Operation work assisting system, operation work assisting method and assisting program

Abstract

To provide an operation work assisting system that automatically presents, from the past operation state similar to the present operation state, optimal operation information.SOLUTION: An operation work assisting system according to the present invention includes: a work information inputting unit 31 that inputs work information and an event name representing the details of the work information in a manner associated with the date and time at which a work occurs; an operation data obtaining unit 35 that obtains operation data on a plant; an event determining unit 33 which searches for a past actual record similar to the present state of the plant obtained by the operation data obtaining unit, and which determines, when the event name is set at the date and time at which the searched similar past actual record occurred, an event that needs countermeasures has occurred or not based on the event name; and a countermeasure information presenting unit 34 that presents, when the event determining unit determines that an event needing countermeasures has occurred, countermeasure information that includes the work information at the date and time at which the event name occurs, and the event name.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The present invention relates to an operation support system, an operation support method, and an operation support program for water supply and sewage plants, chemical plants, electric power plants, and waste treatment plants. [Background technology]

[0002] In recent years, water supply and sewage plants have been consolidating and relocating facilities to address issues such as declining demand due to population decline, aging facilities, and labor shortages. In particular, in the water supply sector, the Water Supply Act was revised in 2018. The revised Water Supply Act states that water suppliers are obligated to make an effort to systematically update water facilities from a long-term perspective, and clarifies the importance of consolidating and relocating facilities.

[0003] In the operation and maintenance of water supply and sewage plants, there are times when management relies on the visual inspection and experience of the operators. On the other hand, in order to streamline personnel allocation, consolidation and relocation of facilities is being promoted, and a shift to a centralized monitoring system from an integrated base is being made. It is expected that the number of business entities switching to a centralized monitoring system from an integrated base will increase in the future, but as a result of personnel reallocation, there are concerns that the workload per operator will increase and that the judgment of operators will decrease due to the management of facilities by inexperienced operators. In addition, as the number of experienced operators decreases, it is becoming more difficult for inexperienced operators to accumulate and pass on know-how and technology.

[0004] Methods for accumulating and passing on know-how and technology include on-the-job training (OJT) at the site and creating and reading manuals. In recent years, created manuals are often stored electronically. Manuals also use photographs and videos in addition to documents to visually organize information in an easy-to-understand manner. However, traditional methods require manpower and time to accumulate and pass on know-how and technology, and in plants managed by a small number of people, there is no room to work on accumulating and passing on know-how and technology other than the main maintenance work. In other words, OJT and the creation of manuals are often not possible.

[0005] Even if the know-how and technical information of events that require some kind of countermeasure for plant operation can be organized and compiled as a manual, it may not be possible to quickly search for past countermeasure information when an unexpected event occurs, and it may not be used effectively.In addition, if time has passed since the start of maintenance work or when facilities are newly constructed or updated, the countermeasure information may not be updated and may no longer be effective.

[0006] For this reason, various methods for accumulating and passing on know-how and technology have been proposed. For example, Patent Document 1 describes a "technical succession support method and system that stores various management data, alarm history information output when water quality management standards are deviated, and operation / driving history information (process) data, displays various know-how information input by operators for the stored water quality data, alarm output history, and process data in chronological order on a screen, discloses information to workers in the water purification plant, passes on know-how, and prepares new effective management and operation manuals based on quantitatively evaluated know-how information." [Prior art documents] [Patent documents]

[0007] [Patent Document 1] JP 2012-118830 A Summary of the Invention [Problem to be solved by the invention]

[0008] According to the above prior art, operation history, process data, alarm occurrence date and time, and alarm content are recorded in the history / process database, and the system diagnoses whether the process data is within a preset reference value, and records the alarm output date and time and alarm content when process data that is outside the reference value range is detected. These reference values ​​include upper and lower limits of data, correlation analysis values, statistical analysis values, etc., and these values ​​must be input in advance.

[0009] During operation, the prepared manual is presented by determining whether the value falls within the range of the reference value, so there is a possibility that the manual cannot be presented if the condition is not met. In addition, in Patent Document 1, in order to apply a text mining method to extract know-how, there are rules (5W1H) defined for the method of inputting know-how, which may make the input work of the operator cumbersome.

[0010] An object of the present invention is to provide a driving operation support system etc. that automatically presents optimal driving information based on past driving states similar to the current driving state. [Means for solving the problem]

[0011] In order to solve the above problems, the operation operation support system of the present invention includes a business information input unit that inputs business information and an event name indicating the content of the business information in association with the date and time when the business occurred; an operation data acquisition unit that acquires operation data of the plant; an event determination unit that searches for past records similar to the current state of the plant acquired by the operation data acquisition unit, and, when an event name is set on the date and time when the searched similar past record occurred, determines whether an event requiring countermeasures has occurred based on the event name; and a countermeasure information presentation unit that, when the event determination unit determines that an event requiring countermeasures has occurred, presents the business information of the date and time when the event name occurred and the event name as countermeasure information. Effect of the Invention

[0012] According to the present invention, it is possible to provide a driving operation support system that automatically presents optimal driving information based on past driving states similar to the current driving state. [Brief description of the drawings]

[0013] [Figure 1] 1 is a configuration diagram of a driving operation support system according to an embodiment. [Diagram 2] FIG. 1 is a graph showing the change in turbidity of treated water when a flocculant is added to counter an increase in turbidity of the treated water due to rainfall. [Diagram 3]FIG. 13 is a diagram showing the change in the coagulant injection rate when a coagulant is added to counter an increase in turbidity in the water to be treated due to rainfall. [Figure 4] FIG. 11 is a process flow diagram of an event determination unit. [Diagram 5] FIG. 11 is a diagram showing an example of a search for transition of the turbidity of the water to be treated in step S2. [Figure 6] 13 is a diagram showing an example of information acquired by an event determination unit and displayed by a countermeasure information presentation unit; FIG. [Figure 7] FIG. 13 is a process flow diagram of a business information input unit. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0014] Hereinafter, a driving operation support system according to an embodiment of the present invention will be described in detail with reference to the drawings. FIG. 1 is a configuration diagram of a driving operation support system according to an embodiment.

[0015] The operation operation support system comprises an operation operation support device 10 that presents operation information, an information input device 40 into which the operator inputs work information, etc., an information output device 50 that presents the operation information obtained by the operation operation support device 10 to the operator, and a network 60 that connects the operation operation support device 10 to multiple plants to be maintained.

[0016] Although details will be described later, the operation operation support device 10 is composed of an information storage unit 20 having a business information storage unit 21 that stores the response details of operators (daily reports, handover information, etc.), a process operation data storage unit 22, an alarm storage unit 23, an operation log storage unit 24, and an event storage unit 25 that determines whether or not countermeasures are necessary, and an operation support unit 30 having an operation data acquisition unit 35, a business information input unit 31, a countermeasure evaluation setting unit 32, an event determination unit 33, and a countermeasure information presentation unit 34.

[0017] Specifically, the driving operation support device 10 is configured with a computer (information processing device) having storage means such as a CPU, memory, and hard disk, not shown, and an interface such as a network, and the CPU executes a program stored in the storage device to realize the functions of the operation support unit 30. The storage unit also constitutes an information accumulation unit 20.

[0018] The information input device 40 is not particularly limited as long as it is an interface that can input necessary information, such as a keyboard, a mouse, an audio microphone, etc. The information output device 50 is a display device, and may be capable of outputting audio. The network 60 may be a wireless LAN, a wired LAN, or other communication means, and is not particularly limited.

[0019] In addition, the driving operation support device 10 can be configured by a computer (information processing device) having an interface such as a network. It does not have to be installed on the plant premises, but may be installed away from the plant.

[0020] Here, a water purification plant, which is an example of a plant that is a target of support by the operation support system of the embodiment, will be described.

[0021] A water purification plant is a facility that purifies river water, dam water, or groundwater and sends the treated water to factories, homes, etc., and is composed of multiple pieces of equipment, such as a receiving well, a rapid mixing basin, a flocculation basin, a sedimentation basin, a filtration basin, a disinfection basin, and a distribution reservoir, which remove turbidity from the treated water and sterilize it.

[0022] The process of removing turbidity is called coagulation and sedimentation. In typical water purification plants, coagulation and sedimentation is carried out by injecting chemicals called coagulants, such as polyaluminum chloride or aluminum sulfate, into the water being treated that has flowed into the plant. One of the purposes of injecting chemicals is to remove insoluble substances suspended in the water (hereafter referred to as turbid matter). Turbid matter is negatively charged in the water, but adding chemicals makes it possible to electrically neutralize it. Another purpose of injecting chemicals is to facilitate coagulation when neutralized turbid matter collides with each other due to the bridging action of the chemicals.

[0023] In the rapid mixing basin, chemicals are injected into the water being treated, and rapid mixing causes the suspended solids to collide with each other, forming coagulation nuclei. Next, in the flocculation basin, flocs (fine dust or debris in the water that has formed clumps) are grown by slow mixing at a strength that does not destroy them. In the settling basin, the grown flocs are then settled and removed.

[0024] In coagulation and sedimentation treatment, as the amount of chemical injected increases, the bridging action becomes stronger, causing flocs to grow faster and resulting in a good coagulation state (reduced turbidity in the treated water). However, if the amount of chemical injected is excessive, the turbid matter will become positively charged, which may result in a poor coagulation state (increased turbidity in the treated water). The more turbidity in the water (turbidity of the treated water) increases, the more likely it is that the turbid matter (or coagulation nuclei, flocs) will collide with each other, causing flocs to grow faster. Thus, floc growth, which is one of the factors in the floc coagulation mechanism, is affected by plant operating conditions such as the amount of chemical injected and water quality conditions.

[0025] Although the flocculation mechanism is common to all water purification plants, the structure and scale of the facilities differ from plant to plant, and so does the growth of flocs. For example, there are differences in the capacity of the settling tank and the presence or absence of an inclined plate from plant to plant.

[0026] More specifically, the retention time of the water in the settling tank is determined by the amount of water to be treated and the capacity of the settling tank, but the longer the retention time, the easier it is for even small flocs to settle, and the more the flocs are removed from the water to be treated. Also, when there is an inclined plate, even with the same amount of water to be treated and the capacity of the settling tank, more flocs are removed from the water to be treated than when there is no inclined plate. In the rapid mixing tank, the coagulant is mixed using a stirring device, but the uniformity of mixing changes depending on the shape of the rapid mixing tank, which affects the subsequent growth of flocs.

[0027] In addition, because the source of the water to be treated differs for each water purification plant, the water quality also differs from plant to plant. For this reason, the amount of chemicals injected (control value) and other operational procedures differ from plant to plant. Furthermore, even within a single water purification plant, the amount and content of operational procedures may change due to long-term changes such as changes in water demand and aging facilities, or short-term changes such as construction work on facilities within the water purification plant.

[0028] When an operator is an experienced person, he or she can respond to changes in the situation within the water purification plant using their past knowledge, but when managing a facility with an inexperienced operator, it may be difficult for the operator to respond. The operation work support system of the embodiment presents optimal operation information and supports smooth operation of the water purification plant. The configuration of the driving operation support device 10 will be described in detail below.

[0029] The task information storage unit 21 of the information storage unit 20 is linked to the date and time when the task occurred, and stores task information when the operator takes over (a series of actions taken by the operator when taking some kind of countermeasure, minutes of discussions regarding the actions, reasons, the operator's subjective opinion, etc.). Specifically, daily reports input by the operator every day using the information input device 40 are acquired via the task information input unit 31, which will be described later, and stored.

[0030] The operation data accumulation unit 22 stores past measurement data obtained from sensors and the like installed in the plant as operation data. In detail, the operation data includes data acquired by a group of sensors (not shown) installed in the plant that measure water quality items related to water treatment, operation parameters of equipment, and the like.

[0031] Specifically, sensors installed in a water purification plant include sensors that can measure water quality items that affect water treatment, such as a turbidity meter (for water to be treated and water to be treated) that measures the turbidity of water, a water thermometer that measures water temperature, a pH meter that measures pH, an alkalinity meter that measures alkalinity, a TOC meter that measures organic matter in water, and an ultraviolet absorptiometer. Other sensors include a water flow meter that measures the amount of water being treated. The operating data acquired from these sensors is accumulated in the operating data accumulation unit 220 as time-series information.

[0032] The alarm accumulation unit 23 stores past alarm data issued in the plant as time-series information. The alarm data includes alarm data when the value of an operation parameter set in advance in the plant exceeds a threshold value, such as an upper limit abnormality in the turbidity of the treated water, equipment failure such as a pump stoppage, and power supply abnormality.

[0033] The operation log storage unit 24 stores operation history data of the plant operated by the operator as time-series information. Here, the operation history data is data of operation operations that are automatically recorded, unlike the business information inputted by the information input device 40, such as the amount of chemical injection (control value) and the change in the water intake flow rate (change in the valve opening) that the operator manually changes.

[0034] The event storage unit 25 stores, as time-series information, the event name indicating whether or not an event occurred that requires some kind of countermeasure regarding the operation of the plant. This event name indicates the event that occurred, such as "treated water quality abnormality" or "pump stop." When an operator inputs handover information (task information) from the information input device 400, if the event involved some kind of countermeasure, the event name is input together with the handover information (task information).

[0035] Next, the details of the business support unit 30 will be described. The task information input unit 31 is a processing unit that stores task information (such as a series of responses made by the operator when taking some kind of countermeasure, minutes of discussion regarding the response, reasons, and the operator's subjective opinion) inputted by the information input device 40 when the operator takes over, the date and time of the task, and an event name indicating task information related to the operation of the plant, in the task information accumulation unit 21 and the event accumulation unit 25. The event name is a name that can be used to determine whether or not an event that requires some kind of countermeasure has occurred regarding the operation of the plant.

[0036] In detail, the task information input unit 31 links the task information when the operator takes over with the date and time of the task occurrence, and stores the linked information in the task information accumulation unit 21. By linking the task information and the event name with the date and time of the task occurrence, when searching for a situation similar to the current situation in the event determination unit 33 described later, it becomes possible to automatically search for and present task information based on the date and time of the similar situation.

[0037] Furthermore, the business information itself includes records of daily maintenance work, and does not distinguish whether the information is important or not, and whether it should be presented when an event occurs that requires some kind of countermeasure in relation to the operation of the plant. For this reason, when inputting business information, the business information input unit 31 inputs the event name that determines whether an event that requires some kind of countermeasure has occurred, and the date and time when the countermeasure started and ended. By linking the event name with the business information, when business information is searched for based on the date and time of a similar situation, it becomes possible to determine whether an event that requires some kind of countermeasure is occurring in a similar situation.

[0038] The countermeasure evaluation setting unit 32 is a processing unit that evaluates the results of responding to an event that requires some kind of countermeasure regarding the operation of the plant.

[0039] The following describes an example of changing the coagulant injection rate as a measure. Water purification plants take in water to be treated from rivers, etc., but the quality of the water to be treated from rivers, etc. is greatly affected by natural phenomena such as rainfall. For example, when heavy rain falls due to a typhoon, etc., the suspended insoluble substances in the water to be treated, that is, the turbidity, increases significantly in a short period of time. In such cases, the amount of coagulant added is increased, but the timing of the increase and the amount of increase at one time often differ depending on the individual operator and the situation. As a result, even if the trend (tendency fluctuation) of the turbidity of the water to be treated remains the same, the amount of coagulant added and the trend of the turbidity of the treated water will change. Therefore, a quantitative evaluation is performed on the corresponding results. Here, the KPIs (indicators) for the quantitative evaluation include water quality and quantity, cost, labor, and number of alarms.

[0040] An example of the evaluation of measures related to water quality and quantity in the measures evaluation setting unit 32 will be described with reference to Fig. 2. Fig. 2 is a diagram showing the change in treated water turbidity (trends 1 and 2) when a flocculant is added to deal with an increase in turbidity of the treated water due to rainfall. The horizontal axis of Fig. 2 is date and time, and the vertical axis is the turbidity of the treated water (treated water turbidity). The treated water turbidity is an actual measurement value of the plant, and is acquired from the plant by the operation data acquisition unit 35 via the network 60.

[0041] From the perspective of water quality, a measure is considered highly rated if it does not deviate from the target value previously set at the water purification plant (in the case of Figure 2, the target value is 0.8 degrees). The countermeasure evaluation setting unit 32 evaluates countermeasures from the viewpoint of water quality in the treated water turbidity trends 1 and 2 as shown in FIG. 2 as follows.

[0042] As shown in formula (1), the countermeasure evaluation setting unit 32 takes the absolute value of the difference between the plant's actual measured value and the target value for the interval including the start and end dates and times of the countermeasures inputted in the work information input unit 31, and then calculates the average value by adding up the absolute values ​​of the differences and dividing it by the score for the interval to set the KPI for water quality and quantity. Here, k is data for a certain period within the start and end dates and times of the countermeasures, zero is the first data in the interval, and l is the last data in the interval.

number

[0043] In the above, the KPI was the average value of the difference between the actual measurement and the target value of the turbidity of the treated water when a coagulant was added to counter the increase in turbidity of the treated water due to rainfall, but the KPIs for water quality and quantity change depending on the event that occurs. When the KPIs are calculated from trends 1 and 2 of the treated water turbidity shown in Figure 2, they are 0.07 degrees and 0.18 degrees, respectively, and from the viewpoint of water quality, trend 1, which has a smaller average value, is evaluated as high.

[0044] Next, an example of cost-related countermeasure evaluation in the countermeasure evaluation setting unit 32 will be described with reference to Fig. 3. Fig. 3 is a diagram showing changes in the flocculant injection rate (trends 1 and 2) when a flocculant is added as a countermeasure against an increase in turbidity in the treated water due to rainfall. The horizontal axis of Fig. 3 is date and time, and the vertical axis is the amount of flocculant added (flocculant injection rate). The flocculant injection rate is an actual measurement value of the plant, and is acquired by the operation data acquisition unit 35 from the plant via the network 60.

[0045] From a cost perspective, a measure is highly evaluated when it can be implemented without increasing the coagulant injection rate in response to the event that has occurred. The countermeasure evaluation setting unit 32 evaluates countermeasures from the viewpoint of cost in trends 1 and 2 of the coagulant injection rate as shown in FIG. 3 as follows.

[0046] As shown in formula (2), the countermeasure evaluation setting unit 32 takes the start and end dates and times of the countermeasure inputted in the work information input unit 310 as an interval, calculates the difference between the coagulant injection rate before the countermeasure started and the coagulant injection rate during the countermeasure, then sums up the differences and divides them by the score for the interval to calculate an average value as the (chemical) cost KPI. Here, k is data for a certain period within the start and end dates and times of the countermeasure, zero is the first data in the interval, and l is the last data in the interval.

number

[0047] In the above, the KPI was the average value of the difference between the coagulant injection rate before the start of countermeasures and the coagulant injection rate during countermeasures. However, the KPI can also be converted into a monetary value by multiplying the total value before calculating the average by the volume of treated water and the price of the coagulant (yen / kg), and is not particularly limited as long as it is possible to distinguish the difference in cost.

[0048] When the KPIs are calculated from trends 1 and 2 of the coagulant injection rate shown in Fig. 3, they are 17.4 mg / L and 17.0 mg / L, respectively. From the perspective of cost, trend 2, which shows a smaller increase in the coagulant injection rate during the countermeasures compared to the coagulant injection rate before the countermeasures were started, is highly evaluated.

[0049] In the above, the cost-related evaluation of measures in the measures evaluation setting unit 32 has been described, but evaluation may be made in terms of man-hours instead of costs. For example, in Fig. 3, the coagulant injection rate is changed twice in trend 1 and three times in trend 2 in the period before and after the measures, and the operation frequency per hour can be calculated by dividing the change by the time required to start and finish the measures. If the time required to start and finish the measures is 10 hours, comparing trends 1 and 2 in Fig. 2 in terms of man-hours, the operation frequency of trend 1 is 0.2, which is lower than trend 2's 0.3, and is therefore highly evaluated.

[0050] Also, a countermeasure that generates a smaller number of alarms in a section before and after the countermeasure may be given a higher rating in order to determine which countermeasure should be taken. In the above, the countermeasure evaluation setting unit 32 sets the KPIs as water quality / quantity, cost, labor, and number of alarms, but as long as the merits and demerits of the countermeasures can be evaluated, the KPIs are not limited to those exemplified above, and are not particularly limited.

[0051] Returning to FIG. 1, the event determination unit 33 will be described. The event determination unit 33 is a processing unit that searches for similar past results stored in the operation data storage unit 22 based on the current status of the plant acquired by the operation data acquisition unit 35 via the network 60, and determines that an event requiring some kind of action has occurred when an event name is set in the task information of the occurrence date and time of the past result in the task information storage unit 21 that corresponds to the searched similar past result. In more detail, it refers to the event storage unit 25 and acquires the event name of the occurrence date and time of the past result.

[0052] The event determination unit 33 determines whether the current situation corresponds to an event name indicating the occurrence of an event requiring countermeasures stored in the event storage unit 25, and therefore the countermeasures taken by the experienced operator who stored the event name can be known, and optimal operation information can be obtained. Details of the event determination unit 33 will be described later with reference to FIG. 4.

[0053] 1 is a processing unit that displays the information acquired by the event determination unit 33 on the information output device 50 and presents it to the operator. The displayed contents will be described later with reference to FIG.

[0054] Next, the function of the event determination unit 33 in FIG. 1 will be described with reference to FIG. FIG. 4 is a process flow diagram of the event determination unit 33.

[0055] In step S1, the event determination unit 33 acquires current operation data such as water quality and quantity from the plant via the network 60 using the operation data acquisition unit 35, and also acquires past operation data such as water quality and quantity from the operation data storage unit 22.

[0056] In step S2, the event determination unit 33 determines the increase in turbidity of the treated water due to rainfall in the current operating data acquired in step S1 as the current situation, and searches for past trends in the turbidity of the treated water that are similar to the current trend in the turbidity of the treated water in the past operating data acquired in step S1.

[0057] In detail, the event determination unit 33 calculates the similarity between the current turbidity trend of the water to be treated and the past turbidity trend of the water to be treated by using a method such as comparing Euclidean distances, as shown in formula (3), and finds trends whose similarity is within a predetermined value, where An is the value of the n-th trend A, Bn is the value of the n-th trend B, and x is the score used to calculate the similarity.

number

[0058] This allows the event determination unit 33 to know at what point in the past the trend being searched for (the transition in the turbidity of the water to be treated) occurred. In addition, by determining a trend slightly ahead of the trend being searched for, it becomes possible to predict changes in the trend that may occur in the future.

[0059] Fig. 5 is a diagram showing an example of searching for the transition of the turbidity of the water to be treated in step S2. The horizontal axis of Fig. 5 is time, and the vertical axis is the turbidity of the water to be treated. When trend A is the current transition of the turbidity of the water to be treated and the zero point is the current date and time, the similarity is calculated using formula (3) for a total of six points from the zero point minus five hours while shifting the past transition of the turbidity of the water to be treated, for example, trend B, to search for past results with small similarity, i.e., similar results. Here, a total of six points every hour are used to calculate the similarity, but the number of points and time intervals are not particularly limited as long as the transition of the turbidity of the water to be treated can be known.

[0060] Returning to Figure 4, in step S3, the event determination unit 33 uses the date and time when a past trend in the turbidity of the treated water (past performance) occurred that is similar to the current trend in the turbidity of the treated water searched for in step S2, to obtain an event name for the corresponding date and time from the event accumulation unit 25 (an event name indicating whether or not an event occurred that requires some kind of action regarding the operation of the plant).

[0061] In this case, the number of similar past results does not have to be one, and multiple results may be selected in ascending order of similarity, or a threshold value for similarity may be set in advance and information on the relevant date and time of similar past results that are equal to or less than the threshold may be obtained. The following explanation will be given for the case where two or more similar past results are targeted.

[0062] If there is no similar past record, past operation data such as water quality and quantity of other plants may be obtained from the operation data accumulation unit 22 to search for similar past records.

[0063] In step S4, the event determination unit 33 determines whether the event name for the relevant date and time acquired in step S3 is an event name indicating whether an event requiring some kind of countermeasure has occurred regarding the operation of the plant, and judges whether an event requiring some kind of countermeasure has occurred. If an event requiring some kind of countermeasure has occurred, the process proceeds to step S5, and if not, the process proceeds to step S6.

[0064] In step S5, based on the date and time at which it was determined in step S4 that an event requiring some kind of countermeasure had occurred, the event determination unit 33 acquires information on the relevant date and time from the task information accumulation unit 21, the alarm accumulation unit 23, and the operation log accumulation unit 24. The acquired information is notified to the information output device 50 by the countermeasure information presentation unit 340 as countermeasure information, and is presented to the operator.

[0065] In step S6, the event determination unit 33 determines whether there are other similar past results for which steps S4 and S5 have not been performed, for the similar past results acquired in step S3, and if there are other similar past results (Yes in S3), the process returns to step S4. If there are no other similar past results (No in S3), the process ends.

[0066] FIG. 6 is a diagram showing an example of information acquired by the event determination unit 33, which the countermeasure information presenting unit 34 notifies and displays on the information output device 50. As shown in FIG.

[0067] The display screen of the information output device 50 displays the turbidity trend of the water to be treated, the retrieved past performance trend (51), the operation performance trend (52), and the treatment performance trend (53) and presents them to the operator. In addition, a table (54) listing the KPIs of the retrieved past performance trends is also displayed. This allows the operator to view evaluations of past performance similar to the current situation.

[0068] Furthermore, the display area 55 provides an input or selection area (such as a text box or list box) for the KPIs that the operator considers important, and by inputting the KPIs that the operator considers important, it becomes possible to present the work information with the highest KPIs from each perspective based on similar past performance.

[0069] For example, if an operator selects water quality and quantity as the most important KPI, links to trend 1's business information, alarms, and operation logs will be displayed, and the operator can quickly access the necessary information by selecting a link. This allows the operator to search for past performance when considering the most important perspective when an event occurs, and easily judge whether the operation is good or bad.

[0070] According to the embodiment of the operation support system, even when a less skilled operator manages a facility with little experience, it is expected that the amount of chemical usage can be optimized by preventing insufficient or excessive injection rates of chemicals. If the amount of chemical usage can be optimized, the frequency of chemical replenishment and transportation can be reduced, and carbon dioxide gas emissions during chemical production and transportation can be reduced.

[0071] According to the embodiment of the operation support system, countermeasure information based on past performance is automatically presented to operators who have little experience managing facilities when facilities are consolidated, abolished, or rearranged, making it possible to speed up and improve the accuracy of decision-making.

[0072] In addition, in plant operations, there are cases where measures are taken not only when a standard value is exceeded, but also when measures are taken in advance before the standard value is exceeded. In the present invention, since the judgment is based on the similarity of the operating state rather than the standard value, it is possible to present countermeasure information in either case and support the judgment of the operator.

[0073] The present invention is not limited to the above-described embodiment, but includes various modified examples. The above description is provided for the purpose of explaining the present invention in an easily understandable manner, and the present invention is not necessarily limited to the embodiment having all of the configurations. Furthermore, these functions may be integrated in any combination. For example, although the task information and event triggers are recorded separately in the task information storage unit 21 and the event storage unit 25, respectively, they may be recorded together.

[0074] In the above embodiment of the operation support system, an example has been shown in which it is applied to chemical injection control at a water purification plant. However, the system can also be applied to maintenance work such as blower control at a sewage treatment plant, or temperature control at an electric power plant or a waste disposal plant, where the system can explain (indicate) by the event name whether or not an event has occurred that requires some kind of countermeasure in relation to the operation of the plant.

[0075] In detail, this technology can be applied to the blower control of sewage treatment plants, where the blower is controlled to keep the DO (Dissolved Oxygen) of the treated water constant according to the inflow load (nitrogen), thereby promoting the nitrification of the treated water. The present invention can also be applied to controlling ventilation equipment at waste disposal plants to keep the temperature of incinerators constant depending on the amount of waste, etc.

[0076] Next, a description will be given of support for the operator's information input work in the task information input unit 31. In detail, when the operator inputs task information, the task information input unit 31 applies a similarity search in advance to acquire and display task information for the relevant date and time of past results similar to the current situation.

[0077] FIG. 7 is a process flow diagram of the business information input unit 31.

[0078] In step S11, the business information input unit 31 acquires current operation data such as water quality and quantity from the plant connected to the network 60 as the current situation, and also acquires past operation data such as water quality and quantity from the operation data accumulation unit 22. In step S12, driving data similar to the current situation acquired in step S11 is searched for and regarded as similar past results.

[0079] In step S13, the task information input unit 31 acquires information on the corresponding date and time from the task information accumulation unit 21 using the date and time when the similar past performance searched for in step S12 occurred. In step S14, the task information input unit 31 notifies the information output device 50 of task information for the relevant date and time of past results similar to the acquired current situation, and presents it to the operator.

[0080] When inputting task information, the task information input unit 31 presents the operator with task information and event names of past results similar to the current situation, allowing the operator to refer to the information necessary for input, making it easier to input task information. In addition, by viewing past task information and event names, it is expected that there will be an effect of preventing inconsistencies in notation.

[0081] In the above, a method of presenting the business information as is has been described, but the information to be presented is not particularly limited as long as it can assist the operator in entering information, for example, by extracting and presenting only nouns from the business information using a text mining technique. [Explanation of symbols]

[0082] 10 Driving support equipment 20 Information Storage Unit 21 Business Information Storage Unit 22 Operation data storage unit 23 Alarm storage section 24 Operation log storage unit 25 Event Storage Unit 30 Business Support Department 31 Business information input section 32 Measures Evaluation and Setting Division 33 Event Judgment Section 34 Countermeasures Information Presentation Department 35 Operation data acquisition section 40 Information input device 50 Information output device 60 Network

Claims

1. a task information input unit for inputting task information and an event name indicating the content of the task information in association with the date and time when the task occurred; an operation data acquisition unit for acquiring operation data of the plant; an event determination unit that searches for past records similar to the current state of the plant acquired by the operation data acquisition unit, and when an event name is set at the occurrence date and time of the searched similar past record, determines whether or not an event requiring a countermeasure has occurred based on the event name; a countermeasure information presentation unit that presents, when the event determination unit determines that an event requiring a countermeasure has occurred, business information on the date and time of occurrence of the event name and the event name as countermeasure information; A driving operation support system equipped with

2. The driving operation support system according to claim 1, further comprising: a countermeasure evaluation setting unit for determining a KPI of a countermeasure from a predetermined viewpoint regarding the similar past performance, the countermeasure information presentation unit presents countermeasure information having a high evaluation in the KPI obtained by the countermeasure evaluation setting unit; Driving operation support system.

3. The driving operation support system according to claim 2, The countermeasure evaluation setting unit sets a plurality of KPIs, The countermeasure information presentation unit presents the most highly rated past similar performance task information, alarm information, and operation log information by allowing the operator to select the KPI that he or she wants to prioritize. Driving operation support system.

4. The driving operation support system according to claim 2, The countermeasure evaluation setting unit sets any one of water quality / quantity, cost, labor, and number of alarms as a KPI when a water purification plant is the target. Driving operation support system.

5. The driving operation support system according to claim 1, the event determination unit searches for past results similar to a current situation by calculating a similarity between trends using Euclidean distance; The countermeasure information presentation unit extracts task information, alarm information, and operation log information based on the date and time of occurrence of the searched similar past results. Driving operation support system.

6. The driving operation support system according to claim 1, When the task information input unit inputs the task information and the event name, it searches for past records similar to the plant state at the date and time of the task information to be input, and presents task information and event names corresponding to the dates and times of the similar past records. Driving operation support system.

7. The driving operation support system according to claim 1, The countermeasure information presentation unit presents a display screen on which a list of similar past results, operation results, processing results, and KPIs, and links to task information, alarm information, and operation log information of the most highly evaluated trend among the KPIs selected by the operator are displayed. Driving operation support system.

8. inputting task information and an event name indicating the content of the task information in association with the date and time when the task occurred; acquiring operational data of a plant; a step of searching for past records similar to the current state of the plant, and when an event name is set at the occurrence date and time of the searched similar past record, determining whether or not an event requiring a countermeasure has occurred based on the event name; when it is determined that an event requiring a countermeasure has occurred, presenting business information on the date and time of occurrence of the event name and the event name as countermeasure information; A driving operation support method including:

9. A program for a driving operation support system, a task information input unit for inputting task information and an event name indicating the content of the task information in association with the date and time when the task occurred; an operation data acquisition unit for acquiring operation data of the plant; an event determination unit that searches for past records similar to the current state of the plant acquired by the operation data acquisition unit, and when an event name is set at the occurrence date and time of the searched similar past record, determines whether or not an event requiring a countermeasure has occurred based on the event name; a countermeasure information presentation unit that presents, when the event determination unit determines that an event requiring a countermeasure has occurred, business information on the date and time of occurrence of the event name and the event name as countermeasure information; A program to make it function as such.

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