5] 1 is an activity diagram showing the flow of information processing using the information processing device 1 and the like. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0011] Hereinafter, embodiments of the present invention will be described. Note that various features shown in the following embodiments can be combined with each other.

[0012] Incidentally, the program for realizing the software appearing in this embodiment may be provided as a non-transitory computer-readable recording medium, or may be provided so as to be downloadable from an external server, or may be provided so that the program is started on an external computer and its functions are realized on a client terminal (so-called cloud computing).

[0013] In this embodiment, the term "unit" may include, for example, a combination of hardware resources implemented by a circuit in the broad sense and software information processing that can be specifically realized by these hardware resources. In addition, this embodiment handles various information, which may be represented by, for example, physical values ​​of signal values ​​representing voltage and current, high and low signal values ​​as a binary bit set consisting of 0 or 1, or quantum superposition (so-called quantum bits), and communication and calculation may be performed on a circuit in the broad sense.

[0014] In addition, a circuit in the broad sense is a circuit realized by at least appropriately combining a circuit, circuitry, a processor, and a memory, etc. In other words, it includes an application specific integrated circuit (ASIC), a programmable logic device (e.g., a simple programmable logic device (SPLD), a complex programmable logic device (CPLD), and a field programmable gate array (FPGA)), etc.

[0015] 1. Hardware Configuration In this section, a hardware configuration of the information processing system 100 according to this embodiment will be described.

[0016] The information processing system 100 of this embodiment is a system configured to be able to execute an operation method (sometimes simply referred to as an "operation method") of a waste liquid treatment facility that treats waste liquid from a product production process, and a method (sometimes simply referred to as a "prediction method") for predicting the properties of waste liquid after treatment in a waste liquid treatment facility that treats waste liquid from a product production process. From this perspective, the information processing system 100 of this embodiment is also sometimes referred to as an "operation system" or a "prediction system." Here, the information processing system 100 of this embodiment includes an information processing device 1 and a communication line 2. The communication line 2 includes the Internet or the like, and mediates data exchange between devices connected to the line. In the information processing system 100 of this embodiment, the information processing device 1 is connected to a plant PL1 and a plant PL2 via the communication line 2. It should be noted that the system exemplified as the information processing system 100 is made up of one or more devices or components. Therefore, even the information processing device 1 alone is an example of a system.

[0017] Here, plant PL1 is a plant that executes a product production process, and plant PL2 is a plant that functions as a waste liquid treatment facility that treats waste liquid from the product production process. That is, in terms of the flow of waste liquid, plant PL1 is located upstream of plant PL2, and typically, waste liquid generated in plant PL1 is transferred to plant PL2 via liquid line LL1. The equipment and the like arranged in the plant PL2 can be appropriately set according to the type of waste liquid. For example, if the waste liquid is aqueous, a biological treatment device or the like may be provided in the plant PL2. Note that this biological treatment device may be applied with microorganisms capable of purifying the waste water. Although not shown in FIG. 1, a sensor may be attached to the liquid line LL1, and this sensor and the information processing device 1 may be connected via the communication line 2.

[0018] 2 is a diagram showing a hardware configuration of the information processing device 1. The information processing device 1 has a control unit 11, a storage unit 12, an input unit 13, a display unit 14, and a communication unit 15, and is configured by electrically connecting each of these units via a communication bus 10. Each unit provided in the information processing device 1 will be described below.

[0019] (Control unit 11) The control unit 11 is, for example, a central processing unit (CPU) not shown. The control unit 11 realizes various functions related to the information processing device 1 by reading out a predetermined program stored in the storage unit 12. That is, information processing by software stored in the storage unit 12 can be specifically realized by the control unit 11, which is an example of hardware, and executed as each functional unit included in the control unit 11. These will be described in more detail in the next section. Note that the control unit 11 is not limited to being single, and may be implemented with multiple control units 11 for each function. Also, a combination of these may be used.

[0020] (Storage unit 12) The storage unit 12 stores various pieces of information defined by the above description. This can be implemented, for example, as a storage device such as a solid state drive (SSD) that stores various programs and the like related to the information processing device 1 executed by the control unit 11, or as a memory such as a random access memory (RAM) that stores temporarily required information (arguments, arrays, etc.) related to the program calculations. The storage unit 12 stores various programs, variables, etc. related to the information processing device 1 executed by the control unit 11.

[0021] (Input section 13) The input unit 13 may be included in the housing of the information processing device 1, or may be externally attached. For example, the input unit 13 may be implemented as a touch panel integrated with the display unit 14. If it is a touch panel, the user can input a tap operation, a swipe operation, or the like. Of course, a switch button, a mouse, a QWERTY keyboard, or the like may be adopted instead of the touch panel. That is, the input unit 13 accepts an operation input made by the user. The input is transferred as a command signal to the control unit 11 via the communication bus 10, and the control unit 11 can execute a predetermined control or calculation as necessary.

[0022] (Display section 14) The display unit 14 may be, for example, included in the housing of the information processing device 1, or may be externally attached. The display unit 14 displays a screen of a graphical user interface (GUI) that can be operated by a user. This is preferably implemented by using display devices such as a CRT display, a liquid crystal display, an organic EL display, and a plasma display according to the type of the information processing device 1.

[0023] (Communications Department 15) The communication unit 15 is configured to be able to transmit various electrical signals from the information processing device 1 to external components. The communication unit 15 is also configured to be able to receive various electrical signals from the external components to the information processing device 1. The communication unit 15 may have a network communication function, thereby enabling communication of various information between the information processing device 1 and an external device via the communication line 2.

[0024] Although not shown, the plant PL1 and the plant PL2 connected to the information processing device 1 via the communication line 2 may also be equipped with devices having the same hardware configuration as the information processing device 1 described above.

[0025] 2. Functional configuration In this section, the functional configuration of this embodiment will be described. Fig. 3 is a functional block diagram showing the functions of the information processing device 1. As described above, information processing by software (stored in the storage unit 12) is specifically realized by hardware (control unit 11), and can be executed as each functional unit included in the control unit 11.

[0026] Specifically, the information processing device 1 (control unit 11) may include, as each functional unit, a data acquisition unit 111, a effluent prediction value output unit 112, an operating condition setting unit 113, a post-treatment effluent prediction value output unit 114, a data reacquisition unit 115, a post-treatment effluent prediction value re-output unit 116, a prediction model creation unit 117, and a memory management unit 118. Note that each of these functional units may be appropriately increased or omitted depending on the application to which the information processing device 1 is applied, etc.

[0027] (Data Acquisition Unit 111) The data acquisition unit 111 is configured to be able to execute a data acquisition step. In the data acquisition step, the data acquisition unit 111 acquires first data including product production process data in the product production process at a first time. In addition, in the data acquisition step, the data acquisition unit 111 acquires second data including product production process data in the product production process at the first time and operating condition parameters to be executed by the waste liquid treatment facility. In this acquisition, the data acquisition unit 111 is configured to acquire various information (analysis data, etc.) via the communication unit 15, for example, from sensors and instruments arranged in the plant PL1.

[0028] (Waste liquid prediction value output unit 112) The waste liquid prediction value output unit 112 is configured to be able to execute a waste liquid prediction value output step. In the waste liquid prediction value output step, the waste liquid prediction value output unit 112 outputs a prediction value regarding the properties of the waste liquid from the product production process at a second time after the first time, based on the above-mentioned first data and a prediction model that predicts the properties of the waste liquid. Here, the prediction model is a model created by associating past product production process data in the product production process with data regarding the properties of the waste liquid discharged at that time. Details of this information processing will be described later.

[0029] (Operation condition setting unit 113) The operating condition setting unit 113 is configured to be able to execute an operating condition setting step. In the operating condition setting step, the operating condition setting unit 113 sets operating condition parameters of the wastewater treatment facility based on the predicted value relating to the property of the wastewater outputted by the wastewater predicted value output unit. When setting the operating conditions, the operating condition setting unit 113 is typically configured to transmit various information (signals, etc.) to various devices arranged in the plant PL2 via the communication unit 15.

[0030] (Post-treatment wastewater predicted value output unit 114) The post-treatment waste liquid predicted value output unit 114 is configured to be able to execute a post-treatment waste liquid predicted value output step. In the post-treatment waste liquid predicted value output step, the post-treatment waste liquid predicted value output unit 114 outputs a predicted value regarding the properties of the post-treatment waste liquid from the waste liquid treatment equipment at a second time after the first time, based on the above-mentioned second data and a prediction model for predicting the properties of the post-treatment waste liquid. Here, the prediction model is a model created by associating past product production process data in the product production process, data regarding the properties of the waste liquid discharged at that time, operating condition parameters when the waste liquid treatment equipment treated the discharged waste liquid at that time, and the properties of the post-treatment waste liquid. Details of this information processing will be described later.

[0031] (Data reacquisition unit 115) The data reacquisition unit 115 is configured to be able to execute a data reacquisition step. In the data reacquisition step, if the predicted value relating to the properties of the post-treatment wastewater outputted in the post-treatment wastewater predicted value output step does not fall within a predetermined range, the data reacquisition unit 115 resets the operating condition parameters to be executed by the wastewater treatment facility, and acquires second data. A specific embodiment will be described later.

[0032] (Post-treatment wastewater predicted value re-output unit 116) The post-treatment waste liquid predicted value re-output unit 116 is configured to be able to execute a post-treatment waste liquid predicted value re-output step. In the post-treatment waste liquid predicted value re-output step, the post-treatment waste liquid predicted value re-output unit 116 re-outputs a predicted value regarding the properties of the post-treatment waste liquid from the waste liquid treatment facility at the second time based on the second data acquired in the data re-acquisition step and a prediction model for predicting the properties of the post-treatment waste liquid.

[0033] (Prediction model creation unit 117) The prediction model creation unit 117 is configured to be able to execute a prediction model creation step. In the prediction model creation step, the prediction model creation unit 117 creates or updates a prediction model used in the above-mentioned wastewater predicted value output step, the post-treatment wastewater predicted value output step, and the like.

[0034] (Memory Management Department 118) The memory management unit 118 is configured to be able to execute a memory management process. In the memory management process, the memory management unit 118 is configured to manage various pieces of information to be stored that are related to the information processing system 100 of this embodiment. Typically, the memory management unit 118 is configured to store information input from the plant PL1 or the plant PL2 to the information processing device 1 in a memory area. This memory area is exemplified by the memory unit 12 of the information processing device 1 or the memory units of various terminals, but this memory area does not necessarily have to be within the system of the information processing system 100, and the memory management unit 118 can also manage various pieces of information to be stored in an external storage device or the like.

[0035] 3. Details of data processing In Section 3, an information processing method executed by the information processing device 1 etc. will be described with reference to an activity diagram etc.

[0036] (Applies to) First, an application target of the information processing device 1 of this embodiment will be described. As described above, the information processing system 100 (information processing device 1) of this embodiment is used in a method for operating a waste liquid treatment facility and a method for predicting waste liquid after treatment in the waste liquid treatment facility, and the type of waste liquid here can be set appropriately. That is, the waste liquid supplied from the product production process depends on the type of the product production process and may be water-based or oil-based. That is, the plant PL1 that executes the product production process in this embodiment is not limited to a specific product, and may be any of various known plants, such as a paper plant, a steel plant, a power plant, a petroleum plant, or a chemical plant. Below, we will explain the flow of information processing for the method of operating a waste liquid treatment facility and the method of predicting the amount of waste liquid after treatment at the waste liquid treatment facility, assuming that the waste liquid from a product production process is aqueous.

[0037] (Information processing flow (operation method of waste liquid treatment equipment)) The flow of information processing performed by the information processing device 1 etc. of this embodiment will be described with reference to Fig. 4 etc. Fig. 4 is an activity diagram showing the flow of information processing using the information processing device 1 etc.

[0038] First, in the operating method of this embodiment, the data acquiring unit 111 acquires first data including product production process data in the product production process at a first time (activity A101).

[0039] The first data here includes product production process data in the product production process at the first time, and this product production process data includes the product production volume, production brand, chemicals used and their amounts, the amount of waste liquid to be treated, control parameters within plant PL1, etc.

[0040] Acquisition of this data is achieved, for example, by acquiring various information (analysis data, etc.) from sensors and instruments arranged in the plant PL1 via the communication unit 15. That is, in the case of the production volume of products, this activity is achieved by the data acquisition unit 111 acquiring the weight of the produced products as at least a part of the first data. The data (data group) constituting the first data may be quantitative or qualitative. When a qualitative parameter is used, a numerical value may be assigned to the parameter and the parameter may be treated as quantitative data.

[0041] With regard to such product production process data, specific examples of various parameters in a papermaking process using a water system during the product production process will be described below, including water quality parameters, control parameters, and result parameters.

[0042] Water quality parameters include, for example, pH of the water system, electrical conductivity, redox potential, zeta potential, turbidity, temperature, bubble height, biochemical oxygen demand (BOD), chemical oxygen demand (COD (e.g. COD Mn , C.O.D. Cr )), absorbance (e.g., UV absorbance), color (e.g., RGB value), residual chemical concentration, particle size distribution, degree of aggregation, amount of foreign matter, foamed area on the water surface, dirty area in the water, amount of air bubbles, amount of glucose, amount of organic acid, amount of starch, amount of calcium, amount of total chlorine, amount of free chlorine, amount of dissolved oxygen, cationic demand, amount of hydrogen sulfide, amount of hydrogen peroxide, and respiration rate of microorganisms in the system.

[0043] Examples of control parameters include the operating speed (machining speed) of the papermaking machine, the filter cloth rotation speed of the raw material dehydrator, the filter cloth rotation speed of the washer, the amount of chemicals added to the water system, the amount of chemicals added to the raw materials added to the water system, the amount of chemicals added to equipment related to the water system, the amount of steam for heating, the temperature of the steam for heating, the pressure of the steam for heating, the flow rate from the seed box, the nip pressure of the press part, the felt vacuum pressure of the press part, the blending ratio of the papermaking raw materials, the blending amount of broken paper in the papermaking raw materials, the mesh size of the screen for the papermaking raw materials, the gap distance between the rotor and stator of the beater, the freeness and the degree of beating, etc. Examples of "equipment related to the water system" include equipment such as the wires and felts of the papermaking machine to which chemicals are directly added.

[0044] Examples of the result parameters include white water consistency, the amount of steam in the equipment for producing paper products, the amount of steam in the equipment for producing paper products, the steam temperature in the equipment for producing paper products, the steam pressure in the equipment for producing paper products, the timing of paper breakage in the process, freeness, degree of beating, amount of aeration, etc. Among these, examples of the amount of steam in the equipment for producing paper products that can be used include the amount of steam in the paper machine dryer, the amount of steam in the kraft pulp black liquor evaporator, the amount of steam in the black liquor heater in the kraft pulp digester, and the amount of steam injected to heat the pulp raw material or white water.

[0045] The first data may further include information on a predetermined parameter of the product. The predetermined parameter of the product is typically an analytical value related to the product, and may be, for example, the workmanship or quality of the product (product purity, impurities contained, analytical values ​​obtained by equipment, etc.). Such predetermined parameters of the product may be acquired from various sensors arranged in the plant PL1 via the communication unit 15, or may be acquired based on the contents of a quality guarantee issued by the plant PL1.

[0046] Following the above, specific examples of various parameters in a papermaking process that uses an aqueous system during the product production process will be described. The specified parameters of such products include the unit weight (basis weight), yield rate, moisture content of the paper product, thickness of the paper product, ash concentration in the paper product, types of defects in the paper product, number of defects in the paper product, etc.

[0047] In the operating method of this embodiment, after acquiring the first data in this manner, a predicted value regarding the properties of the waste liquid from the product production process at a second time after the first time is output based on the first data and a prediction model that predicts the properties of the waste liquid (activity A102).

[0048] In this activity, the prediction model is a model created by associating past product production process data in the product production process with data on the properties of the waste liquid discharged during the process. Here, this predictive model is a model of the relationship between the actual performance of the product production process and the properties of the waste liquid discharged during that process. This model may be, for example, a function or a lookup table that shows the relationship between the two, or it may be a trained model that has learned the relationship between the two.

[0049] Regarding such a prediction model, the relationship between past product production process data in the product production process and data on the properties of the waste liquid discharged at that time can be analyzed based on a known analysis method. Typically, a desired prediction model can be obtained by analyzing using regression analysis (linear model, generalized linear model, generalized linear mixed model, ridge regression, lasso regression, elastic net, support vector regression, projection pursuit regression, etc.), time series analysis (VAR model, SVAR model, ARIMAX model, SARIMAX model, state space model, etc.), decision tree (decision tree, regression tree, random forest, XGBoost, etc.), neural network (simple perceptron, multilayer perceptron, DNN, CNN, RNN, LSTM, etc.), Bayes (Naive Bayes, etc.), clustering (k-means, k-means++, etc.), ensemble learning (Boosting, Adaboost, etc.), etc. In addition, the prediction model is created by the prediction model creation unit 117, but this is not necessarily limited thereto. Such a prediction model may be created outside the information processing system 100, and the created model may be installed in the information processing device 1 or the like to perform the operation method of this embodiment. Furthermore, the prediction model may be a model configured to be updatable before the wastewater predicted value output step is executed. In this case, the prediction model creation unit 117 may be configured to update the prediction model sequentially in accordance with the accumulation of wastewater treatment results, etc.

[0050] Furthermore, this prediction model outputs a predicted value regarding the properties of the wastewater at a second time after the first time, and this prediction model may be configured to predict changes (deterioration) of the wastewater over time. When predicting such changes (deterioration) over time, the environment (temperature, weather) in which the information processing system 100 exists may be taken into account as reference information to improve the prediction accuracy. Depending on the application scene of the information processing system 100 of this embodiment, the first time and the second time may be substantially simultaneous.

[0051] Here, the properties of the discharged waste liquid associated with the prediction model can be set appropriately, but in the case where the waste liquid is aqueous, various items of the water quality parameters mentioned above can be mentioned.

[0052] The prediction model may be a model created by further associating with a predetermined parameter of a product produced in the product production process. That is, in addition to past product production process data in the product production process and data on the properties of the waste liquid discharged at that time, a prediction model may be created by further associating with a predetermined parameter of a product produced in the product production process. When the first data acquired by the data acquisition unit 111 includes a predetermined parameter of a product, applying a prediction model associated with the predetermined parameter of the product can contribute to improving the prediction accuracy in this activity.

[0053] Next, in the operating method of this embodiment, operating condition parameters of the wastewater treatment facility are set based on the predicted values ​​relating to the properties of the wastewater outputted in the wastewater predicted value output step (activity A103).

[0054] In a typical embodiment, this activity is achieved by the operating condition setting unit 113 of the information processing device 1 transmitting various information (signals, etc.) via the communication unit 15 to various devices arranged in the plant PL2. More specifically, the operating condition setting unit 113 sets conditions for the properties of the wastewater so that the wastewater can be discharged from the plant PL2, and controls the plant PL2 to operate under the conditions. For example, when it is predicted that the pH of the wastewater supplied from the plant PL1 is different from normal, the amount of neutralizing agent used in the plant PL2 can be adjusted to be appropriate. Similarly, when it is predicted that the chemical oxygen demand (COD) value of the wastewater supplied from the plant PL1 is higher than normal, the operating condition setting unit 113 can set conditions such as the dissolved oxygen concentration and sludge control concentration in the biological treatment process performed in the plant PL2 to an appropriate range. In addition, the operating condition setting unit 113 can set various conditions such as the treatment temperature condition in the plant PL2, the humidity condition in the plant, and the mixing condition of the mixing tank.

[0055] The wastewater treated in this manner is discharged from the plant PL2 as appropriate. For example, if the wastewater treated in the plant PL2 is water, it may be discharged into a river or the like after a final inspection of the water quality, etc.

[0056] (Information processing flow (method of predicting the properties of treated wastewater)) The flow of information processing performed by the information processing device 1 etc. of this embodiment will be described with reference to Fig. 5 etc. Fig. 5 is an activity diagram showing the flow of information processing using the information processing device 1 etc. Note that this prediction method overlaps with the above-mentioned driving method in some parts, so the following description will focus on the differences.

[0057] First, in the prediction method of this embodiment, the data acquisition unit 111 acquires second data including product production process data in the product production process at a first time and operating condition parameters to be executed by the waste liquid treatment equipment (activity A201).

[0058] The product production process data included in this second data may be the same as the product production process data in the above-mentioned prediction method, and the description thereof will be omitted here. Also, the operating condition parameters included in the second data may be the same as the operating condition parameters in the above-mentioned prediction method, and the description thereof will be omitted here.

[0059] In the prediction method of this embodiment, the data acquisition unit 111 may be configured to set constraint conditions for some of the operating condition parameters to be executed by the wastewater treatment facility. To explain with a typical example, the constraint conditions include the operating limit value of the wastewater treatment facility, costs, environmental load constraints, etc., and the prediction method of this embodiment can propose optimal treatment specifications even with certain constraints. Specifically, when setting operating condition parameters to match the target values, constraint conditions such as the amount of chemicals used as a cost condition and the amount of dilution water used, the amount of chemicals used, pump operating conditions, and aeration volume as environmental load conditions are set, and optimal operating conditions can be proposed within the range of the constraints.

[0060] The second data may further include information about a predetermined parameter of the product. The predetermined parameter of the product that may be included in the second data may be the same as the predetermined parameter of the product in the above-mentioned prediction method, and the description thereof will be omitted here.

[0061] The second data may further include information on the temperature of the wastewater and / or the temperature transition. In other words, by increasing the number of parameters that can be included in the second data, the accuracy of predicting the properties of the treated wastewater can be improved, and the details of this process will be described later.

[0062] In the prediction method of this embodiment, after acquiring the second data in this manner, the post-treatment waste liquid predicted value output unit 114 outputs a predicted value regarding the properties of the post-treatment waste liquid from the waste liquid treatment equipment at a second time after the first time based on the second data and a prediction model that predicts the properties of the post-treatment waste liquid (activity A202).

[0063] In this activity, the predictive model is a model created by associating past product production process data in the product production process, data on the properties of the waste liquid discharged at that time, the operating condition parameters used by the waste liquid treatment equipment to treat the waste liquid discharged at that time, and the properties of the waste liquid after treatment.

[0064] Regarding the differences from the above-mentioned operating method, the predictive model used in this embodiment has a feature in that it associates past product production process data in the product production process and data on the properties of the waste liquid discharged at that time, as well as operating condition parameters used by the waste liquid treatment equipment to treat the discharged waste liquid and the properties of the waste liquid after treatment.

[0065] In other words, because such a predictive model is a model in which at least these four parameters are correlated, it can be said that it is easy to accurately predict the properties of the treated wastewater after it is actually treated by the wastewater treatment equipment. This prediction model may also be configured to be updateable before the post-treatment wastewater predicted value output step is executed.

[0066] In addition, similarly to the above-mentioned operating method, the model may be created by further associating certain parameters of the product produced in the product production process. In this case, it becomes easier to predict the properties of the post-treatment wastewater with higher accuracy.

[0067] Furthermore, this prediction model may be a model that is created by further associating the temperature and / or temperature transition of the wastewater with the biological treatment capacity corresponding thereto. That is, since the second data may include information on the temperature of the waste liquid and / or the temperature transition, by using such a prediction model, it becomes possible to make predictions taking into account seasonal changes in biological treatment capacity. In a typical example, the operation status of the biological treatment device may become insufficient in summer due to an increase in the waste liquid temperature (particularly the water temperature), but the optimal operating condition parameters for the biological treatment device can be set by taking into account the transition of the waste liquid temperature (particularly the water temperature) at this time and the operating conditions of the temperature control equipment before and after. The data on the temperature of the waste liquid (wastewater) associated as the prediction model may be based on the temperature of the waste liquid in the plant PL1 and / or plant PL2, the data on the temperature of the waste liquid in the biological treatment device (and the processes before and after it), or meteorological data.

[0068] The output of the predicted value of the treated wastewater as described above enables management of the treated wastewater in the plant PL2. The treated wastewater may be discharged from the plant PL2 as appropriate, as described in the above-mentioned operation method. For example, if the treated wastewater treated in the plant PL2 is water, it may be discharged into a river or the like after a final inspection of the water quality, etc. is performed.

[0069] In the prediction method of this embodiment, the data reacquisition unit 115 may be configured to reset the operating condition parameters to be executed by the waste liquid treatment facility and acquire second data when the predicted value relating to the properties of the post-treatment waste liquid outputted in the post-treatment waste liquid predicted value outputting step does not fall within a predetermined range (this step may be referred to as the "data reacquisition step"). Also, the post-treatment waste liquid predicted value re-output unit 116 may be configured to re-output a predicted value relating to the properties of the post-treatment waste liquid from the waste liquid treatment facility at the second time based on the second data acquired in the data reacquisition step and a prediction model for predicting the properties of the post-treatment waste liquid (this step may be referred to as the "post-treatment waste liquid predicted value re-outputting step").

[0070] As shown in the activity diagram of Fig. 5, when a post-treatment effluent predicted value is once output, if a certain parameter is not within a predetermined range (for example, if the value is such that it is not appropriate to discharge the treated effluent into a river, etc.), the second data can be acquired again. That is, the system can be configured to perform an operation similar to the above-mentioned activity A201, but for the sake of convenience, this operation will be referred to as a "data reacquisition process" in this specification. As described above, a post-processing waste liquid prediction value can be output based on the second data acquired in the data reacquisition process, and this process can be repeated until the managed parameters fall within a predetermined range. Typically, this data reacquisition step can be performed while changing the operating condition parameters for the waste liquid treatment, i.e., by repeatedly performing the data reacquisition step until the controlled parameters are within a predetermined range, this essentially has the aspect of optimizing the operating condition parameters for the waste liquid treatment.

[0071] Examples of parameters that do not fall within this predetermined range include the water quality parameters mentioned above, but these can be set appropriately depending on the type of waste liquid.

[0072] As described above, the present embodiment provides a method for operating a wastewater treatment facility that can flexibly respond to changes in the properties of the wastewater. Such an embodiment reduces the investment required for the wastewater treatment facility and is expected to have the effect of reducing the environmental load.

[0073] 4. Variations In Section 4, a modification of the information processing method of the information processing device 1 and the like described above will be described.

[0074] Although the above embodiment has been described as the configuration of the information processing device 1, a program for causing a computer to function as each unit of the information processing device may be provided.

[0075] In the above embodiment, the information processing device 1 is applied to plants PL1 and PL2 connected by the liquid line LL1, but the two plants do not necessarily need to be connected by the liquid line LL1, and a configuration in which waste liquid is transported from plant PL1 to plant PL2 by a rotary or the like can also be adopted. Note that the business entity that owns plant PL1 and the business entity that owns plant PL2 may be the same or different.

[0076] In the above embodiment, the operation method and the prediction method using the prediction model are shown, but the information associated when creating the prediction model is not limited to the above. That is, the prediction model used in the present embodiment may be associated with various other conditions such as weather conditions, regional conditions, and conditions related to the age of the facility.

[0077] Finally, although various embodiments of the present invention have been described, these are presented as examples and are not intended to limit the scope of the invention. The novel embodiments can be implemented in various other forms, and various omissions, substitutions, and modifications can be made without departing from the spirit of the invention. The embodiments and their modifications are included within the scope and spirit of the invention, and are included in the scope of the invention and its equivalents described in the claims. [Explanation of symbols]

[0078] 1: Information processing equipment 2: Communication lines 10: Communication bus 11: Control section 12: Storage section 13: Input section 14:Display section 15: Communications Department 100: Information processing systems 111: Data acquisition section 112: Waste liquid prediction value output section 113: Operation condition setting section 114: Post-treatment wastewater predicted value output section 115: Data reacquisition unit 116: Post-treatment wastewater predicted value re-output unit 117: Prediction Model Creation Department 118: Memory management department LL1: Liquid Line PL1: Plant PL2: Plant

Claims

1. A method for operating a wastewater treatment facility for treating wastewater from a product production process, comprising: The method includes a data acquisition step, a wastewater prediction value output step, and an operating condition setting step, In the data acquisition step, first data including product production process data in the product production process at a first time is acquired; wherein the product production process data includes data on the weight of the product to be produced, the wastewater predicted value output step outputs a predicted value regarding the properties of the wastewater from the product production process at a second time after the first time based on the first data and a prediction model that predicts the properties of the wastewater; wherein the prediction model is a model created by associating product production process data relating to past product production in the product production process with data relating to properties of waste liquid discharged during the past product production, In the operating condition setting step, operating condition parameters of the waste liquid treatment facility are set based on the predicted value relating to the properties of the waste liquid outputted in the waste liquid predicted value output step.

2. The method for operating a waste liquid treatment facility according to claim 1, A method for operating a waste liquid treatment facility, wherein the prediction model is a model configured to be able to be updated before the waste liquid prediction value output step is executed.

3. The method for operating a waste liquid treatment facility according to claim 1, the prediction model is a model created by further associating predetermined parameters of a product produced in the product production process during the past product production, A method for operating a waste liquid treatment facility, wherein the first data acquired in the data acquisition step further includes information regarding a predetermined parameter of a product related to the product production process.

4. In the method for operating the waste liquid treatment equipment according to claim 3, A method for operating a waste liquid treatment facility, wherein the predetermined parameter of the product is information relating to the performance or quality of the product produced in the product production process.

5. A method for predicting the properties of treated wastewater from a wastewater treatment facility that treats wastewater from a product production process, comprising: A data acquisition step and a post-treatment wastewater predicted value output step are provided, In the data acquisition step, second data including product production process data in the product production process at a first time and operating condition parameters that the waste liquid treatment facility is to execute after the first time is acquired; wherein the product production process data includes data on the weight of the product to be produced, the post-treatment wastewater predicted value output step outputs a predicted value relating to the properties of the post-treatment wastewater from the wastewater treatment equipment at a second time after the first time, based on the second data and a prediction model for predicting the properties of the post-treatment wastewater; Here, the method for predicting the properties of treated wastewater is a model created by associating product production process data related to past product production in the product production process, operating condition parameters used to treat wastewater discharged by the wastewater treatment equipment during the past product production, and the properties of the treated wastewater.

6. 6. The method for predicting the properties of a post-treatment wastewater according to claim 5, The method further comprises a data reacquisition step and a post-treatment waste liquid predicted value re-output step, In the data reacquisition step, if the predicted value relating to the properties of the post-treatment wastewater outputted in the post-treatment wastewater predicted value output step does not fall within a predetermined range, an operating condition parameter to be executed by the wastewater treatment facility is reset, and the second data is acquired; A method for predicting the properties of post-treatment waste liquid, in which the post-treatment waste liquid predicted value re-output process re-outputs a predicted value regarding the properties of post-treatment waste liquid from the waste liquid treatment equipment at the second time based on the second data acquired in the data re-acquisition process and the prediction model that predicts the properties of the post-treatment waste liquid.

7. 6. The method for predicting the properties of a post-treatment wastewater according to claim 5, A method for predicting the properties of a post-treatment effluent, wherein the prediction model is configured to be updateable before the post-treatment effluent prediction value output step is executed.

8. 6. The method for predicting the properties of a post-treatment wastewater according to claim 5, The wastewater treatment facility performs biological treatment of the wastewater, The prediction model is a model created by further associating the temperature and / or temperature transition of the wastewater with the corresponding biological treatment capacity, A method for predicting the properties of treated effluent, wherein the second data acquired in the data acquisition step further includes information regarding the temperature and / or temperature transition of the effluent.

9. 6. The method for predicting the properties of a post-treatment wastewater according to claim 5, The method for predicting the properties of treated wastewater, wherein the data acquisition step is configured so that constraints can be set on some of the operating condition parameters that the wastewater treatment facility is to operate.

10. 6. The method for predicting the properties of a post-treatment wastewater according to claim 5, the prediction model is a model created by further associating predetermined parameters of a product produced in the product production process, A method for predicting properties of a treated effluent, wherein the second data acquired in the data acquisition step further includes information regarding a predetermined parameter of the product.

11. The method for predicting the properties of a post-treatment wastewater according to claim 10, A method for predicting the properties of post-treatment effluent, wherein the predetermined product parameter is information about the performance or quality of a product produced in the product production process.

12. An operation system for wastewater treatment equipment that treats wastewater from a product production process, The apparatus includes a data acquisition unit, a wastewater prediction value output unit, and an operating condition setting unit, the data acquisition unit acquires first data including product production process data in the product production process at a first time; wherein the product production process data includes data on the weight of the product to be produced, the wastewater prediction value output unit outputs a prediction value regarding the property of the wastewater from the product production process at a second time after the first time, based on the first data and a prediction model that predicts the property of the wastewater; wherein the prediction model is a model created by associating product production process data relating to past product production in the product production process with data relating to properties of waste liquid discharged during the past product production, The operating condition setting unit sets operating condition parameters for the waste liquid treatment facility based on the predicted value relating to the properties of the waste liquid output by the waste liquid predicted value output unit.

13. A prediction system for predicting the properties of wastewater after treatment at a wastewater treatment facility that treats wastewater from a product production process, A data acquisition unit and a post-treatment wastewater predicted value output unit are provided, the data acquisition unit acquires second data including product production process data in the product production process at a first time and operating condition parameters that the waste liquid treatment facility is to execute after the first time; wherein the product production process data includes data on the weight of the product to be produced, the post-treatment wastewater predicted value output unit outputs a predicted value regarding the properties of the post-treatment wastewater from the wastewater treatment equipment at a second time after the first time, based on the second data and a prediction model that predicts the properties of the post-treatment wastewater; Here, the prediction model is a model created by associating product production process data relating to past product production in the product production process, operating condition parameters when the waste liquid treatment equipment treated the waste liquid discharged during the past product production, and the properties of the treated waste liquid, in this prediction system.

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