JP6143994B2 - Remote monitoring device, remote monitoring maintenance system, remote monitoring method, and remote monitoring program - Google Patents

Description

  The present invention relates to a remote monitoring device, a remote monitoring and maintenance system, a remote monitoring method, and a remote monitoring program that calculate a failure probability of a component included in a monitoring target device.

  The conventional remote monitoring and maintenance system calculates the future failure probability from the elapsed usage period of the parts included in the monitored device, calculates the maintenance cost for each part based on the calculated failure probability, and based on this maintenance cost Thus, the maintenance staff has determined the inspection time for inspecting the monitoring target device (for example, Patent Document 1).

JP 2009-217718 A

  The technique described in Patent Document 1 does not calculate a failure probability based on information (hereinafter, maintenance information) obtained when a maintenance staff visits the site and inspects parts of the monitoring target device. In general, the failure probability predicted from the maintenance information obtained when the maintenance staff inspects the failure is predicted from the device information transmitted from the monitored device (for example, information such as the elapsed usage time for each part). More accurate than probability. However, when the maintenance staff checks all parts for every inspection, it takes cost and time, and an efficient inspection work cannot be performed. On the other hand, if the inspection timing of the monitoring target device is determined based on the failure probability calculated only from the device information, an efficient inspection operation cannot be performed, for example, an unnecessary inspection operation occurs.

  A remote monitoring device, a remote monitoring and maintenance system, a remote monitoring method, and a remote monitoring program according to the present invention are made to solve the above-described problems, and include device information transmitted from a monitoring target device. The purpose is to calculate the failure probability using maintenance information obtained when maintenance personnel inspected.

  The remote monitoring device according to the present invention includes a failure probability calculation unit that calculates a failure probability for each part of the monitored device based on device information acquired from the monitored device, and maintenance that checks the monitored device A failure probability correction unit that corrects the failure probability based on maintenance information at the previous inspection of the worker, and a failure risk that calculates a failure risk at the next inspection based on the failure probability corrected by the failure probability correction unit And a calculating unit.

  The remote monitoring and maintenance system of the present invention includes a device information storage unit that stores device information acquired from a monitoring target device, a maintenance information storage unit that stores maintenance information at the time of a previous inspection of a maintenance person who checks the monitoring target device, and A failure probability calculation unit that calculates a failure probability for each part of the monitored device at the next inspection based on the device information, a failure probability correction unit that corrects the failure probability based on the maintenance information, and the failure Based on the failure probability corrected by the probability correction unit, the failure risk calculation unit that calculates the failure risk, and the failure risk calculated by the failure risk calculation unit among the components of the monitored device exceeds a threshold value A maintenance item selection unit that selects a maintenance item of a part as a priority maintenance item that needs to be inspected next time.

  According to the remote monitoring method of the present invention, a failure probability calculating step for calculating a failure probability for each part at the next inspection based on device information acquired from the monitored device, and a previous inspection of a maintenance worker who checks the monitored device A failure probability correction step for correcting the failure probability based on the maintenance information in the step, and a failure risk calculation step for calculating a failure risk based on the failure probability corrected in the failure probability correction step. And

  The remote monitoring program of the present invention includes a failure probability calculating step for calculating a failure probability for each part of the monitored device based on device information acquired from the monitored device, and maintenance for checking the monitored device A failure probability correcting step for correcting the failure probability based on maintenance information at the previous inspection of the worker, and a failure risk for calculating a failure risk at the next inspection based on the failure probability corrected in the failure probability correcting step And calculating step.

  Since the remote monitoring device, remote monitoring maintenance system, remote monitoring method, and remote monitoring program according to the present invention calculate the failure probability based on the maintenance information in addition to the device information, the failure probability calculated only by the device information More accurate failure probability can be calculated. Therefore, an accurate inspection time can be determined, and the inspection work can be performed efficiently.

1 is a configuration diagram of a remote monitoring and maintenance system according to Embodiment 1. FIG. 3 is a functional block diagram of a failure risk processing unit according to Embodiment 1. FIG. 4 is an operation flowchart of the remote monitoring and maintenance system according to the first embodiment. 6 is an operation flowchart for calculating a failure probability by the remote monitoring apparatus according to the first embodiment. It is a figure explaining the implementation aspect of the remote monitoring maintenance system which concerns on Embodiment 1. FIG. It is a block diagram of the remote monitoring maintenance system which concerns on Embodiment 2. FIG. 7 is an operation flowchart of the remote monitoring and maintenance system according to the second embodiment. It is a figure explaining the implementation aspect of the remote monitoring maintenance system which concerns on Embodiment 2. FIG. It is a block diagram of the remote monitoring and maintenance system which concerns on Embodiment 3. FIG. 12 is an operation flowchart when the remote monitoring and maintenance system according to the third embodiment classifies device information. 12 is an operation flowchart when the remote monitoring and maintenance system according to the third embodiment selects priority maintenance items. It is a hardware block diagram of the remote monitoring apparatus which concerns on Embodiment 1 to Embodiment 3.

Embodiment 1 FIG.
Hereinafter, the remote monitoring and maintenance system according to the first embodiment will be described with reference to FIG. FIG. 1 is a configuration diagram of a remote monitoring and maintenance system according to the first embodiment.

  In FIG. 1, the remote monitoring and maintenance system includes a monitoring target device 1a, a monitoring target device 1b, and a remote monitoring device 2. The monitoring target devices 1 a and 1 b are connected to the remote monitoring device 2 via the network 100. The monitoring target devices 1a and 1b are devices such as an elevator, for example. The remote monitoring device 2 is a device that monitors the monitored devices 1a and 1b, and calculates a failure risk for each component of the monitored devices 1a and 1b. This failure risk will be described later. In the following description, the number of monitored devices monitored by the remote monitoring device 2 will be described using two examples 1a and 1b. However, the remote monitoring and maintenance system includes two or more monitored devices. Even if it exists, it is feasible. Hereinafter, the monitoring target devices 1a and 1b and other monitoring target devices are collectively referred to as the monitoring target device 1.

  The remote monitoring device 2 includes a device information storage unit 23, a maintenance information storage unit 24, a maintenance information input unit 25, a failure risk processing unit 26, and a maintenance item selection unit 27.

  The device information storage unit 23 stores a device information DB (database). The device information DB includes device information transmitted from the monitoring target device 1. The device information is information transmitted from the monitoring target device 1, and corresponds to, for example, the number of times the elevator is started, the travel distance, the accumulated operation time, and the like.

  The maintenance information storage unit 24 stores a maintenance information DB. The maintenance information DB includes maintenance information obtained when a maintenance staff visits the site and inspects the parts of the monitoring target device 1. The maintenance information is, for example, the remaining thickness of the brake shoes of the elevator, the amount or deterioration of the gear oil of the hoisting machine, and the like.

  The maintenance information input unit 25 is an input unit that inputs the contents of maintenance work performed by maintenance personnel at each site as maintenance information.

  The failure risk processing unit 26 calculates the failure risk of the monitored device 1 at each site based on the contents of the device information DB and the maintenance information DB. The failure risk is an index for the maintenance personnel to determine which maintenance item should be inspected among the components constituting the monitored device 1, and is calculated for each component of the monitored device 1.

  The failure risk is calculated by the product of the failure probability obtained from the device information and the maintenance information and a risk value determined in advance for each component. The failure probability obtained from the device information and the maintenance information is calculated by the failure risk processing unit 26 calculating the failure probability based on the device information and correcting the failure probability based on the maintenance information obtained by the maintenance staff at the previous inspection. Calculated.

  It is generally known that the failure probability increases with the passage of time. The failure probability calculated based on the device information may be calculated using a general method such as a Weibull distribution. For a failure probability correction method based on maintenance information, for example, a threshold value related to maintenance information at the previous inspection may be set, and the failure probability may be corrected depending on whether the value indicated by the maintenance information is greater than or less than the threshold value. Specifically, the failure risk processing unit 26 may reduce the failure probability by 10% if the maintenance information at the time of the previous inspection is equal to or less than the threshold, and may add 10% if the maintenance information is equal to or greater than the threshold. That is, the failure risk processing unit 26 corrects the failure probability at the next inspection calculated based only on the device information with the correction value corresponding to the threshold value, and sets it as the failure probability at the next inspection. Therefore, if it is determined that the degree of wear of the brake or rope is small and the margin of the remaining portion is large based on the maintenance information obtained by the maintenance staff at the previous inspection, the failure probability related to the corresponding part is corrected to be low. Note that the failure risk processing unit 26 according to the present embodiment does not necessarily calculate the failure probability using the threshold value. For example, a relational expression between the maintenance information and the failure probability correction value is determined in advance. It is sufficient that the failure probability can be corrected based on the maintenance information. The threshold value and the relational expression may be determined based on simulations or empirical rules.

  The risk value is a value determined in advance for each component, and is set according to the risk when the component fails. The risk value is a value that can be arbitrarily changed by the designer and administrator of the remote monitoring and maintenance system. From various points of view, such as the risk of passengers when a component breaks down, the magnitude of damage to equipment, and repair costs It can be set. Thus, since the failure risk processing unit 26 calculates the failure probability based on the maintenance information in addition to the device information, the failure risk processing unit 26 can calculate a more accurate failure probability than the failure probability calculated based only on the device information. .

  Here, the configuration of the failure risk processing unit 26 will be described in detail with reference to FIG. FIG. 2 is a functional block diagram of the failure risk processing unit 26. In FIG. 2, the failure risk processing unit 26 includes a failure probability calculation unit 261, a failure probability correction unit 262, a risk value storage unit 263, and a failure risk calculation unit 264.

  The failure probability calculation unit 261 acquires device information from the device information DB of the device information storage unit 23 and calculates a failure probability for each component.

  The failure probability correction unit 262 acquires maintenance information from the maintenance information DB stored in the maintenance information storage unit 24, and corrects the failure probability calculated by the failure probability calculation unit 261 based on the maintenance information.

  The risk value storage unit 263 stores a risk value for each part.

  The failure risk calculation unit 264 calculates a failure risk based on the failure probability for each component corrected by the failure probability correction unit 262 and the risk value stored in the risk value storage unit 263.

  In FIG. 1, the maintenance item selection unit 27 selects maintenance items (priority maintenance items) related to parts that need to be inspected at the next inspection based on the failure risk calculated by the failure risk processing unit 26. When selecting a priority maintenance item, the maintenance item selection unit 27 selects a maintenance item so as to preferentially maintain an item with a high failure risk. For example, the maintenance item selection unit 27 calculates a failure risk X at the next inspection and a failure risk Y at the next inspection as the failure risk. Assuming that the failure risk threshold requiring maintenance is A, there are the following three patterns. (1) X <Y <A, (2) X <A <Y, (3) A <X <Y. In the case of (1), the risk of failure is low, and it is considered sufficient to inspect at the next inspection work. In this inspection work, the priority as a maintenance item is lowered. In the case of (2), the failure risk is low in the next inspection work, but the failure risk exceeds the threshold that requires maintenance in the next inspection work, so the priority is raised as the maintenance item for this time. In the case of (3), since it is an essential maintenance item in this inspection work, the priority is given the highest priority. That is, the maintenance item selection unit 27 determines the priority of the maintenance item according to the failure risk, and determines the priority maintenance item based on the priority and the threshold value. Thus, the maintenance item selection unit 27 selects the priority maintenance item based on both the failure risk X and the failure risk Y. For example, when selecting the priority maintenance item at the next inspection, the maintenance item selection unit 27 performs the inspection one after another. Priority maintenance items can be selected in consideration of sufficient items even if they are inspected from time to time, and maintenance personnel can be assigned to inspection work more efficiently.

  In the present embodiment, the maintenance item selection unit 27 is not necessarily limited to selecting priority maintenance items based on both the failure risk X at the next inspection and the failure risk Y at the next inspection. The priority maintenance item may be selected based only on the failure risk X at the time. That is, the maintenance item selection unit 27 compares the failure risk X at the next inspection calculated by the failure risk processing unit 26 with the threshold A, and selects a maintenance item related to a component with the failure risk X exceeding the threshold as a priority maintenance item. May be. Further, the maintenance item selection unit 27 may not necessarily select the priority maintenance item based on the failure risk threshold. For example, the maintenance item selection unit 27 selects priority maintenance items in order from items related to parts having a high failure risk, and appropriately determines items to be actually inspected at the next inspection according to constraints such as cost and the number of maintenance personnel. Also good.

  Next, the operation of the remote monitoring apparatus according to the first embodiment will be described with reference to FIGS. FIG. 3 is an operation flowchart of the remote monitoring apparatus according to the first embodiment. FIG. 4 is an operation flowchart in which the remote monitoring apparatus according to the first embodiment calculates a failure probability. As a premise for the following description, the device information storage unit 23 stores device information as a device information DB, and the maintenance information storage unit 24 stores maintenance information up to the previous inspection as a maintenance information DB. It is assumed that

  In ST1a, the failure probability calculation unit 261 acquires device information from the device information storage unit 23 (device information acquisition step).

  In ST1b, the failure probability correction unit 262 acquires maintenance information from the maintenance information storage unit 24 (maintenance information acquisition step).

  In ST2, the failure probability calculation unit 261 calculates a failure probability X at the next inspection for each part based on the device information acquired from the device information storage unit 23 and the maintenance information acquired from the maintenance information storage unit 24. Details of ST2 will be described with reference to FIG. In ST21 of FIG. 4A, the failure probability calculation unit 261 acquires device information from the device information storage unit 23, and calculates a failure probability at the next inspection for each component (failure probability calculation step). The failure probability correction unit 262 corrects the failure probability calculated by the failure probability calculation unit 261 based on the maintenance information for each component (failure probability correction step). For example, the failure probability correction unit 262 has a threshold value related to maintenance information at the time of the previous inspection, and corrects the failure probability at the next inspection calculated based on only the device information according to the threshold value. The failure probability X is calculated.

  In ST3, the failure probability calculation unit 261 calculates the failure probability Y at the time of the next inspection for each part based on the device information acquired from the device information storage unit 23 and the maintenance information acquired from the maintenance information storage unit 24. Details of ST3 will be described with reference to FIG. In ST31 of FIG. 4B, the failure probability calculation unit 261 calculates a failure probability for each part based on the device information acquired from the device information storage unit 23 (failure probability calculation step). In ST32, the failure probability correction unit 262 corrects the failure probability calculated by the failure probability calculation unit 261 based on the maintenance information for each component at the time of the previous inspection (failure probability correction step). For example, the failure probability correction unit 262 has a threshold value related to maintenance information at the previous inspection, corrects the failure probability at the subsequent inspection calculated based on only the device information according to the threshold, and The failure probability Y is calculated.

  In ST4 of FIG. 3, the failure risk calculation unit 264 acquires the risk value of the component for which the failure probability has been calculated, and calculates the failure risk by multiplying the failure probability X at the next inspection with the failure probability Y at the next inspection. X, failure risk Y is calculated (failure risk calculation step). The failure risk X and the failure risk Y are calculated for each part. The failure risk calculation unit 264 outputs the calculated failure risks X and Y to the maintenance item selection unit 27.

  In ST5, the maintenance item selection unit 27 selects a priority maintenance item for each component based on the failure risk X at the next inspection calculated for each component, the failure risk Y at the subsequent inspection, and the threshold A (priority). Maintenance item selection step). The maintenance staff goes to the site where the monitoring target device 1 is installed, and performs inspection work on the priority maintenance item selected by the maintenance item selection unit 27.

  Note that the order of ST2 and ST3 is not limited to this, and may be reversed. Also, ST3 does not necessarily have to be performed.

  As described above, since the remote monitoring and maintenance system according to the present invention calculates the failure probability based on the maintenance information in addition to the device information, the failure probability is calculated more accurately than the failure probability calculated based only on the device information. can do. Therefore, an accurate inspection time can be determined, and the inspection work can be performed efficiently.

  In this Embodiment, although the monitoring object apparatus 1 demonstrated using the example of an elevator, the monitoring object apparatus 1 may be apparatuses, such as not only an elevator but a car, a rail vehicle, and a plant.

  In the present embodiment, the configuration of the remote monitoring and maintenance system is not limited to that shown in FIG. FIG. 5 is a diagram for explaining an embodiment of the remote monitoring and maintenance system according to the first embodiment. In FIG. 5A, the maintenance item selection unit 27 is provided in the external maintenance item selection device 3. The maintenance item selection device 3 is, for example, a device managed by a maintenance company. In the remote monitoring and maintenance system shown in FIG. 5A, the failure risk processing unit 26 includes the device information acquired from the device information DB of the device information storage unit 23 and the maintenance information acquired from the maintenance information DB of the maintenance information storage unit 24. Based on the above, the failure risk is calculated, and the calculated failure risk is transmitted to the maintenance item selection unit 27 of the maintenance item selection device 3. In the case of the remote monitoring and maintenance system shown in FIG. 5A, the maintenance information input unit 25 may be provided in any of the remote monitoring device 2 and the maintenance item selection device 3, but the maintenance information input unit 25 is When the maintenance item selection device 3 is provided, the maintenance information needs to be transmitted from the maintenance information input unit 25 to the maintenance information storage unit 24 of the remote monitoring device 2.

  In the present embodiment, the configuration of the remote monitoring and maintenance system may be the configuration shown in FIG. In FIG. 5B, the device information storage unit 23 and the maintenance information storage unit 24 may be provided in the external server 4 installed outside the remote monitoring device 2. The failure risk processing unit 26 acquires device information from the device information storage unit 23 of the external server 4, acquires maintenance information from the maintenance information storage unit 24, and calculates a failure risk. In the remote monitoring and maintenance system shown in FIG. 5B, the device information storage unit 23 and the maintenance information storage unit 24 may be provided in different servers. As for the embodiments of the device information storage unit 23, the maintenance information storage unit 24, the failure risk processing unit 26, and the maintenance item selection unit 27 shown in FIG. 5, each configuration of the remote monitoring and maintenance system according to the following embodiment is also applied. It is the same.

Embodiment 2. FIG.
The remote monitoring and maintenance system according to the second embodiment is characterized in that maintenance personnel assigned to inspection work of priority maintenance items are selected based on the level of proficiency of maintenance personnel. Hereinafter, the configuration of the remote monitoring and maintenance system according to the second embodiment will be described with reference to FIG. FIG. 6 is a configuration diagram of a remote monitoring and maintenance system according to the second embodiment. In the description of FIG. 6, the components corresponding to the configuration of the remote monitoring and maintenance system according to the first embodiment are denoted by the same reference numerals and the description thereof is omitted.

  In FIG. 6, the maintenance work optimization device 5 includes a work proficiency level storage unit 51 and a maintenance work optimization unit 52.

  The work proficiency level storage unit 51 has a work proficiency level DB. The work proficiency level DB is a database in which the proficiency level of maintenance work determined from the years of maintenance work experience or the acquired skill level is associated with maintenance personnel. The acquired skill level is, for example, work qualification. The proficiency level may be set in advance by the administrator or designer of the remote monitoring and maintenance system.

  The maintenance work optimization unit 52 acquires priority maintenance items from the maintenance item selection unit 27 and refers to the work proficiency level DB of the work proficiency level storage unit 51 to assign maintenance personnel to be assigned to the inspection work of the priority maintenance items. Select. The maintenance work optimization unit 52 selects a maintenance person to be assigned to the inspection work of the priority maintenance item based on the failure risk of the parts related to the priority maintenance item and the proficiency level of the maintenance person. For example, parts that are not inspected at the time of the previous inspection and that have a long operation time after the inspection work (part A) are the same as parts A that have been inspected at the time of the previous inspection and that have been operated after the inspection work. With the component (component B), it is expected that the failure risk related to the component A is relatively higher than that of the component B. Accordingly, the maintenance item selection unit 27 is arranged so that the maintenance staff level assigned to the priority maintenance item related to the part A is higher than the maintenance level level of the maintenance staff assigned to the inspection of the priority maintenance item related to the part B. Is selected. Note that the maintenance work optimization unit 52 according to the present embodiment selects the maintenance personnel to be assigned to the priority maintenance items based on the failure risk and the level of proficiency of the maintenance personnel, but is not limited thereto. The maintenance item selection unit 27 may acquire the proficiency level of the maintenance staff from the work proficiency level DB, and assign it to the inspection work of the priority maintenance items from the maintenance level with high proficiency level. As described above, the maintenance work optimization unit 52 selects the maintenance staff to be assigned to the inspection work of the priority maintenance items according to the level of proficiency of the maintenance staff. Can be assigned to work. In addition, the maintenance work optimization unit 52 selects maintenance personnel to be assigned to the inspection work of the priority maintenance items based on the failure risk and the level of proficiency of the maintenance personnel, so that the inspection work for the priority maintenance items with a high failure risk is selected. Maintenance personnel with a high level of proficiency can be selected, maintenance personnel with a low level of proficiency can perform inspections more reliably and in a shorter time than inspection work, and more efficient and optimal maintenance can be realized. .

  Next, the operation of the remote monitoring and maintenance system according to the second embodiment will be described with reference to FIG. FIG. 7 is an operation flowchart of the remote monitoring and maintenance system according to the second embodiment. In the description of FIG. 7, components corresponding to the operations of the remote monitoring and maintenance system according to the first embodiment are denoted by the same reference numerals and description thereof is omitted.

  In ST6, the maintenance work optimization unit 52 acquires the priority maintenance item and the failure risk from the maintenance item selection unit 27 (priority maintenance item acquisition step). Note that the maintenance work optimization unit 52 according to the present embodiment does not necessarily need to acquire a failure risk, and may acquire at least priority maintenance items. In the following description, it is assumed that the maintenance work optimization unit 52 acquires both the priority maintenance item and the failure risk.

  In ST7, the maintenance work optimizing unit 52 refers to the work proficiency level storage unit 51 and acquires the proficiency level of maintenance personnel who can perform inspection work at the next inspection (skill level acquisition step).

  In ST8, the maintenance work optimization unit 52 selects a maintenance person to be assigned to the inspection work for the priority maintenance items of the parts based on the proficiency level of the maintenance person and the failure risk (maintenance person selection step). Specifically, the maintenance work optimization unit 52 assigns maintenance personnel with a high level of proficiency in order of priority maintenance items with a high component failure risk.

  As described above, the remote monitoring and maintenance system according to the second embodiment assigns maintenance personnel to inspection work for priority maintenance items based on the level of proficiency of maintenance personnel. Maintenance personnel with a high level of proficiency can be selected, and maintenance personnel with a low level of proficiency can perform inspections more reliably and in a shorter time than when performing inspection work, thereby realizing more efficient and optimal maintenance.

  Also in the present embodiment, the configuration of the remote monitoring and maintenance system is not limited to that shown in FIG. FIG. 8 is a diagram for explaining an embodiment of the remote monitoring and maintenance system according to the second embodiment. As shown in FIG. 8, the remote monitoring device 2 may include a work proficiency level storage unit 51 and a maintenance work optimization 52. The device information storage unit 23, the maintenance information storage unit 24, and the work proficiency level storage unit 51 may be provided in the external server 4 (see FIG. 5).

Embodiment 3 FIG.
The remote monitoring and maintenance system according to the third embodiment is characterized in that a risk value is determined based on a component failure history. Hereinafter, the configuration of the remote monitoring and maintenance system according to the third embodiment will be described with reference to FIG. FIG. 9 is a configuration diagram of a remote monitoring and maintenance system according to the third embodiment. In the description of FIG. 9, components corresponding to the configuration of the remote monitoring and maintenance system according to the first or second embodiment are denoted by the same reference numerals and description thereof is omitted. The configuration diagram of the failure risk processing unit 26 in FIG. 9 is the same as that in FIG.

  9, the remote monitoring and maintenance system according to the third embodiment includes a similar device classification unit 28, a plurality of device information storage units 23a, 23b, and 23c, and a failure history storage unit 29.

  The similar device classification unit 28 groups the monitoring target devices 1 for each similar device. The similar device here refers to a monitoring target device having similar operating conditions such as specifications and installation environment. As an example of grouping according to the environment in which the monitoring target device 1 is installed, for example, classification may be performed by an elevator in which a person such as an apartment lives and an elevator installed in a store or the like. As an example of grouping according to the specifications of the monitoring target device 1, for example, classification may be performed depending on whether an elevator for carrying a person or an elevator for carrying luggage. Since similar devices sometimes have similar failure occurrence timings and failure probabilities, more accurate failure risk can be calculated by managing the failure risk for each similar device. Note that it is sufficient that at least one monitoring target device 1 exists in the group of similar devices.

  The device information storage units 23 a, 23 b, and 23 c store the device information of the monitoring target device 1 for each group classified by the similar device classification unit 28. Similar to the device information storage unit 23 according to the first embodiment, each of the device information storage units 23a, 23b, and 23c has a device information DB. Note that the device information storage units 23a, 23b, and 23c are not necessarily configured by physically separated hardware, and may be stored in one storage device. In other words, the device information storage units 23a, 23b, and 23c only need to be stored so that the device information of the monitoring target device 1 can be identified as to which group it is classified by the similar device classification unit 28.

  The failure history storage unit 29 includes a failure history DB. The failure history DB stores a failure history of each monitored device 1 for each group classified by the device information storage units 23a, 23b, and 23c. In the failure history, for example, a failed component and information for identifying the monitoring target device 1 including the failed component are stored in association with each other. For example, an identification ID transmitted when the monitoring target device 1 transmits device information may be used as the information for identifying the monitoring target device 1.

  The failure risk processing unit 26 searches the failure history DB for a failure history related to the same component as the component for which the failure risk is calculated in the group to which the component for which the failure risk is calculated belongs. The failure risk processing unit 26 sets a risk value for a part based on the identified failure history. The failure history corresponds to, for example, the number of failures. When the failure risk processing unit 26 calculates the failure risk of the component A included in the monitored device 1a, the component A of the monitored device 1a and other monitored devices belonging to the same group as the monitored device 1a (not shown) The number of failures of the component A included in (1) is specified by searching the failure history DB. The failure risk processing unit 26 sets the risk value higher by a predetermined change value when the number of failures of the identified component A is larger than a predetermined threshold, and the number of failures of the component A is smaller than the threshold. In this case, the risk value is set low by a predetermined change value. Subsequently, the failure risk processing unit 26 calculates a failure risk based on the product of the failure probability and the risk value.

  In the failure risk processing unit 26, a plurality of failure frequency thresholds may be set. In this case, the change value of the risk value corresponding to the threshold value may be stored in the risk value storage unit 263 in advance.

  Also, the risk value itself corresponding to the failure frequency threshold value is stored in the risk value storage unit 263 in advance, and the failure risk processing unit 26 acquires the risk value corresponding to the failure frequency threshold value from the risk value storage unit 263. A failure risk may be calculated. In this case, the failure risk processing unit 26 may calculate the failure risk based on the product of the risk value corresponding to the component, the risk value corresponding to the number of failures, and the failure probability.

  The failure risk processing unit 26 may set the risk value or the change value of the risk value based on a preset relational expression between the number of failures and the risk value or the change value of the risk value. The threshold value and the relational expression may be determined based on simulations or empirical rules.

  That is, in the present embodiment, the failure risk processing unit 26 may set a risk value corresponding to the failure history regarding the component for which the failure probability has been calculated. As described above, the failure risk processing unit 26 determines the risk value based on the failure history of the parts in the similar device, so that it is possible to calculate the failure risk corresponding to the monitored device 1.

  Next, the operation when the remote monitoring and maintenance system according to the third embodiment classifies device information will be described using FIG. FIG. 10 is an operation flowchart when the remote monitoring and maintenance system according to the third embodiment classifies device information. In the following description, an example in which a risk value is set based on the number of failures as an example of a failure history will be described.

  In ST11 of FIG. 10, the similar device classification unit 28 acquires device information transmitted from the monitoring target device 1 and an identification ID of the monitoring target device (device information acquisition step).

  In ST12, the similar device classification unit 28 determines, based on the identification ID, to which group the monitoring target device 1 that has transmitted the device information belongs to each similar device (group determination step). In the group determination of the identification ID, the similar device classification unit 28 only needs to include a group DB (not shown) in which the group to which the monitoring target device 1 belongs and the identification ID are associated with each other. The similar device classification unit 28 refers to the group DB and determines to which group the acquired identification ID belongs. The similar device classification unit 28 outputs an identification ID and device information to the device information storage unit 23a, 23b, or 23c corresponding to the group obtained as a result of the determination.

  In ST13, the device information storage unit 23a, 23b, or 23c stores the acquired identification ID and device information in association with each other (device information storage step). The remote monitoring device 2 executes the operations of ST11 to ST13 each time device information is acquired from the monitoring target device 1.

  Next, the operation when the remote monitoring and maintenance system according to the third embodiment selects priority maintenance items will be described using FIG. FIG. 11 is an operation flowchart when the remote monitoring and maintenance system according to the third embodiment selects priority maintenance items. In the description of FIG. 11, components corresponding to the operations of the remote monitoring and maintenance system according to the first embodiment are denoted by the same reference numerals and description thereof is omitted.

  In ST1c, the failure risk calculation unit 264 searches the failure history DB, and specifies the number of failures of this component in the group of monitored devices 1 including the components for which the failure probability has been calculated in ST2 and ST3 (failure history search step) ).

  In ST1d, the failure risk calculation unit 264 sets the risk value of the component based on the specified number of failures (risk value setting step). Thereafter, the failure risk is calculated based on the risk value, similarly to the operation of the remote monitoring and maintenance system according to the first or second embodiment.

  As described above, since the remote monitoring and maintenance system according to the present embodiment determines the risk value based on the failure history of the parts, it is possible to calculate the failure risk according to the specifications of the monitored device 1 and the installation environment. It becomes possible. Therefore, even when the specifications and installation environment of the monitoring target device 1 are different, the optimal failure risk can be calculated.

  In the remote monitoring and maintenance system according to the third embodiment, the work proficiency level storage unit 51 and the maintenance work optimization unit 52 according to the second embodiment can be applied.

  In the above description, an example in which the risk value is set based on the number of failures as an example of the failure history has been described. However, the remote monitoring and maintenance system according to the present embodiment also uses the risk value based on the failure history other than the number of failures. Can be set. That is, the failure history is not limited to the number of failures as long as it is an element that affects the risk value.

  Hereinafter, the hardware configuration of the remote monitoring apparatus 2 according to the first to third embodiments will be described with reference to FIG. FIG. 12 is a hardware configuration diagram of the remote monitoring apparatus according to the first to third embodiments. In FIG. 12, the remote monitoring device 2 includes an input device 201, an output device 202, a storage device 203, and a processing device 204. The input device 201 is a device in which device information transmitted from the monitoring target device 1, maintenance information output from a maintenance worker or a maintenance company device (not shown), or maintenance personnel directly input maintenance information to the remote monitoring device 2. It is. For example, as shown in FIG. 5, the output device 202 transmits information such as failure risk from the remote monitoring device 2 when the remote monitoring device 2 and other devices (maintenance item selection device 3, etc.) are separated. It is a device to do. The storage device 203 is a device that executes the functions of the device information storage units 23, 23a, 23b, and 23c, the maintenance information storage unit 24, the failure history storage unit 29, the work proficiency level storage unit 51, and the risk value storage unit 263. . The processing device 204 is, for example, a CPU (Central Processing Unit), and includes a failure risk processing unit 26, a maintenance item selection unit 27, a similar device classification unit 28, a work proficiency level storage unit 51, a maintenance work optimization unit 52, a failure The functions of the probability calculation unit 261, failure probability correction unit 262, and failure risk calculation unit 264 are executed. The device information storage unit 23, the failure risk processing unit 26, the maintenance item selection unit 27, the similar device classification unit 28, the maintenance work optimization unit 52, the failure probability calculation unit 261, the failure probability correction unit 262, and the failure risk calculation unit 264 These functions may be configured by hardware, or can be realized by causing a computer such as the processing device 204 to execute a predetermined program.

1, 1a, 1b Monitoring target device, 2 Remote monitoring device, 3 Maintenance item selection device, 4 External server, 23 Device information storage unit, 24 Maintenance information storage unit, 26 Failure risk processing unit, 27 Maintenance item selection unit, 28 Similar Device classification unit, 29 Failure history storage unit, 51 Work proficiency level storage unit, 52 Maintenance work optimization unit, 261 Failure probability calculation unit, 262 Failure probability correction unit, 263 Risk value storage unit, 264 Failure risk calculation unit, 100 Network, 201 input device, 202 output device, 203 storage device, 204 processing device

Claims (9)

A failure probability calculation unit for calculating a failure probability for each component of the monitored device based on device information acquired from the monitored device;
A failure probability correction unit that corrects the failure probability based on maintenance information at the time of a previous inspection of a maintenance worker who checks the monitored device;
Based on the failure probability corrected by the failure probability correction unit, a failure risk calculation unit that calculates a failure risk at the next inspection,
A remote monitoring device comprising: A maintenance item selection unit that selects maintenance items related to components for which the failure risk calculated by the failure risk calculation unit exceeds a threshold among the components of the monitoring target device as a priority maintenance item that requires inspection work at the next inspection;
The remote monitoring apparatus according to claim 1, further comprising: The failure risk calculation unit
Based on the device information and the maintenance information, calculate the failure risk at the time of the next inspection for each component of the monitored device,
The maintenance item selection unit
The remote monitoring apparatus according to claim 2, wherein the priority maintenance item is selected based on a failure risk at the next inspection, a failure risk at the next inspection, and the threshold value. The failure risk calculation unit
The remote monitoring apparatus according to claim 1, wherein the failure risk is calculated based on the failure probability corrected by the failure probability correction unit and a risk value for each component. A work proficiency level storage unit that stores the proficiency level of maintenance personnel is provided.
The maintenance item selection unit
3. The remote monitoring according to claim 2, wherein a maintenance person to be assigned to an inspection work of the selected priority maintenance item is selected based on the maintenance degree of the maintenance person stored in the work proficiency level storage unit. apparatus. A failure history storage unit for storing a failure history for each part is provided,
The failure risk calculation unit
The remote monitoring apparatus according to claim 4, wherein the risk value is set based on the failure history stored in the failure history storage unit. A device information storage unit for storing device information acquired from monitored devices;
A maintenance information storage unit for storing maintenance information at the time of the previous inspection of the maintenance staff who inspects the monitoring target device;
A failure probability calculation unit for calculating a failure probability for each component of the monitored device at the next inspection based on the device information;
A failure probability correction unit that corrects the failure probability based on the maintenance information;
A failure risk calculation unit that calculates a failure risk based on the failure probability corrected by the failure probability correction unit;
A maintenance item selection unit that selects a maintenance item of a component whose failure risk calculated by the failure risk calculation unit exceeds a threshold among the components of the monitoring target device as a priority maintenance item that needs to be checked next time;
A remote monitoring and maintenance system. A failure probability calculating step for calculating a failure probability for each part at the next inspection based on the device information acquired from the monitored device;
A failure probability correction step of correcting the failure probability based on maintenance information at the time of a previous inspection of a maintenance worker who inspects the monitored device;
A failure risk calculating step for calculating a failure risk based on the failure probability corrected in the failure probability correcting step;
A remote monitoring method. A failure probability calculating step for calculating a failure probability for each part of the monitored device based on device information acquired from the monitored device;
A failure probability correction step of correcting the failure probability based on maintenance information at the time of a previous inspection of a maintenance worker who inspects the monitored device;
Based on the failure probability corrected in the failure probability correction step, a failure risk calculation step for calculating a failure risk at the next inspection;
A remote monitoring program for causing a computer to execute.

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