Facility state display device, facility state display method and program

Abstract

To provide a technique capable of monitoring a state of a facility by considering an influence when abnormality occurs.SOLUTION: According to one aspect of the present disclosure, a facility state display device has: a calculation part for calculating a plurality of abnormality index values with respect to each of a plurality of monitoring object facilities by an abnormality diagnosis technique by using a plurality of pieces of operation data collected from each of the plurality of monitoring object facilities; and a display control part for displaying each of the plurality of abnormality index values as a facility state on the basis of an influence degree representing the degree of influence magnitude when abnormality occurs in the monitoring object facility.SELECTED DRAWING: Figure 6

Description

[Technical field]

[0001] The present disclosure relates to an equipment status display device, an equipment status display method, and a program. [Background technology]

[0002] An abnormality diagnosis technique using multivariate analysis is known (for example, Patent Document 1, etc.). In the abnormality diagnosis technique, an abnormality index value that indicates the degree of abnormality of equipment is generally calculated, and then an abnormality diagnosis is performed based on whether or not the abnormality index value exceeds a predetermined threshold value. For this reason, the abnormality index value and the corresponding threshold value are visualized to monitor the state of the equipment. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] JP 2011-209847 A Summary of the Invention [Problem to be solved by the invention]

[0004] However, since a factory or the like generally has multiple pieces of equipment, and the impact of an abnormality occurring may differ depending on the equipment, simply visualizing the abnormality index value of each piece of equipment and its corresponding threshold value does not allow for monitoring that takes into account the impact of an abnormality occurring in the equipment.

[0005] The present disclosure has been made in consideration of the above points, and provides a technology that can monitor the state of equipment while taking into account the impact when an abnormality occurs. [Means for solving the problem]

[0006] An equipment status display device according to one aspect of the present disclosure includes a calculation unit that calculates multiple abnormality index values ​​for each of multiple monitored equipment through an abnormality diagnosis technique using multiple operating data collected from each of the multiple monitored equipment, and a display control unit that displays each of the multiple abnormality index values ​​as an equipment status based on an impact degree that indicates the degree of impact when an abnormality occurs in the monitored equipment. Effect of the Invention

[0007] To provide a technology that can monitor the state of equipment while taking into account the impact when an abnormality occurs. [Brief description of the drawings]

[0008] [Figure 1] 1 is a diagram illustrating an example of an overall configuration of a monitoring system according to an embodiment of the present invention. [Diagram 2] FIG. 2 is a diagram illustrating an example of a hardware configuration of a monitoring device according to the present embodiment. [Diagram 3] FIG. 2 is a diagram illustrating an example of a functional configuration of a monitoring device according to the present embodiment. [Figure 4] FIG. 11 is a diagram illustrating an example of facility information. [Diagram 5] 10 is a flowchart illustrating an example of a monitoring process according to the embodiment. [Figure 6] FIG. 1 is a diagram illustrating an example of an equipment state. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0009] An embodiment of the present invention will be described below, which is a monitoring system 1 that can monitor the status of multiple pieces of equipment contained in a facility such as a factory or a plant, taking into account the impact of an abnormality occurring in each piece of equipment.

[0010] <Overall configuration example of monitoring system 1> An example of the overall configuration of a monitoring system 1 according to this embodiment is shown in Fig. 1. As shown in Fig. 1, the monitoring system 1 according to this embodiment includes a monitoring device 10, a facility 20, and an operator terminal 30. Here, the monitoring device 10 and a control device 23 described below are connected to each other so as to be able to communicate with each other via a communication network including, for example, a LAN (Local Area Network). Similarly, the monitoring device 10 and the operator terminal 30 are connected to each other so as to be able to communicate with each other via a communication network including, for example, a LAN.

[0011] The monitoring device 10 uses operation data collected from a facility 20 (more precisely, a control device 23 included in the facility 20) to perform abnormality diagnosis of each monitored equipment 21, which will be described later, by a method of multivariate statistical process control (MSPC). Multivariate statistical process control (MSPC) is one of the abnormality diagnosis techniques that utilizes multivariate analysis, and for details, please refer to, for example, Reference 1. Note that operation data is generally composed of multiple variables (these variables are also called process variables), and the values ​​of each variable are measured by each measuring instrument 22, which will be described later, and therefore are called measurement values, etc. Examples of variables that make up the operation data include temperature, pressure, flow rate, voltage, etc.

[0012] The monitoring device 10 also detects abnormality index values ​​(e.g., Q values, T 2 The abnormality index value (value) is plotted as the equipment status of the monitored equipment 21 on a monitoring screen displayed on a display or the like of the operator terminal 30. At this time, the monitoring device 10 plots the abnormality index values, for example, from the left in descending order of influence, taking into consideration the degree of influence that indicates the degree of influence when an abnormality occurs in each monitored equipment 21. The monitoring screen is a screen on which an operator or the like can check (monitor) the abnormality index value of each monitored equipment 21 in real time. Hereinafter, it is assumed that the greater the influence when an abnormality occurs in each monitored equipment 21, the higher the influence, and that the smaller the influence, the lower the influence.

[0013] Here, the impact when an abnormality occurs in the monitored equipment 21 refers to the operational impact and cost impact that arise when some abnormality (for example, a malfunction or failure) occurs in the monitored equipment 21. Examples of the operational impact include the length of time it takes for the monitored equipment 21 to recover after an abnormality occurs in the monitored equipment 21, the number of other monitored equipment 21 that will be affected by the occurrence of an abnormality in the monitored equipment 21, and the difficulty of recovering the monitored equipment 21 when an abnormality occurs in the monitored equipment 21. Examples of the cost impact include the cost required to recover the monitored equipment 21 when an abnormality occurs in the monitored equipment 21.

[0014] For example, when considering the length of time it takes for the monitored equipment 21 to recover after an abnormality occurs in the monitored equipment 21, the longer the period, the higher the impact, and the shorter the period, the lower the impact. Also, when considering the number of other monitored equipment 21 that will be affected when an abnormality occurs in the monitored equipment 21, the greater the number, the higher the impact, and the smaller the number, the lower the impact. Also, when considering the difficulty of recovering the monitored equipment 21 when an abnormality occurs in the monitored equipment 21, the higher the difficulty, the higher the impact, and the lower the difficulty, the lower the impact. Also, when considering the cost required to recover the monitored equipment 21 when an abnormality occurs in the monitored equipment 21, the higher the cost, the higher the impact, and the lower the cost, the lower the impact.

[0015] The monitoring device 10 is realized by, for example, a PC (personal computer), a general-purpose server, etc. The monitoring device 10 may be, for example, a system configured by a plurality of PCs, a plurality of general-purpose servers, etc.

[0016] In the following, as an example, the abnormality index value is described as a Q value. However, the abnormality index value is not limited to the Q value, and can be any value. 2 It may be a value.

[0017] The facility 20 is, for example, various facilities such as a factory or a plant. The facility 20 includes a plurality of monitored equipment 21, a plurality of measuring instruments 22, and a control device 23. The monitored equipment 21 is various equipment (for example, production equipment, heat source equipment, pump equipment, etc.), industrial equipment, various devices, etc. that are monitored by the monitoring device 10 (i.e., abnormality diagnosis target). The measuring instruments 22 are sensors, etc., that measure physical quantities that indicate various states of the monitored equipment 21, and transmit measurement data including the measured values ​​to the control device 23. One or more measuring instruments 22 are installed in each monitored equipment 21. The control device 23 transmits operation data consisting of measurement values ​​included in the measurement data collected from each measuring instrument 22 installed in the monitored equipment 21 to the monitoring device 10 for each monitored equipment 21, and controls the monitored equipment 21 by a known process control method based on the operation data.

[0018] Hereinafter, the number of monitored equipment 21 included in the facility 20 is defined as m, and each monitored equipment 21 is referred to as monitored equipment 21 i (i = 1, ,m).

[0019] The operator terminal 30 is a terminal such as a PC, a smartphone, or a tablet terminal used by an operator who operates the facility 20. The operator can use the operator terminal 30 to check the Q value of each monitored equipment 21 and the corresponding threshold value in real time on a monitoring screen provided by the monitoring device 10. Moreover, at this time, the operator can check the Q value and the corresponding threshold value of each monitored equipment 21 in descending order of the degree of influence. Therefore, it becomes possible to promptly start preparation work in the event of an abnormality occurring, such as preparing a substitute machine for the monitored equipment 21 or preparing maintenance work, according to the Q value of each monitored equipment 21 and the corresponding threshold value and the degree of influence. For example, the operator terminal 30 is provided with a Web browser or the like, and the monitoring screen can be displayed on a display by the Web browser or the like.

[0020] 1 is merely an example, and is not intended to be limiting. For example, the monitoring device 10 and the operator terminal 30 may be integrated, or the monitoring device 10 and the control device 23 may be integrated. Alternatively, for example, the monitoring device 10 may be realized by a virtual machine (VM), or when the monitoring device 10 is a system made up of a plurality of devices, a part of the system may be realized by a virtual machine.

[0021] <Example of Hardware Configuration of Monitoring Device 10> An example of a hardware configuration of the monitoring device 10 according to this embodiment is shown in Fig. 2. As shown in Fig. 2, the monitoring device 10 according to this embodiment has an input device 101, a display device 102, an external I / F 103, a communication I / F 104, a RAM (Random Access Memory) 105, a ROM (Read Only Memory) 106, an auxiliary storage device 107, and a processor 108. Each of these pieces of hardware is connected to each other via a bus 109 so as to be able to communicate with each other.

[0022] The input device 101 is, for example, a keyboard, a mouse, a touch panel, a physical button, etc. The display device 102 is, for example, a display, a display panel, etc. Note that the monitoring device 10 does not necessarily have to include at least one of the input device 101 and the display device 102, for example.

[0023] The external I / F 103 is an interface with an external device such as a recording medium 103a. Examples of the recording medium 103a include a CD (Compact Disc), a DVD (Digital Versatile Disk), an SD memory card (Secure Digital memory card), and a USB (Universal Serial Bus) memory card.

[0024] The communication I / F 104 is an interface for connecting the monitoring device 10 to a communication network. The RAM 105 is a volatile semiconductor memory (storage device) that temporarily stores programs and data. The ROM 106 is a non-volatile semiconductor memory (storage device) that can store programs and data even when the power is turned off. The auxiliary storage device 107 is a storage device (storage device) such as a hard disk drive (HDD), a solid state drive (SSD), or a flash memory. The processor 108 is various types of arithmetic devices such as a central processing unit (CPU) or a graphics processing unit (GPU).

[0025] 2 is merely an example, and the hardware configuration of the monitoring device 10 is not limited thereto. For example, the monitoring device 10 may have multiple auxiliary storage devices 107 and multiple processors 108, may not have some of the hardware shown in the figure, or may have various types of hardware other than the hardware shown in the figure.

[0026] <Example of functional configuration of monitoring device 10> FIG. 3 shows an example of the functional configuration of the monitoring device 10 according to the present embodiment. As shown in FIG. 3, the monitoring device 10 according to the present embodiment has an operation data collection unit 201, a diagnosis unit 202, and a display control unit 203. These units are realized, for example, by a process in which one or more programs installed in the monitoring device 10 are executed by the processor 108 or the like. The monitoring device 10 according to the present embodiment also has an operation data storage unit 204, a diagnosis model storage unit 205, a diagnosis result storage unit 206, and a facility information storage unit 207. Each of these storage units is realized, for example, by the auxiliary storage device 107 or the like. Note that some of these storage units may be realized, for example, by a storage device connected to the monitoring device 10 via a communication network.

[0027] The operation data collection unit 201 collects operation data transmitted from the facility 20 (more precisely, the control device 23) and stores the operation data in the operation data storage unit 204. Hereinafter, for i=1, . . . , m, the monitored equipment 21 i Operating data of x (i) In addition, the index representing time is t, and the monitored equipment 21 at the time index t is expressed as follows: i Operating data of x (i) (t). Note that the operating data x (i) is collected by the driving data collection unit 201 for each sampling period. That is, the driving data collection unit 201 collects, for example, (x (1) ,···,x (m) ) is collected. If i ≠ i', the driving data x (i) The variables that make up the x (i') may be different from the variables that make up

[0028] The diagnosis unit 202 is a monitoring target facility 21 i For each (i=1, , m), the monitored equipment 21 i Operating data representing the normal state of x (i) The set of the abnormality diagnosis model is created by the MSPC method and stored in the diagnosis model storage unit 205. i Let M be the anomaly diagnosis model for (i=1, ,m). (i) This is expressed as:

[0029] In addition, the diagnosis unit 202 is a monitoring target facility 21 i For each (i=1, . . . , m), the abnormality diagnosis model M stored in the diagnosis model storage unit 205 is (i) and the driving data x of the latest time index stored in the driving data storage unit 204. (i) The Q value is calculated as an abnormality index value using the above and is stored in the diagnosis result storage unit 206. Here, generally, the abnormality diagnosis model M (i) (i=1, ,m) is the monitored equipment 21 i On the other hand, the Q value is generated when the monitored equipment 21 iCalculated sequentially while online (for example, operation data x (i) The abnormality index value is calculated sequentially for each sampling period. The abnormality index value is compared with a predetermined threshold value to determine whether the abnormality index value is equal to or smaller than the threshold value. i For example, the first and second thresholds are set to th1 and th2, respectively. (i) and th2 (i) (However, 0 <th1 (i) <th2 (i) ) as monitored equipment 21 i The Q value of the first threshold th1 (i) The following is "normal": the first threshold th1 (i) and the second threshold th2 (i) If it is less than or equal to the second threshold th2, it is a "warning". (i) If it exceeds this, it is diagnosed as “abnormal.”

[0030] Below, for i = 1,...,m, the operation data x (i) The Q value calculated from (t) is Q (i) If the time index t is not specified, it is expressed as Q (i) This is expressed as:

[0031] The display control unit 203 displays the information of each monitored facility 21 i While (i=1, ,m) is online, its Q value Q (i) (t) is sequentially plotted on the monitoring screen as the equipment status (for example, operation data x (i) At this time, the display control unit 203 uses the facility information stored in the facility information storage unit 207 to display the facility information of each monitored facility 21. i The Q value Q (i) In this way, the operator can easily see which equipment (t) is the most likely to be affected by an abnormality. i It becomes possible to easily check the Q values ​​of the elements from left to right.

[0032] The driving data storage unit 204 stores the driving data x collected by the driving data collection unit 201. (i)(i=1, . . . , m). That is, the driving data storage unit 204 stores (x (1) (t),...,x (m) (t)) is stored as time-series data. Note that the driving data x (i) If necessary, some pre-processing may be performed on the data, such as missing value interpolation and normalization.

[0033] The diagnosis model storage unit 205 stores the abnormality diagnosis model M created by the diagnosis unit 202. (i) Store (i = 1, , m).

[0034] The diagnosis result storage unit 206 stores the Q value Q calculated by the diagnosis unit 202. (i) (i=1, , m). That is, the diagnosis result storage unit 206 stores (Q (1) (t),...,Q (m) (t)) is stored as time series data.

[0035] The equipment information storage unit 207 stores information on each monitored equipment 21 i The facility information of each of the monitored facilities 21 (i=1, . . . , m) is stored. Here, as an example, m=8. An example of the facility information stored in the facility information storage unit 207 is shown in FIG. 4. As shown in FIG. 4, the facility information storage unit 207 stores the facility information of each of the monitored facilities 21 i The equipment information for each of the equipments (i=1, . . . , 8) is stored, and each piece of equipment information includes, for example, an equipment ID, an equipment name, a first threshold, a second threshold, and an impact degree. The equipment ID is stored in the monitored equipment 21. i The equipment name is identification information for identifying the monitored equipment 21. i The first threshold and the second threshold are the names of the monitored equipment 21 i The threshold value is used to diagnose abnormalities in the monitored equipment. iThe impact level is a numerical value that indicates the degree of the impact when an abnormality occurs in the monitored equipment 21. The impact level is determined and set manually, for example, according to the operational impact and cost impact that occur when an abnormality occurs in the monitored equipment 21. However, for example, when the operational impact and cost impact of the monitored equipment 21 are known, the impact level may be determined and set automatically in the order of the magnitude of the impact.

[0036] For example, the first line in the example shown in FIG. 4 is the equipment information of the monitored equipment 211, and the equipment information includes the equipment ID "1", the equipment name "equipment 1", the first threshold "th1 (1) ", the second threshold "th2 (1) 4 is the facility information of the monitored facility 212, and the facility information includes a facility ID of "2," a facility name of "facility 2," a first threshold value of "th1," and an impact level of "4." (2) ", the second threshold "th2 (2) " and impact level "1". The same is true for lines 3 to 8 in the example shown in FIG. 4. Note that in the example shown in FIG. 4, the impact level is expressed as a value quantified with an integer of 1 or more, but this is just one example, and it may be expressed as a value quantified with, for example, a real number.

[0037] The monitoring device 10 according to the present embodiment may have a functional unit and a storage unit that realize various functions in addition to the units shown in Fig. 3. For example, the monitoring device 10 according to the present embodiment may have a "post-processing unit" that realizes post-processing such as notifying the user of an "abnormality" diagnosis by the diagnosing unit 202 by sending an email or the like.

[0038] <Monitoring process> The monitoring process according to this embodiment will be described below with reference to FIG. 5. Here, the following steps S101 to S104 are performed by each of the monitored equipment 21. i Sequential execution during online operation (e.g., operation data x (i) In the following, the diagnosis unit 202 performs the abnormality diagnosis for each abnormality diagnosis model M (i) (i=1, ,m) is each monitored equipment 21 iThese abnormality diagnosis models are created offline. (i) is stored in the diagnostic model storage unit 205.

[0039] First, the diagnosis unit 202 calculates the driving data (x (1) (t),...,x (m) (t) is acquired (step S101).

[0040] Next, the diagnosis unit 202 uses the abnormality diagnosis model M stored in the diagnosis model storage unit 205. (i) (i=1, ,m) and the driving data (x (1) (t),...,x (m) (t)) and the Q value (Q (1) (t),...,Q (m) That is, the diagnosis unit 202 calculates an abnormality diagnosis model M (i) and driving data x (i) (t) and the Q value Q (i) Calculate (t).

[0041] Next, the diagnosis unit 202 calculates the Q value (Q (1) (t),...,Q (m) (t)) is stored in the diagnosis result storage unit 206 (step S103).

[0042] Then, the display control unit 203 uses the facility information stored in the facility information storage unit 207 to calculate the Q value (Q (1) (t),...,Q (m) (t)) is displayed on the monitoring screen as the equipment status (step S104). At this time, the display control unit 203 displays Q (i) (t) is drawn from the left. This allows the operator to draw each monitored equipment 21 i You can check the Q values ​​in real time in order of their impact.

[0043] <Example of equipment status drawing> An example of the equipment status displayed on the monitoring screen will be described below. FIG. 6 shows the equipment status when m=8 and the equipment information shown in FIG. 4 is stored in the equipment information storage unit 207. The equipment status 1100 shown in FIG. 6 shows the equipment status of each of the monitored equipment 21 with the equipment names "equipment 1" to "equipment 8". i Q value Q for (i=1, ,8) (i) A graph showing (t) and the first threshold th1 for it (i) and the second threshold th2 (i) In the example shown in Figure 6, Q (i) (t) is the "first threshold th1 (i) "Below", "First threshold th1 (i) and the second threshold th2 (i) "Second threshold th2 (i) The Q value is depicted in a different display manner (e.g., a different color, etc.) depending on whether the Q value is in an “abnormal”, “warning”, or “normal” state (i.e., whether the Q value is in an “abnormal”, “warning”, or “normal” state).

[0044] In this way, in the equipment status, the Q values ​​of the monitored equipment 21 are displayed from the left in descending order of the degree of influence of the monitored equipment 21. Generally, an operator checks the Q values ​​from left to right, so the equipment status 1100 as shown in Fig. 6 makes it possible to check preferentially the Q values ​​of the monitored equipment 21 with a high degree of influence. However, drawing the Q values ​​from the left in descending order of the degree of influence of the monitored equipment 21 is just one example, and for example, the Q values ​​may be drawn from the right by changing the settings by the operator.

[0045] <Modification> Below, some variations of this embodiment will be described.

[0046] Variation 1 In the above embodiment, the abnormality diagnosis model is created by the MSPC method, and the Q value is assumed as the abnormality index value, but the abnormality diagnosis model and the abnormality index value are not limited to this. For example, the abnormality diagnosis model may be created using LOF (Local Outlier Factor), One Class SVM, isolation forest, INNE (isolation using Nearest Neighbour Ensemble), etc. In addition, an appropriate index value that measures the degree of abnormality according to the abnormality diagnosis model may be used as the abnormality index value.

[0047] Variation 2 In the above embodiment, the Q values ​​of each monitored facility 21 are drawn from the left according to the influence of each monitored facility 21, but for example, the Q values ​​may be drawn from the left in descending order of the product of the influence and the Q value. More generally, the Q values ​​may be drawn from the left in descending order of the product of the weighting coefficient, the influence, and the Q value using a weighting coefficient predetermined for each monitored facility 21.

[0048] Variation 3 In the above embodiment, the degree of influence is fixed, but the degree of influence may change dynamically. For example, when the monitored equipment 21 has multiple operation modes, the degree of influence of the monitored equipment 21 may change according to the operation mode. Also, for example, when the monitored equipment 21 executes multiple processes, the degree of influence of the monitored equipment 21 may change according to the type of process. Note that an example of a case where multiple processes are executed is when the monitored equipment 21 executes both a "manufacturing process for product A" and a "manufacturing process for product B".

[0049] <Summary> As described above, the monitoring system 1 according to this embodiment can plot, as the equipment status, the abnormality index value when the monitored equipment 21 is diagnosed as abnormal, while taking into consideration the impact when an abnormality occurs in the monitored equipment 21. This allows the operator of the monitored equipment 21 to monitor the monitored equipment 21 with a high degree of impact with priority, and for example, enables the operator to quickly start preparatory work when an abnormality occurs, planning work for the occurrence of the abnormality, and the like.

[0050] The present invention is not limited to the above-described embodiments specifically disclosed, and various modifications, changes, combinations with known technologies, etc. are possible without departing from the scope of the claims.

[0051] [References] Reference 1: Manabu Kano, "Multivariate Statistical Process Control", Internet<URL:http: / / manabukano.brilliant-future.net / research / report / Report2005_MSPC.pdf> [Explanation of symbols]

[0052] 1. Surveillance System 10 Monitoring equipment 20 Facilities 21 Monitored Equipment 22 Measuring Instruments 23 Control device 30 Operator terminal 101 Input Device 102 Display device 103 External I / F 103a Recording media 104 Communication I / F 105 RAM 106 ROM 107 Auxiliary storage 108 processors 109 Bus 201 Driving Data Collection Division 202 Diagnostic Department 203 Display control unit 204 Operation data storage unit 205 Diagnostic Model Memory Unit 206 Diagnosis result storage unit 207 Equipment information storage section

Claims

1. a calculation unit that calculates a plurality of abnormality index values ​​for each of a plurality of monitored equipment by an abnormality diagnosis technique using a plurality of operation data collected from each of the plurality of monitored equipment; a display control unit that displays each of the plurality of abnormality index values ​​as an equipment status based on an influence degree that indicates a degree of influence when an abnormality occurs in the monitored equipment; An equipment status display device having

2. The display control unit is The equipment status display device according to claim 1 , wherein each of the plurality of abnormality index values ​​is displayed as the equipment status in descending order of the degree of influence.

3. 3. The equipment status display device according to claim 1, wherein the degree of influence is a value that quantifies an operational influence or a cost influence that occurs when an abnormality occurs in the monitored equipment.

4. The equipment status display device according to claim 3 , wherein the degree of influence dynamically changes depending on an operation mode of the monitored equipment or a type of process executed by the monitored equipment.

5. The display control unit is The equipment status display device according to claim 1 , further comprising: displaying, as the equipment status, each of the plurality of abnormality index values ​​in descending order of a product of the degree of influence and the abnormality index value.

6. The display control unit is 6. The equipment status display device according to claim 5, further comprising: displaying, as the equipment status, each of the plurality of abnormality index values ​​in descending order of a product of a weighting coefficient predetermined for each of the monitored equipment, the influence degree, and the abnormality index value.

7. a calculation step of calculating a plurality of abnormality index values ​​for each of a plurality of pieces of monitored equipment by an abnormality diagnosis technique using a plurality of pieces of operation data collected from each of the plurality of pieces of monitored equipment; a display control procedure for displaying each of the plurality of abnormality index values ​​as an equipment status based on an influence degree that indicates the degree of the influence when an abnormality occurs in the monitored equipment; The computer executes the equipment status display method.

8. a calculation step of calculating a plurality of abnormality index values ​​for each of a plurality of pieces of monitored equipment by an abnormality diagnosis technique using a plurality of pieces of operation data collected from each of the plurality of pieces of monitored equipment; a display control procedure for displaying each of the plurality of abnormality index values ​​as an equipment status based on an influence degree that indicates the degree of the influence when an abnormality occurs in the monitored equipment; A program that causes a computer to execute the following.

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