Method for operating wastewater treatment equipment, method for predicting the properties of treated wastewater, 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 factory production processes, water is used for various purposes, such as dissolving raw materials, cleaning production lines, and cooling, and this water is usually subjected to specific treatment before being disposed of. However, the properties of the water to be treated change with changes in the raw materials used, the products produced, and production volume, so it may be necessary to devise measures for the wastewater treatment process.

[0003] A related technique is known, for example, from Patent Document 1. Patent Document 1 discloses a method for predicting a quantity to be monitored, which includes a primary prediction step of calculating a plurality of primary predicted values ​​of a quantity to be monitored of a plant facility using a plurality of different prediction models, operation record data of the plant facility, data related to the current operating status, meteorological observation data, and data related to weather forecasts, 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 quantity to be monitored of the plant facility as a predicted value of the quantity to be monitored of the plant facility using the plurality of weighted primary predicted values. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Japanese Patent Application Laid-Open No. 2013-161336 Summary of the Invention [Problem to be solved by the invention]

[0005] However, the inventors' investigations have 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 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 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; 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 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 properties of the waste liquid outputted in the waste liquid predicted value output step. (2) In the method for operating the waste liquid treatment equipment according to (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) In the method for operating the waste liquid treatment equipment according to (1) or (2), the prediction model is a model created by further associating predetermined parameters 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 treated wastewater from 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 properties 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 properties of the post-treatment wastewater; Here, the method for predicting the properties of treated wastewater is a model created by associating past product production process data in the product production process, data on the properties of the wastewater discharged at that time, operating condition parameters under which the wastewater treatment equipment treated the discharged wastewater at that time, and the properties of the treated wastewater. (5) (4) In the method for predicting the properties of a treated wastewater according to the present invention, 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, the operation condition parameters to be executed by the wastewater treatment facility are reset, and the second data is acquired; A method for predicting the properties of post-treatment wastewater, in which the post-treatment wastewater predicted value re-output process re-outputs a predicted value regarding the properties of post-treatment wastewater from the wastewater 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 post-treatment wastewater. (6) In the method for predicting the properties of a treated wastewater according to (4) or (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. (7) In the method for predicting the properties of a treated 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 corresponding biological treatment capacity, A method for predicting the properties of treated wastewater, wherein the second data acquired in the data acquisition step further includes information regarding the temperature and / or temperature transition of the wastewater. (8) In the method for predicting the properties of a treated 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 constraints can be set on some of the operating condition parameters that the wastewater treatment facility is to operate. (9) In the method for predicting the properties of a treated wastewater according to any one of (4) to (7), 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 the 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. (10) 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; the wastewater prediction value output unit outputs a prediction 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 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 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. (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, 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 that predicts 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 on 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 solely on the operating conditions of the wastewater treatment plant itself. In contrast, the method of operating a wastewater treatment facility of the present application utilizes data related to the product production process located upstream of wastewater generation, thereby optimizing 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 impact of waste liquid treatment equipment. Furthermore, even within the limited processing capacity of waste liquid treatment equipment, by adjusting parameters related to waste liquid treatment data linked to the product production process, it is possible to achieve the target waste liquid properties (wastewater quality standards, etc.) without making additional capital investments.

[0009] Therefore, it can be said that the above-described 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 explanation of the drawings]

[0010] [Figure 1] 1 is a diagram showing the overall configuration of an information processing system 100. FIG. [Figure 2] 1 is a diagram illustrating a hardware configuration of an information processing device 1. FIG. [Figure 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. [Figure 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 INVENTION

[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 medium, or may be provided so that it can be downloaded 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 also 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 types of information, which may be represented by, for example, physical values ​​of signal values ​​representing voltages and currents, 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 calculations 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, a memory, etc. That is, 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 a method for operating a waste liquid treatment facility that treats waste liquid from a product production process (sometimes simply referred to as an "operation method") and a 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 (sometimes simply referred to as a "prediction method"). 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 communication 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. In other words, 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 to be installed in plant PL2 can be set appropriately depending on the type of wastewater. For example, if the wastewater is aqueous, a biological treatment device or the like may be installed in plant PL2. Note that this biological treatment device may use microorganisms capable of purifying the wastewater. Although not shown in FIG. 1, a sensor may be attached to the liquid line LL1, and this sensor may be connected to the information processing device 1 via the communication line 2.

[0018] 2 is a diagram showing the 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 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 predetermined programs stored in the storage unit 12. In other words, information processing by software stored in the storage unit 12 is specifically realized by the control unit 11, which is an example of hardware, and can be 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 the device may be implemented with multiple control units 11 for each function. A combination of these may also be used.

[0020] (Storage unit 12) The memory unit 12 stores various pieces of information defined above. 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 operations. The memory 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. The touch panel allows the user to input tapping, swiping, and the like. Of course, a switch button, a mouse, a QWERTY keyboard, or the like may be used 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 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 graphical user interface (GUI) screen that can be operated by the user. This is preferably implemented by selectively using display devices such as a CRT display, a liquid crystal display, an organic EL display, and a plasma display depending on 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. Note that the communication unit 15 may have a network communication function, which allows various pieces of information to be communicated between the information processing device 1 and external devices via the communication line 2.

[0024] Furthermore, although not shown, the plants PL1 and 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 its functional units, a data acquisition unit 111, a liquid waste prediction value output unit 112, an operating condition setting unit 113, a post-treatment liquid waste prediction value output unit 114, a data reacquisition unit 115, a post-treatment liquid waste prediction value re-output unit 116, a prediction model creation unit 117, and a memory management unit 118. Note that these functional units may be increased or omitted as appropriate 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 the 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 equipment. 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] (Wastewater 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 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 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 waste liquid discharged at that time. Details of this information processing will be described later.

[0029] (Operating 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 for the wastewater treatment facility based on the predicted values ​​relating to the properties of the wastewater output by the wastewater predicted value output unit. When setting these operating conditions, the operating condition setting unit 113 is configured to transmit various information (signals, etc.) via the communication unit 15 to various devices typically arranged in the plant PL2.

[0030] (Post-treatment waste liquid predicted value output unit 114) The post-treatment wastewater predicted value output unit 114 is configured to be able to execute a post-treatment wastewater predicted value output step. In the post-treatment wastewater predicted value output step, the post-treatment wastewater predicted value output unit 114 outputs a predicted value regarding the properties of post-treatment wastewater from the wastewater treatment equipment at a second time period after the first time period, 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 past product production process data in the product production process, data regarding the properties of the wastewater discharged at that time, operating condition parameters used when the wastewater treatment equipment treated the discharged wastewater at that time, and the properties of the post-treatment wastewater. 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 output 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. Specific aspects will be described later.

[0032] (Post-treatment waste liquid 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 a second time based on the second data acquired in the data re-acquisition step and a prediction model that predicts 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 which the prediction model creation unit 117 creates or updates a prediction model used in the aforementioned effluent prediction value output step, post-treatment effluent prediction value output step, etc.

[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 to the information processing device 1 from the plant PL1 or the plant PL2 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 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 and the like will be described with reference to an activity diagram and the like.

[0036] (Applicable to) First, we will explain the application of the information processing device 1 of this embodiment. 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 a waste liquid treatment facility, and the type of waste liquid here can be set appropriately. In other words, the waste liquid supplied from the product production process may be either water-based or oil-based depending on the type of the product production process. In other words, the plant PL1 that executes the product production process in this embodiment is not limited to a specific product item, and may be any of a variety of well-known plants, such as a paper plant, steel plant, power plant, petroleum plant, or chemical plant. Below, we will explain the flow of information processing for a method of operating a wastewater treatment facility and a method of predicting the amount of wastewater after treatment at the wastewater treatment facility, assuming that the wastewater from the 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 acquisition 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 a product, this activity is achieved by the data acquisition unit 111 acquiring the weight of the produced product as at least a part of the first data. The data (data group) constituting the first data may be quantitative or qualitative. When qualitative parameters are used, they may be assigned numerical values ​​and treated as quantitative data.

[0041] Regarding such product production process data, specific examples of various parameters in a papermaking process that uses 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, oxidation-reduction potential, zeta potential, turbidity, temperature, bubble height, biochemical oxygen demand (BOD), chemical oxygen demand (COD) (e.g., COD Mn , COD Cr )), absorbance (e.g., UV absorbance), color (e.g., RGB value), residual chemical concentration, particle size distribution, degree of aggregation, amount of foreign matter, foam area on the water surface, area of ​​dirt 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, cation demand, amount of hydrogen sulfide, amount of hydrogen peroxide, and respiration rate of microorganisms in the system.

[0043] Control parameters include, for example, the operating speed (machine 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 aqueous system, the amount of chemicals added to the raw material added to the aqueous system, the amount of chemicals added to equipment related to the aqueous 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 amount of broken paper blended 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. Incidentally, "equipment related to the aqueous system" includes, for example, equipment such as the wires and felt of the papermaking machine to which chemicals are directly added.

[0044] Examples of 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, and 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 predetermined parameters of the product. Here, the predetermined parameters of the product are typically analytical values ​​related to the product, such as the workmanship and quality of the product (product purity, impurities contained, analytical values ​​obtained by equipment, etc.). Such predetermined parameters of the product can be acquired from various sensors arranged in the plant PL1 via the communication unit 15, or can 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 explained. Examples of predetermined parameters for 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, type 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 that process. Here, this prediction 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 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 predictive model, the relationship between past product production process data in the product production process and data on the properties of the wastewater discharged during the process can be analyzed using known analytical methods. Typically, a desired predictive model can be obtained by analysis using regression analysis methods (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.), Bayesian (naive Bayes, etc.), clustering (k-means, k-means++, etc.), ensemble learning (Boosting, Adaboost, etc.), etc. Note that, although the prediction model is created by the prediction model creation unit 117 in this example, the present invention is not necessarily limited to this. 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, thereby performing the operating method of this embodiment. Furthermore, the prediction model may be a model configured to be updatable before the wastewater prediction 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, although this prediction model outputs a predicted value regarding the properties of the wastewater at a second time after the first time, 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 accuracy of the prediction. 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 wastewater associated in the prediction model can be set as appropriate, but if the wastewater is aqueous, the various water quality parameters mentioned above can be used.

[0052] The prediction model may be a model created by further associating predetermined parameters of the 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 during the process, a prediction model may be created by further associating predetermined parameters of the product produced in the product production process. When the first data acquired by the data acquisition unit 111 includes predetermined parameters of the product, applying a prediction model associated with the predetermined parameters 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 for the wastewater treatment facility are set based on the predicted values ​​relating to the properties of the wastewater output 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.) to various devices located in the plant PL2 via the communication unit 15. More specifically, the operating condition setting unit 113 sets conditions for the wastewater properties so that they are at a level that allows them to be discharged from plant PL2, and controls plant PL2 to operate under those conditions. For example, if the pH of the wastewater supplied from plant PL1 is predicted to be different from normal, the amount of neutralizing agent used in plant PL2 can be adjusted to be optimal. Similarly, if the chemical oxygen demand (COD) value of the wastewater supplied from plant PL1 is predicted to be 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 plant PL2 to appropriate ranges. In addition, the operating condition setting unit 113 can set various conditions within plant PL2, such as the treatment temperature condition, humidity condition within the plant, and agitation condition of the agitation 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 undergoing a final inspection of the water quality, etc.

[0056] (Information processing flow (method for 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 description of the driving method described above 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 that the waste liquid treatment equipment is to execute (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 therefore a description thereof will be omitted here.Furthermore, 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 therefore a description thereof will be omitted here.

[0059] In the prediction method of this embodiment, the data acquisition unit 111 may be configured to set constraints on some of the operating condition parameters to be executed by the wastewater treatment facility. To explain this with a typical example, these constraints include the operating limits of the wastewater treatment facility, costs, and environmental load constraints. The prediction method of this embodiment can propose optimal treatment specifications even when certain constraints are imposed. Specifically, when setting operating condition parameters to match the target values, constraints are set, 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, and optimal operating conditions can be proposed within the range of these constraints.

[0060] The second data may further include information about predetermined parameters of the product. The predetermined parameters of the product that may be included in the second data may be the same as the predetermined parameters of the product in the above-mentioned prediction method, and therefore will not be described here.

[0061] The second data may further include information on the temperature of the wastewater and / or its transition over time. 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; details of this process will be explained later.

[0062] In the prediction method of this embodiment, after acquiring the second data in this manner, the post-treatment wastewater predicted value output unit 114 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 (activity A202).

[0063] In this activity, the prediction 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 under which the waste liquid treatment equipment treated the discharged waste liquid at that time, and the properties of the treated waste liquid.

[0064] Regarding the differences from the above-mentioned operating method, the predictive model used in this embodiment is characterized in that it associates past product production process data in the product production process with data on the properties of the waste liquid discharged at that time, as well as operating condition parameters under which the waste liquid treatment equipment treated the discharged waste liquid with the properties of the treated waste liquid.

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

[0066] Furthermore, similar to the above-described operating method, the model may be created by further associating predetermined parameters of the product produced in the product production process, which makes it easier to predict the properties of the post-treatment wastewater with higher accuracy.

[0067] Furthermore, this prediction model may be a model 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 wastewater temperature and / or temperature trends, use of such a prediction model makes it possible to make predictions that take into account seasonal changes in biological treatment capacity. In a typical example, in the summer, an increase in wastewater temperature (particularly water temperature) can lead to insufficient operation of a biological treatment device. At this time, optimal operating condition parameters for the biological treatment device can be set by taking into account the trends in wastewater temperature (particularly water temperature) and the operating conditions of the temperature control equipment before and after the treatment. The wastewater (wastewater) temperature data associated with the prediction model may be based on the temperature of the wastewater in plants PL1 and / or PL2, the temperature of the wastewater in the biological treatment device (and in the processes before and after), or meteorological data.

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

[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 if the predicted value regarding the properties of the post-treatment waste liquid output in the post-treatment waste liquid predicted value output step does not fall within a predetermined range (this step may be referred to as a "data reacquisition step"). Also, the post-treatment waste liquid predicted value re-output unit 116 may be configured to re-output a predicted value regarding the properties of the post-treatment waste liquid from the waste liquid treatment facility at a second time based on the second data acquired in the data re-acquisition step and a prediction model that predicts the properties of the post-treatment waste liquid (this step may be referred to as a "post-treatment waste liquid predicted value re-output step").

[0070] As shown in the activity diagram of Fig. 5, when a predicted value of the treated liquid waste is 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 liquid waste into a river, etc.), the system can be configured to acquire second data again. In other words, the system can be configured to perform an operation similar to the above-mentioned activity A201, but for convenience, this operation will be referred to as a "data re-acquisition process" in this specification. As mentioned above, the predicted post-processing wastewater value can be output based on the second data acquired in the data re-acquisition process, and this process can be repeated until the managed parameters fall within a specified range. Typically, this data reacquisition step can be performed while changing the operating condition parameters for the wastewater treatment. That is, repeating the data reacquisition step until the managed parameters fall within a predetermined range has the effect of essentially optimizing the operating condition parameters for the wastewater 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, this embodiment provides a method for operating a wastewater treatment facility that can flexibly respond to changes in the properties of wastewater. This embodiment reduces the investment required for wastewater treatment facilities and is expected to have other effects, such as reducing the environmental impact.

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

[0074] The above embodiment has been described as a configuration of the information processing device 1, but a program that causes a computer to function as each part of the information processing device may be provided.

[0075] In the above-described embodiment, the information processing device 1 is applied to plants PL1 and PL2 connected by a liquid line LL1, but the two plants do not necessarily need to be connected by the liquid line LL1, and it is also possible to adopt a configuration in which waste liquid is transported from plant PL1 to plant PL2 using a rotary or the like. 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-described embodiment, an operation method and a prediction method using a prediction model are described, but the information associated with creating the prediction model is not limited to the above. That is, the prediction model used in this 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, while various embodiments of the present invention have been described, these are presented by way of example only and are not intended to limit the scope of the invention. The novel embodiments may be embodied in various other forms, and various omissions, substitutions, and modifications may be made without departing from the spirit of the invention. Such embodiments and modifications are intended to be included within the scope and spirit of the invention, as well as within the scope of the inventions and their equivalents as defined in the accompanying claims. [Explanation of symbols]

[0078] 1: Information processing equipment 2: Communication line 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 unit 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 that treats wastewater from a product production process that does not fall under the category of wastewater generated by treating exhaust gas, 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 is acquired, the first data including product production process data in the product production process at a first time and information on a predetermined parameter of a product related to the product production process; the wastewater predicted value output step includes outputting 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, predetermined parameters of a product produced in the product production process during the past product production, and data relating to the 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 method for operating a waste liquid treatment facility, wherein the waste liquid from the product production process is wastewater used for dissolving raw materials, cleaning a production line, or cooling the product production process.

4. A method for predicting the properties of treated wastewater from a wastewater treatment facility that treats wastewater from a product production process that does not fall under the category of wastewater generated by treating exhaust gas, comprising: The method includes a data acquisition step and a post-treatment wastewater predicted value output step, In the data acquisition step, second data is acquired, the second data including product production process data in the product production process at a first time, information on predetermined parameters of a product related to the product production process, and operating condition parameters that the waste liquid treatment facility is to execute after the first time; 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, predetermined parameters of the product produced in the product production process during the past product production, operating condition parameters under which the wastewater treatment equipment treated the wastewater discharged during the past product production, and the properties of the treated wastewater.

5. 5. The method for predicting the properties of a post-treatment wastewater according to claim 4, 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.

6. 5. The method for predicting the properties of a post-treatment wastewater according to claim 4, 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.

7. 5. The method for predicting the properties of a post-treatment wastewater according to claim 4, 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.

8. 5. The method for predicting the properties of a post-treatment wastewater according to claim 4, 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.

9. 5. The method for predicting the properties of a post-treatment wastewater according to claim 4, The method for predicting the properties of treated wastewater, wherein the wastewater from the product production process is wastewater used for dissolving raw materials, cleaning a production line, or cooling the product production process.

10. An operation system for wastewater treatment equipment that treats wastewater from a product production process that does not fall under the category of wastewater generated by treating exhaust gas, 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 and information on a predetermined parameter of a product related to the product production process; 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, predetermined parameters of a product produced in the product production process during the past product production, and data relating to the 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.

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 that does not fall under the category of wastewater generated by treating exhaust gas, 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 for the product production process at a first time, information on predetermined parameters of a product related to the product production process, and operating condition parameters that the waste liquid treatment facility is to execute after the first time; 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, predetermined parameters of the product produced in the product production process during the past product production, operating condition parameters when the waste liquid treatment equipment treated the waste liquid discharged during the past product production, and properties of the treated waste liquid.

Images