TWI854538B - Support device, support method and support program - Google Patents

Abstract

[Topic] When a sensor in a factory detects an abnormality, it is easy and quick to grasp the information required for determining the fault location or cause. [Solution] A support device (10) for supporting the operation of a factory, comprising: an abnormality detection unit (14e) that detects a sensor that has displayed an abnormality based on sensor data detected by a plurality of sensors installed in the factory (1); a memory unit (18) that stores sensor correlation information, wherein the sensor correlation information is associated with: a plurality of sensor locations to which each sensor belongs and which represent a component of the factory, and a plurality of sensor locations that are detected by the plurality of sensors. The sensor parts are respectively used to measure the processes and the process sequence of the processes passing through the sensor parts; and the related information determination unit (14d) refers to the sensor related information stored in the memory unit (18) to determine the information related to the related sensor detected by the abnormality detection unit (14e) in at least one of the sensor parts, process and process sequence.

Description

Support device, support method and support program

The present invention relates to a support device, a support method and a support program for supporting the operation of a factory.

In the central monitoring room of the factory, the time series data obtained from the sensors installed in the factory are monitored, and the alarms issued by the DCS (distributed control system) are always monitored. The alarms issued span multiple levels from the attention level to the monitoring level. After the alarm is issued, the operator evaluates the importance or urgency of each alarm and determines whether specific treatment actions should be taken. [Prior Art Literature] [Patent Literature]

[Patent Document 1] Japanese Patent Publication No. 2000-56825

[The problem that the invention wants to solve]

However, there are also cases where the factory's manufacturing processes are complex and sometimes operators who do not have sufficient experience and knowledge are unable to determine the information needed to make judgments.

One of the exemplary purposes of one aspect of the present invention is to provide a support device, a support method, and a support program that can easily and quickly grasp the information required for determining the fault location or cause when a sensor in a factory detects an abnormality. [Means for solving the problem]

In order to solve the above-mentioned problem, one aspect of the present invention is a support device. The support device is a device for supporting the operation of a factory, and comprises: an abnormality detection unit, which detects a sensor showing an abnormality based on sensor data detected by a plurality of sensors installed in the factory; a memory unit, which stores sensor correlation information, and the sensor correlation information is associated with: a sensor location indicating a component of the factory to which each sensor belongs, a communication channel, and a communication channel; A process passing through the sensor portion and measured by the sensor, and a process sequence of the process passing through the sensor portion; and a related information determination unit, which refers to the sensor related information stored in the memory unit to determine information related to the related sensor confirmed to be related in at least one of the sensor portion, the process and the process sequence with respect to the detection sensor detected by the abnormality detection unit.

According to the above aspect, the support device determines the associated sensors confirmed to be relevant in at least one of the sensor location, process, and process sequence for the detection sensor, so that even an operator who does not have sufficient experience and knowledge can easily and quickly grasp the information required for judgment.

Another aspect of the present invention is a support method. The method is a method for supporting the operation of a factory, comprising the following steps: an abnormality detection step, which is to detect a sensor that shows an abnormality based on sensor data detected by a plurality of sensors installed in the factory; a memory step, which is to memorize sensor association information, wherein the sensor association information is associated with: a sensor location indicating a component of the factory to which each sensor belongs, and a sensor; A process for detecting a part of a sensor and measured by a sensor, and a process sequence indicating the order in which the process passes through the sensor part; and a correlation information specific step, which refers to the sensor correlation information stored in the storage step, to determine information related to the correlation sensor confirmed to be correlated in at least one of the sensor part, the process and the process sequence with respect to the detection sensor detected in the abnormality detection step.

Another aspect of the present invention is a support program. The program is a program for supporting the operation of a factory, which enables the computer to function as the following means: an abnormality detection means, which detects sensors that show abnormalities based on sensor data detected by multiple sensors installed in the factory; a memory means, which stores sensor correlation information, and the sensor correlation information is associated with: sensor locations representing the constituent elements of the factory to which each sensor belongs, A process that passes through a sensor portion and is measured by a sensor, and a process sequence that indicates the order in which the process passes through the sensor portion; and a correlation information specifying means that refers to the sensor correlation information stored by the storage means to determine information related to a correlation sensor that is confirmed to be correlated with a detection sensor detected by the abnormality detection means in at least one of the sensor portion, the process, and the process sequence.

In addition, any combination of the above components, or the components of the present invention or the components or expressions in methods, devices, systems, computer programs, data structures, recording media, etc., are also valid as aspects of the present invention. [Effects of the invention]

According to the present invention, when a sensor in a factory detects an abnormality, information required for determining the fault location or cause can be easily and quickly obtained.

The present invention is described below with reference to the drawings and through the embodiments of the invention, but the following embodiments do not limit the scope of the invention application, and all combinations of features described in the embodiments are not necessarily required for the solution of the invention. The same or equivalent components, components, and processes shown in each drawing are marked with the same element symbols, and repeated descriptions are appropriately omitted.

Fig. 1 to Fig. 5 are diagrams for explaining the support device 10 of an embodiment of the present invention. Specifically, Fig. 1 is a diagram showing the configuration of the support device 10 of an embodiment of the present invention, and Fig. 2 is a diagram showing an example of the hardware configuration of the support device 10. Fig. 3 and Fig. 4 are diagrams showing an example of the relationship between the sensor, sensor position, and process of the support device 10. Fig. 5 is a diagram for explaining an example of sensor correlation information stored in the sensor correlation information storage unit 18e.

The support device 10 is a device that supports the operation of the factory 1. As an example of the factory 1, a power plant, an incineration plant, or a chemical plant can be cited. Arbitrary sensor data is used in the factory 1. The sensor data is, for example, data of process values such as temperature, pressure, air volume, concentration, or composition. Specifically, the process value of the sensor data can include a measured value detected by a sensor (not shown) installed in the factory 1 and an operating amount based on the difference between a set value and a measured value for a point detected by the sensor. The sensor data obtained from the factory 1 is multidimensional data of more than hundreds of types.

The support device 10 is connected to the factory 1 via the DCS (distributed control system) 2 to obtain sensor data from sensors installed in the factory 1. According to the support device 10, when any sensor in the factory detects an abnormality, the information required for determining the fault location or cause can be easily and quickly obtained.

The support device 10 is pre-installed with a predetermined program required for executing the support method of the present embodiment, and an example of its hardware configuration is shown in FIG2 . Specifically, the support device 10 can use a general-purpose or dedicated computer having a CPU 100, a ROM 102, a RAM 104, an external memory device 106, a user interface 108, a display 110, and a communication interface 112. Based on information input by an operator through the user interface 108, the CPU 100 performs calculations and outputs the calculation results to the display 110. The operator can input required information to the support device 10 through the user interface 108 while recognizing the output.

The support device 10 may be composed of a single computer or a plurality of computers distributed on a network. In the support device 10, for example, the CPU executes a predetermined program (a program that specifies the support method of this embodiment) stored in the above-mentioned ROM, RAM, external storage device, etc. or downloaded via a communication network, so that the support device 10 can function as various functional blocks or various steps to be described later.

Hereinafter, various functional blocks of the support device 10 will be described using FIG. 1 .

The support device 10 of this embodiment includes an input unit 12 having an operation accepting unit 12a and a selection accepting unit 12b, a processing unit 14, a display unit 16 having a display 16a, and a memory unit 18. Here, the processing unit 14 includes a data acquisition unit 14a, a display control unit 14c, a related information determination unit 14d, and an abnormality detection unit 14e. In addition, the memory unit 18 includes an abnormal threshold information memory unit 18a, a sensor data memory unit 18b, a detection sensor information memory unit 18c, a related sensor information memory unit 18d, and a sensor correlation information memory unit 18e.

The data acquisition unit 14a acquires the sensor data of the factory through the DCS. The sensor data is used to determine the operating status of the factory and can also be called operating data. The sensor data is, for example, data representing the gradual change of the measured value of the sensor. In this case, the sensor data can also be the change of the measured value of the continuous sensor in a predetermined time interval. The sensor data can also be multi-dimensional data. The sensor data acquired by the data acquisition unit 14a is stored in the sensor data storage unit 18b together with the information related to the moment.

The abnormality detection unit 14e refers to the abnormal threshold information stored in the abnormal threshold information storage unit 18a, detects the existence of a value deviating from the threshold in the acquired sensor data, and stores the sensor representing the process value outside the threshold as a detection sensor in the detection sensor information storage unit 18c. Furthermore, the abnormal threshold information includes information on the threshold value that is determined to be abnormal for each sensor in the factory. The so-called abnormal state includes not only a state in which the factory operation has to be stopped, but also a state in which the factory can continue to operate but has deviated from a good operating state.

Furthermore, the abnormal threshold value information is information input by the user through the user interface 108, information stored in the external storage device 106 or the RAM 104, information automatically set as the factory operates, and the like.

The threshold for judging an abnormality can be set appropriately and arbitrarily. Furthermore, the threshold can be set in multiple stages. For example, when the measured value related to the temperature of a certain sensor is 60℃～80℃, the user can be notified "Caution", and when it is 80℃～100℃, the user can be notified "Monitoring is required".

The associated information determination unit 14d refers to the sensor associated information stored in the sensor associated information storage unit 18e and the detection sensor information stored in the detection sensor information storage unit 18c, and stores the sensors that are determined to be associated in at least one of the sensor position, process, and process sequence as associated sensor information in the associated sensor information storage unit 18d. The definition of the sensor position and process sequence will be described later. In addition, a specific example of the sensor associated information stored in the sensor associated information storage unit 18e will also be described later.

The display control unit 14c displays the measurement information of the related sensor on the display 16a according to the related sensor information stored in the related sensor information storage unit 18d. The measurement information is, for example, a time chart with the sensor's measurement value as the vertical axis and the measurement time as the horizontal axis, or the instantaneous value of the sensor's measurement value at a specific time.

The operation accepting unit 12a and the selection accepting unit 12b accept an operation or selection through the user interface 108 from a user who has confirmed the measurement information displayed on the display 16a, and change the information displayed on the display 16a through the display control unit 14c. The types of operation include, for example, filtering a part of the measurement information or changing the time width of the measurement information to be displayed.

Next, the relationship between the sensor, sensor location, and process is explained using Figure 3.

The sensor location represents the constituent elements of the factory. As an example, the sensor locations A to D in FIG3 are respectively the combustion furnace, the compact separator outlet, the superheater inlet, and the carbon dioxide equivalent inlet. Furthermore, the type of sensor location used as an example does not limit the factory to which the present invention is applied.

The so-called process is the process of a substance passing through various sensor parts of the factory. For example, process α and process β in Figure 3 pass through sensor parts A to D in different orders.

A process may only pass through a part of the components of a factory. For example, when all the components of a factory are sensor parts A to D, a process may pass through sensor parts A to C but not sensor part D. In addition, a process may branch to multiple sensor parts. For example, after a process passes through sensor part A, the process may branch to pass through sensor parts B and sensor parts C.

The sensor performs a measurement of a certain process in a certain sensor location. For example, sensor A1 in FIG3 performs a measurement of process α in sensor location A.

Furthermore, the sensor may be a sensor group consisting of a plurality of sensors that perform measurements in the same process at the same sensor site. For example, since sensors A1a to A1h all perform measurements of process α in sensor site A, sensor A1 can also be referred to as a sensor group consisting of sensors A1a to A1h. In cases where the area of the sensor site is wide and a single physical sensor cannot obtain sufficient information about the sensor site, a plurality of sensors may be provided as described above. For example, in a case where process α passes through a large area of sensor site A, a single physical sensor cannot measure the entire portion that passes through. Therefore, by using eight sensors A1a to A1h, the entire passing portion can be measured.

In this case, the detection sensor determined by the abnormality detection unit 14e may be the sensor A1 as the sensor group, or may be any one of the sensors A1a to A1h included in the sensor A1. For example, when an abnormality is detected in the sensor A1a, the sensor A1a itself may be used as the detection sensor, or the sensor group to which the sensor A1a belongs, i.e., the sensor A1, may be used as the detection sensor.

Furthermore, when sensor A1 is a sensor group, the measurement value of sensor A1 can be expressed in the form of a vector composed of at least a part of the measurement values of sensors A1a to A1h, or can be expressed as a statistic calculated from the measurement values of sensors A1a to A1h.

Furthermore, the sensor set may also be composed of a plurality of types of sensors. For example, sensors A2a to A2d may be temperature sensors, and sensors A2e to A2h may be pressure sensors.

Next, the relationship between the process and the process sequence will be described using FIG4. FIG4 is a simplified diagram of FIG3.

The so-called process sequence refers to the order of sensor parts that a certain process passes through. For example, the process sequence of process α in FIG4 is sensor part A, sensor part B, sensor part C, sensor part D, and the process sequence of process β is sensor part D, sensor part A, sensor part C, sensor part B.

The so-called process sequence stage refers to the order of passing a certain sensor part in the process sequence. For example, in process α, the process sequence of sensor part C is at the third stage among the four stages. In addition, the stages before and after the process sequence mean, for example, relative to sensor part C (the third stage in process α), sensor part B (the second stage in process α) is at the first stage, and sensor part D (the fourth stage in process α) is at the last stage.

Next, an example of sensor correlation information stored in the sensor correlation information storage unit 18e is described using Fig. 5. The so-called sensor correlation information is information in which sensor locations, processes, and process sequences are correlated with each sensor.

FIG5 shows sensor correlation information corresponding to the structure of the factory shown in FIG4. The sensor correlation information is established by correlating each sensor (c10) with the sensor location (c12), the process (c16) to be measured, and the stage (c16) of the process sequence that passes through the sensor location in the process.

By using sensor association information, the sensor location and process corresponding to a certain sensor can be determined, and vice versa, a certain sensor can be determined from the sensor location and process. For example, according to row r18, it is read that sensor C1 (r18, c10) belongs to sensor location C (r18, c12), and process α (r18, c14) is measured. The process sequence in process α of sensor location C is the third stage (r18, c16). In addition, for example, according to row c14 of "Process" which is rows r10, r14, r18, and r22 of process α, it is read that process α is measured by sensors A1, B1, C1, and D1 in sensor locations A, B, C, and D, respectively.

The sensor association information is not limited to that represented by a single table as shown in FIG5. For example, it may be represented by a plurality of tables that can be combined appropriately to create a table equivalent to the table in FIG5. Furthermore, it may be represented by a data structure other than a table, such as a list format or an XML (Extensible Markup Language) format.

As an embodiment of the support device of the present invention, an example of the operation of the support device is described below using the flowcharts of Figures 6 to 9. Figure 6 is an example of the entire operation of the support device of this embodiment. Figures 7 to 9 are examples of the operation when the related information determination unit 14d determines the related sensor.

In FIG6 , first, the sensor data is acquired by the data acquisition unit 14a (S10). The sensor data acquired by the data acquisition unit 14a is stored in the sensor data storage unit 18b. The sensor data can be acquired directly from the DCS 2, or can be acquired by accepting the input of sensor data from the user through the user interface 108, or can be acquired by reading from the RAM 104 or the external storage device 106.

Next, in the abnormality detection unit 14e, the sensor data stored in the sensor data storage unit 18b is compared with the abnormal threshold information stored in the abnormal threshold information storage unit 18a (S14). If there is no sensor data exceeding the threshold, it is assumed that no abnormal sensor is displayed and the support device terminates the operation.

On the other hand, when there is sensor data exceeding the threshold, the sensor corresponding to the sensor data is set as a detection sensor (S16). Information related to the detection sensor is stored in the detection sensor information storage unit 18c.

After step S16, the associated information determination unit 14d determines the associated sensor based on the detection sensor information stored in the detection sensor information storage unit 18c and the sensor association information stored in the sensor association information storage unit 18e (S18). An example of the operation of the associated information determination unit 14d is described separately using FIG. 7 to FIG. 9. The information of the determined associated sensor is stored in the associated sensor information storage unit 18d.

After step S18, the display control unit 14c displays the measurement information on the display 16a based on the detection sensor information stored in the detection sensor information storage unit 18c and the associated sensor information stored in the associated sensor information storage unit 18d (S20). The displayed information can be changed according to the input from the user to the operation receiving unit 12a or the selection receiving unit 12b. An example of the display screen is described separately using FIG. 10. After step S20, the support device 10 ends the operation.

The above-mentioned actions of the embodiment of the present invention are only examples and are not limited thereto. For example, the order of each step can be changed within the range where the actions do not conflict, and at least a part of the steps can be repeatedly executed (for example, after step S20, the steps do not end but return to step S10, etc.).

Next, an example of the operation of the related information determination unit 14d when the sensor C1 in Fig. 4 is a detection sensor showing an abnormality is described using Fig. 7, Fig. 4, and Fig. 5. In this example, the process measured by the sensor C1 is determined, and sensors belonging to other sensor parts through which the process passes are determined as related sensors.

First, determine the process measured by sensor C1 and the sensor part to which sensor C1 belongs. Specifically, first, based on the information of column c14 of the process in row r18 where row c10 of the sensor is "sensor C1", determine process α (r18, c14) (S182a). Second, based on the information of column c12 of the sensor part in row r18 where row c10 of the sensor is "sensor C1", determine sensor part C (r18, c12) (S182b). Here, the determined process α and sensor part C correspond to the process measured by sensor C1 and the part to which sensor C1 belongs, respectively.

Furthermore, in row r10, row r14, row r18 and row r22 where row c14 of the process is "process α", row c12 of the sensor part is referred to to determine the sensor part that is different from the sensor part C and through which process α passes (S182c).

The candidates for the determined sensor parts are sensor part A (r10, c12), sensor part B (r14, c14), and sensor part D (r22, c12), and any one of them may be determined. In this embodiment, an example of determination in consideration of the process sequence is shown. Specifically, when the process sequence of sensor part C in process α is the third stage (r18, c16), the sensor part D in the fourth stage (r22, c16) which is one stage later in the process α is determined.

Finally, the sensor D1 (r22, c10) corresponding to the row r22 whose sensor part column c12 is "sensor part D" and whose process column c14 is "process α" is determined as the associated sensor (S182d).

Even for sensors belonging to a sensor part different from the detection sensor, the correlation of information shown by the sensor parts passing through the same process tends to be higher than that of sensor parts passing through different processes. In particular, the correlation of information shown by the sensor parts that are in the front and back of the process sequence (that is, either the first stage or the last stage) is higher. For example, in the relationship with process α, for sensor part C (r18, c12) in the third stage of the process sequence, there is a tendency to have a higher correlation with sensor part D (r22, c12) in the fourth stage of the process sequence than with sensor part A (r10, c12) in the first stage of the process sequence. In this case, the fault location that cannot be determined by sensor C1 alone can be determined by combining the information of sensor D1.

Next, another example of the operation of the correlation information determination unit 14d when the sensor C1 in Fig. 4 is a detection sensor will be described using Fig. 8, Fig. 4 and Fig. 5. In this example, a sensor belonging to the same sensor part as the sensor C1 and measuring a different process is determined as a correlation sensor.

First, determine the process measured by sensor C1 and the sensor part to which sensor C1 belongs. Specifically, first, based on the information of column c14 of the process in row r18 where row c10 of the sensor is "sensor C1", determine process α (r18, c14) (S184a). Second, based on the information of column c12 of the sensor part in row r18 where row c10 of the sensor is "sensor C1", determine sensor part C (r18, c12) (S184b). Here, the determined process α and sensor part C correspond to the process measured by sensor C1 and the part to which sensor C1 belongs, respectively.

Furthermore, based on the fact that the sensor site row c12 is r18 and r20 of "sensor site C", the process row c14 is referred to to determine the process β (r20, c14) different from the process α (S184c).

Finally, the sensor C2 (r20, c10) corresponding to the row r20 in which the sensor part column c12 is "sensor part C" and the process column c14 is "process β" is determined as the associated sensor (S184d).

Even if the process of measuring and detecting sensors is different, the information displayed by sensors belonging to the same sensor section tends to be more correlated than that of sensors belonging to different sensor sections. For example, the fault section that cannot be determined by sensor C1 alone can be determined by combining the information of the determined sensor C2.

Next, another example of the operation of the related information determination unit 14d when the sensor C1 in Fig. 4 is a detection sensor will be described using Fig. 9, Fig. 4 and Fig. 5. In this example, a sensor belonging to a different sensor part from the sensor C1 and measuring a different process is determined as a related sensor.

First, the process measured by sensor C1 and the sensor part to which sensor C1 belongs are determined. Specifically, first, based on the information of column c14 of the process in row r18 where row c10 of the sensor is "sensor C1", process α is determined (S186a). Second, based on the information of column c12 of the sensor part in row r18 where row c10 of the sensor is "sensor C1", sensor part C is determined (S186b). Here, the determined process α and sensor part C correspond to the process measured by sensor C1 and the part to which sensor C1 belongs, respectively.

Next, based on the fact that the sensor site row c12 is r18 and r20 of "sensor site C", the process row c14 is referenced to determine the process β (r20, c14) different from the process α (S186c).

Furthermore, based on the fact that row c14 of the process is row r12, row r16, row r20 and row r24 of "process β", row c12 of the sensor part is referred to to determine the sensor part different from the sensor part C passed by process β (S186d).

The candidates for the determined sensor parts are sensor part A (r12, c12), sensor part B (r16, c12), and sensor part D (r24, c12), and any one of them can be determined. In this embodiment, an example of determination in consideration of the process sequence is shown. Specifically, when the process sequence of sensor part C in process β is the third stage (r20, c16), the sensor part A whose process sequence in process β is the second stage (r12, c16) of the previous stage is determined.

Finally, the sensor A2 (r12, c10) corresponding to the row r12 whose sensor part column c12 is "sensor part A" and whose process column c14 is "process β" is determined as the associated sensor (S186e).

Even if the sensor measures a different process from the detection sensor and belongs to a different sensor part, the sensor determined by the above method tends to have a higher correlation. This is because the process measured by the sensor determined by the above method and the process measured by the detection sensor both pass through the sensor part to which the detection sensor belongs. For example, since the process β measured by the sensor A2 determined by the above method and the process α measured by the detection sensor C1 both pass through the sensor part C to which the detection sensor C1 belongs, there is a situation where the correlation between sensor A2 and sensor C1 is high.

Furthermore, the information shown by the sensors is more correlated with each other in the process sequence (i.e., either one stage before or one stage after) among the sensor parts. For example, in the relationship with process β, for sensor part C (r20, c12) in the third stage of the process sequence, sensor part A (r12, c12) in the second stage of the process sequence tends to have a higher correlation than sensor part D (r24, c12) in the first stage of the process sequence. In this case, the fault part that cannot be determined by sensor C1 alone can be determined by combining the information of the determined sensor A2. The sensors shown in this embodiment, which are able to be correlated even though the processes and sensor locations are different, are particularly difficult to detect for unskilled operators.

The above-mentioned determination method of the associated sensors can be superimposed using different determination methods. For example, the associated sensors can also include all sensors D1 of the same process but different sensor locations, sensors C2 of different processes but the same sensor locations, and sensors A2 of different processes but different sensor locations.

Furthermore, the above-mentioned determination method of the associated sensor can be superimposed and the same determination method can be used. For example, the associated sensor can also include both the sensor D1 and the sensor B1 which are a plurality of sensors in the same process and different sensor locations.

FIG. 10 is an example of a display screen 200 of information of associated sensors obtained by the present embodiment. The graph display area 230 displays measurement information of the detection sensor and associated sensors. The display period setting area 210 displays the period of the graph to be displayed. The filter option area 220 displays a button for selecting and displaying information of a portion of the graph. The reset button area 240 displays a button for resetting the set filter conditions.

In the graph display area 230, the measurement information of the detection sensor and the related sensors is displayed by the timing graph. The timing graph area 232 displays the timing graph 232a corresponding to the description 233 and the sensor C1. In this way, when the sensor C1 is a single sensor, only one timing graph can be displayed.

However, as shown in the timing chart area 238, a plurality of timing charts may be displayed in the area. Specifically, in a certain sensor portion, when there are a plurality of sensors (sensor groups) measuring the same process, a timing chart corresponding to each sensor may be displayed. For example, as shown in the sensor A2 in FIG. 3, when there are eight sensors A2a to A2h measuring process β in the sensor portion A, eight corresponding timing charts 238a to 238h may be displayed in the timing chart area 238.

Thus, by displaying a plurality of sensors belonging to the same sensor part and measuring the same process side by side, it is possible to more accurately grasp the fault part, etc. For example, when an abnormality is found in the timing chart 238a, and no abnormality is found in the other seven timing charts such as the timing chart 238h arranged in the timing chart area 238, it can be inferred that there is a fault around the part where the sensor corresponding to the timing chart 238a is installed. More specifically, when the sensor corresponding to the timing chart 238a is, for example, the sensor A2a in FIG. 3, it can be inferred that there is a fault part in the sensor part A (combustion furnace), especially in the lower left middle position.

The timing diagram 234a (corresponding to the sensor D1), the timing diagram 236a (corresponding to the sensor C2), and the timing diagrams 238a to 238h (corresponding to the sensor A2) of the graph display area 230 are the measurement information of the associated sensors when the detection sensor in FIG4 is the sensor C1. These associated sensors are determined by superimposing different determination methods. Specifically, the sensor is determined by the associated information determination unit 14d for the sensor C1 as the detection sensor, the sensor D1 as a sensor that measures the same process and belongs to a different sensor part, the sensor C2 as a sensor that measures a different process and belongs to the same sensor part, and the sensor A2 as a sensor that measures a different process and belongs to a different sensor part.

In the graph display area 230, timing graphs corresponding to a plurality of sensors determined in an overlapping manner using the same determination method may also be displayed simultaneously. For example, in the case where the detection sensor in FIG4 is the sensor C1, a timing graph corresponding to the sensor B1 determined as a sensor for measuring the same process and belonging to a different sensor part with respect to the sensor C1 may be displayed simultaneously (not shown in FIG10), and a timing graph corresponding to the sensor B2 determined as a sensor for measuring a different process and belonging to a different sensor part with respect to the sensor C1 may also be displayed simultaneously (not shown in FIG10).

The measured values or the display range of the vertical axis of the timing graph displayed in the graph display area 230 may be different. For example, when the timing graph 238a shows the change of temperature, a graph showing the change of pressure such as the timing graph 238h may also be displayed at the same time. In addition, for example, when the timing graph 232a is displayed in the range of 0°C to 100°C, the timing graph 236a may also be displayed in the range of -80°C to 300°C.

By changing the measured value or vertical axis display range for each timing graph, the display screen's visual visibility can be improved, and information required for diagnosis, such as the location of a fault, can be found effectively.

The timing graph displayed in the graph display area 230 may be provided with a scroll bar for changing the display range in the horizontal direction. By operating the scroll bar, the display range of a timing graph can be changed, and all timing graphs can be scrolled at the same time.

The time series graph displayed in the graph display area 230 has a display range in the horizontal axis that can be changed by user operation. For example, the user receives a scroll wheel operation of a mouse through the user interface 108 and the graph is enlarged or reduced in the horizontal axis accordingly.

By being able to change the display range of the horizontal axis, for example, after checking the overall trend of the timing graph over a long time width, it is possible to check the sensor data by focusing on the period that is particularly necessary for determining the fault location, etc.

The timing charts can be displayed side by side as shown in Figure 10, or multiple sensor data can be overlaid on one timing chart.

The display period setting area 210 can change the display range of the horizontal axis of each time-series graph according to the input from the user through the user interface 108. For example, when it is set to "0:00 on March 1, 2022 to 12:15 on March 2, 2022", the left end of the horizontal axis of each time-series graph is set to "0:00 on March 1, 2022" and the right end is set to "12:15 on March 2, 2022", and the measured value in this period is displayed. The time set in the display period setting area 210 can also be changed to match it according to the operation of the above-mentioned scroll bar.

In the filter option area 220, buttons for processes, sensor locations, and measurement objects are displayed, and information to be displayed can be selected based on input from the user via the user interface 108. For example, when the "process α" of the button 220a is selected, the timing chart 232a and the timing 234a as the measurement information of the sensor measuring the process α are displayed.

Multiple conditions may be applied in a stacked manner to make selections. For example, when "sensor location A" of button 220c and "temperature" of button 220g are selected, only the measurement information of the temperature sensor including timing chart 238a among timing charts 238a to 238h is displayed.

If the number of related sensors increases, the visual visibility of the display screen will decrease if the so-called timing graph corresponding to them is displayed, and it will not be possible to properly find useful information. By enabling such a selection, only the necessary information can be displayed from a large number of related sensors according to the user's operation.

The present invention is not limited to the above-mentioned embodiments, and can be used in various modifications. The operation of the support device 10 is not limited to all automation through computer operation processing, but also includes at least a part of manual operation performed by operators. In addition, in the above-mentioned embodiments, the display unit illustrated in FIG. 10 is only an example and is not limited to this.

The embodiments described in the embodiments of the invention described above can be appropriately combined or modified or improved for use according to the purpose, and the present invention is not limited to the description of the embodiments described above. For example, the present invention can be applied to multiple sensors that detect abnormalities as detection sensors, or one or more sensors with particularly high correlation among the determined sensors can be used as correlation sensors. It can be clearly stated in the description of the scope of the invention application that such a combination or a modified or improved form can also be included in the technical scope of the present invention. This application claims priority based on Japanese Patent Application No. 2022-052747 filed on March 29, 2022. The entire contents of the Japanese application are cited in this specification by reference.

1: Factory 2: DCS 10: Support device 12a: Operation receiving unit 12b: Selection receiving unit 14a: Data acquisition unit 14b: Control unit 14c: Display control unit 14d: Related information determination unit 14e: Abnormal detection unit 16a: Display 18: Memory unit 18a: Abnormal threshold information memory unit 18b: Sensor data memory unit 18c: Detection sensor information memory unit 18d: Related sensor information memory unit 18e: Sensor correlation information memory unit 100: CPU 102: ROM 104: RAM 106: External memory device 108: User interface 110: Display 112: Communication interface

[FIG. 1] is a diagram showing the configuration of a support device 10 related to an embodiment of the present invention. [FIG. 2] is a diagram showing an example of the hardware configuration of the support device 10. [FIG. 3] is a diagram showing an example of the relationship between the sensor, sensor location, and process of the support device 10. [FIG. 4] is a diagram showing an example of the relationship between the sensor, sensor location, and process of the support device 10. [FIG. 5] is a diagram showing an example of sensor correlation information stored in the sensor correlation information storage unit 18e. [FIG. 6] is a flowchart showing an example of a support method based on the support device 10. [FIG. 7] is a flowchart showing an example of a support method based on the support device 10. [FIG. 8] is a flowchart showing an example of a support method based on the support device 10. [Figure 9] is a flowchart showing an example of a support method based on the support device 10. [Figure 10] is a diagram showing an example of a display screen based on the support device 10.

1: Factory

2: DCS (Distributed Control System)

10: Support devices

12: Input section

12a: Operation acceptance department

12b: Select the receiving department

14: Processing Department

14a: Data acquisition department

14b: Control Department

14c: Display control unit

14d: Related information confirmation department

14e: Abnormality Detection Department

16: Display unit

16a: Display

18: Memory Department

18a: Abnormal threshold information storage unit

18b: Sensor data memory unit

18c: Detection sensor information storage unit

18d: Related sensor information memory unit

18e: Sensor related information storage unit

Claims (11)

A support device for supporting the operation of a factory, comprising: an abnormality detection unit, which detects a sensor that shows an abnormality based on sensor data detected by a plurality of sensors installed in the factory; a storage unit, which stores sensor correlation information, wherein the sensor correlation information is associated with: a plurality of sensor parts to which each sensor belongs and which represent the constituent elements of the factory, processes that pass through the plurality of sensor parts and are measured by sensors belonging to the plurality of sensor parts, and the process sequence of the processes passing through the plurality of sensor parts; and a correlation information determination unit, which refers to the information stored in the storage unit. The aforementioned sensor correlation information in the aforementioned memory unit determines information related to the associated sensor confirmed to be correlated in at least one of the aforementioned sensor location, the aforementioned process, and the aforementioned process sequence with respect to the detection sensor detected by the aforementioned abnormality detection unit; wherein the aforementioned process includes a first process passing through the detection sensor location to which the aforementioned detection sensor belongs; the aforementioned detection sensor measures the aforementioned first process; the aforementioned associated sensor includes a first associated sensor, the first associated sensor belongs to a first sensor location different from the aforementioned detection sensor location and through which the aforementioned first process passes, and measures the aforementioned first process. A support device as claimed in claim 1, wherein, the first sensor portion is relative to the detection sensor portion, and the process sequence in the first process is either the first stage or the second stage. As in the support device of claim 1, the aforementioned process includes: a first process passing through the detection sensor part to which the aforementioned detection sensor belongs, and a second process different from the aforementioned first process and passing through the aforementioned detection sensor part; the aforementioned associated sensor includes a second associated sensor different from the aforementioned detection sensor and belonging to the aforementioned detection sensor part. As in the support device of claim 1, the aforementioned process includes: a first process passing through the detection sensor part to which the aforementioned detection sensor belongs, and a second process different from the aforementioned first process and passing through the aforementioned detection sensor part; the aforementioned associated sensor includes a third associated sensor, the third associated sensor belongs to a second sensor part different from the aforementioned detection sensor part and passed by the aforementioned second process, and measures the aforementioned second process. As in claim 4, the supporting device, wherein the second sensor part is relative to the detection sensor part, and the process sequence in the second process is either the first stage or the second stage. The support device of any one of claim 1 to claim 5 further comprises: a display unit that displays the measurement information of at least a part of the aforementioned associated sensors; The aforementioned measurement information is information that associates the measurement time of the aforementioned measurement value with the measurement value. As in the support device of claim 6, the aforementioned measurement information includes a time series chart with the aforementioned measurement time on the horizontal axis established in association with the aforementioned measurement value on the vertical axis. The support device of claim 7 further comprises: an operation accepting unit that accepts an operation from a user; and the display unit changes the display range of the horizontal axis of the timing chart according to the operation accepted by the operation accepting unit. The support device of claim 6 further comprises: a selection accepting unit that accepts a user's selection of at least one of the type of the sensor, the type of the process, and the location of the sensor; and the display unit selects and displays the measurement information according to the selection accepted by the selection accepting unit. A method for supporting the operation of a factory, comprising the following steps: an abnormality detection step, which detects a sensor that shows an abnormality based on sensor data detected by a plurality of sensors installed in the aforementioned factory; a memory step, which stores sensor association information, wherein the sensor association information is associated with: a plurality of sensor locations to which each sensor belongs and which represent the constituent elements of the aforementioned factory, processes that pass through the aforementioned plurality of sensor locations and are measured by sensors belonging to the plurality of sensor locations, and a process sequence of the aforementioned processes passing through the aforementioned plurality of sensor locations; and a correlation information specific step, which refers to the sensor data stored in the aforementioned sensor location by the aforementioned sensor location. The sensor correlation information stored in the memory step is used to determine information related to the associated sensor confirmed to be associated with the detection sensor detected in the abnormal detection step in at least one of the sensor location, the process, and the process sequence; wherein the process includes a first process passing through the detection sensor location to which the detection sensor belongs; the detection sensor measures the first process; the associated sensor includes a first associated sensor, the first associated sensor belongs to a first sensor location different from the detection sensor location and through which the first process passes, and measures the first process. A support program for supporting the operation of a factory, the support program enables a computer to function as the following means: an abnormality detection means, which detects a sensor that shows an abnormality based on sensor data detected by a plurality of sensors installed in the aforementioned factory; a storage means, which stores sensor correlation information, the sensor correlation information is associated with: a plurality of sensor parts to which each sensor belongs and which represent the constituent elements of the aforementioned factory, processes that pass through the aforementioned plurality of sensor parts and are measured by sensors belonging to the plurality of sensor parts, and the process sequence of the aforementioned process passing through the aforementioned plurality of sensor parts; and a correlation information determination means. , which refers to the aforementioned sensor correlation information stored by the aforementioned storage means, and determines the information related to the associated sensor confirmed to be associated in at least one of the aforementioned sensor location, the aforementioned process, and the aforementioned process sequence for the detection sensor detected by the aforementioned abnormal detection means; wherein the aforementioned process includes a first process passing through the detection sensor location to which the aforementioned detection sensor belongs; the aforementioned detection sensor measures the aforementioned first process; the aforementioned associated sensor includes a first associated sensor, the first associated sensor belongs to a first sensor location different from the aforementioned detection sensor location and through which the aforementioned first process passes, and measures the aforementioned first process.

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