JP2023006804A - Temporary transfer planning system, control method, and program - Google Patents

Abstract

To make a temporary transfer plan with high precision.SOLUTION: A temporary transfer planning system (10) comprises: an operation situation acquisition part (11) which acquires an operation situation from a monitor targeted facility, which is an elevator facility whose operation situation can be remotely monitored; an operation situation estimation part (52) which estimates an operation situation of an unmonitored facility which is an elevator facility whose operation situation cannot be remotely monitored; a recovery target specification part (14) which specifies a recovery target from elevator facilities; and a search part (12) which searches an optimum temporary transfer plan which is an optimum or quasi-optimum solution for the temporary transfer plan that determines, by group, the combination of temporary transfer targets which are planned to be recovery targets to which a group consisting of one or a plurality of operators and performs recovery operation is sent, and the order of temporary transfers. The recovery target specification part specifies a recovery target from monitor targeted facilities corresponding to the operation situation acquired when a disaster occurs, and also specifies a recovery target from unmonitored facilities corresponding to the operation situation estimated on the basis of the level of disaster when the disaster occurs.SELECTED DRAWING: Figure 24

Description

The present invention relates to a system, a control method, and a program for making a dispatch plan for dispatching a worker to a restoration target where an event requiring restoration work has occurred.

Patent Literature 1 discloses a wide-area disaster recovery support system for elevators capable of predicting the stoppage of elevators due to an earthquake.

Japanese Patent No. 6122787

In the event of a disaster such as an earthquake that causes many elevators to stop or break down at the same time over a wide area, a dispatch plan stipulates the recovery targets and the order of dispatch for each work group that normally performs restoration work. Secondment of each working group will be arranged according to the Here, there are some elevator equipment whose operating conditions can be grasped in real time by remote monitoring, and there are those which cannot be grasped until they are contacted by telephone or the like because they are not subject to remote monitoring. Therefore, especially in the early stages after a disaster occurs, it is difficult to quickly grasp the overall picture of the suspended elevator equipment, and the secondment plan drawn up at this stage may lack accuracy.

An object of one aspect of the present invention is to formulate a highly accurate dispatch plan that takes into account the operating status of facilities not subject to remote monitoring when a disaster occurs.

In order to solve the above-described problems, a staffing planning system according to an aspect of the present invention acquires the operating status from a monitoring target facility that is an elevator facility capable of remotely monitoring the operating status among a plurality of elevator facilities located at different locations. an operation status acquisition unit, an operation status estimation unit for estimating the operation status of non-monitored equipment that is the elevator equipment whose operation status cannot be remotely monitored, and a restoration that identifies recovery targets from the elevator equipment. and an optimal solution or standard of a dispatch plan in which a combination of dispatch targets, which are restoration targets to which a group consisting of one or a plurality of workers is scheduled to be dispatched, and a dispatch order are determined for each group. a search unit that searches for an optimal seconding plan that is an optimal solution, wherein the restoration target identification unit identifies the restoration target from the monitoring target equipment according to the operating status acquired when a disaster occurs. In addition, when the disaster occurs, the recovery target is specified from the non-monitored equipment according to the estimated operating condition based on the degree of the disaster.

In order to solve the above-described problems, a control method according to an aspect of the present invention is a control method executed by one or more information processing devices, in which operating conditions of a plurality of elevator installations located at different locations are remotely controlled. An operation status acquisition step of acquiring an operation status from the monitoring target equipment that is the elevator equipment that can be monitored, and an operation status of estimating the operation status of the non-monitored equipment that is the elevator equipment that cannot be remotely monitored for the operation status among the elevator equipment. A combination of an estimation process, a restoration target identification process for identifying a restoration target from among the elevator equipment, and a secondment target that is a recovery target to which a group consisting of one or more workers to perform restoration work is scheduled to be seconded, and a search step of searching for an optimal dispatch plan that is an optimal solution or a quasi-optimal solution of the dispatch plan in which the order of dispatch is determined for each group, and the recovery target identification step includes the operation status acquired when the disaster occurred. and specifies the recovery target from among the non-monitoring facilities according to the estimated operating conditions when the disaster occurs.

The secondment planning system according to each aspect of the present invention may be realized by a computer. In this case, the secondment planning system is realized by the computer by operating the computer as each part (software element) included in the secondment planning system. The program of the secondment planning system and the computer-readable recording medium recording it are also included in the scope of the present invention.

According to one aspect of the present invention, it is possible to formulate a highly accurate dispatch plan that takes into account the operational status of facilities not subject to remote monitoring when a disaster occurs.

1 is a block diagram showing an example of a schematic configuration of a learning model generation device according to Embodiment 1 of the present invention; FIG. FIG. 4 is a diagram showing an example of data stored in a disaster record database; FIG. It is a figure which shows the example of the data structure of the seismic intensity of each place. FIG. 4 is a diagram showing an example of a data structure of shake characteristics; It is a figure which shows the example of the data memorize|stored in the elevator equipment installation information database. It is an image diagram showing the positional relationship between the epicenter of an earthquake that occurred in the past and elevator equipment. It is a figure which shows the example of the data memorize|stored in the driving|running condition information database. It is a figure which shows the example of the data structure of a driving situation. 6 is a flowchart showing an example of the flow of learning model generation processing by a learning model generation device; FIG. 4 is a block diagram showing an example of a schematic configuration of a learning model generation device according to Embodiment 2 of the present invention; It is a figure which shows the example of the data memorize|stored in the elevator equipment installation information database. It is an image diagram showing the positional relationship between the epicenter of an earthquake that occurred in the past and elevator equipment. It is a figure which shows the example of the data memorize|stored in the driving|running condition information database. FIG. 11 is a block diagram showing an example of a schematic configuration of a driving situation estimation device according to Embodiment 3 of the present invention; It is a figure which shows the example of the data structure of the disaster occurrence information distributed from the disaster occurrence information distribution apparatus. It is a figure which shows the example of the data structure of the seismic intensity of each place. FIG. 4 is a diagram showing an example of a data structure of shake characteristics; It is a figure which shows the example of the location information of a noted elevator installation, building information, and installation information. It is an image diagram showing the positional relationship between the epicenter of the latest earthquake and elevator equipment. 6 is a flowchart showing an example of the flow of processing for estimating the operating condition of the elevator installation of interest by the operating condition estimating device; It is a figure which shows an example of the estimation result output from a driving condition estimation apparatus. It is a block diagram which shows the outline|summary of the maintenance system which concerns on Embodiment 4 of this invention. FIG. 11 is a flow chart showing processing executed by a secondment support system according to Embodiment 4 of the present invention; FIG. FIG. 11 is a block diagram showing the essential configuration of a secondment planning system according to Embodiment 4 of the present invention; FIG. 10 is a diagram illustrating an example of the data structure of a restoration target list; It is a figure which shows an example of the procedure of the search which a search part performs. It is a figure which shows an example of the procedure of the search which a search part performs. It is a figure which shows an example of the data structure of an optimal secondment plan. It is a figure which shows an example of a temporary transfer plan screen. 1 is a block diagram showing an example of the hardware configuration of the system or device of the present invention; FIG.

[Embodiment 1]
An embodiment of the present invention will be described in detail below with reference to FIGS. 1 to 9. FIG.

(Configuration of learning model generation device 4)
First, FIG. 1 shows the configuration of the learning model generation device 4 that performs machine learning for generating the learning model 451 that outputs the operating status of the elevator equipment using the location information of the elevator equipment and the disaster information as input data. will be used for explanation. FIG. 1 is a block diagram showing an example of a schematic configuration of a learning model generation device 4 according to Embodiment 1 of the present invention. Here, the elevator equipment is typically a passenger conveyor, an elevator, or the like.

The learning model generation device 4 may include a control section 40 and a storage section 45 . The control unit 40 may be, for example, a CPU (Central Processing Unit). The control unit 40 controls to execute processing of each function provided in the learning model generation device 4 . The storage unit 45 is a storage device in which various computer programs read by the control unit 40, data used in various processes executed by the control unit 40, and the like are stored.

In this specification, the learning model generating device 4 capable of generating teacher data for generating the learning model 451 will be described as an example, but the invention is not limited to this. For example, the learning model generation device 4 may store teacher data (not shown) generated in advance by another device in the storage unit 45, and use this to generate the learning model 451. . When this configuration is adopted, the learning section 42 may read out and use the teacher data stored in the storage section 45 . Therefore, in the learning model generation device 4, the later-described teacher data generation unit 41 is not an essential component.

The control unit 40 has a teacher data generation unit 41 and a learning unit 42 .

The learning unit 42 performs machine learning using the teacher data to generate a learning model 451 that outputs the operating status of the elevator installation of interest using the location information of the elevator installation of interest and the disaster information as input data. The training data includes location information indicating the location of the elevator equipment, disaster information including the extent of the disaster at the location, and operating status information indicating the operating status of the elevator equipment when the disaster occurred. Here, the elevator equipment of interest is intended to be an elevator equipment whose operation status is to be estimated by the learning model when a disaster occurs.

The severity of the disaster is defined as (1) the seismic intensity at the location of the elevator equipment, or (2) the magnitude of the earthquake at the location of the elevator equipment calculated from the magnitude of the epicenter, the depth of the epicenter, and the distance from the epicenter. It can be of any size.

The teacher data generation unit 41 generates teacher data for generating the learning model 451 . For example, the training data generation unit 41 may use disaster records of past disasters acquired from the disaster record database 6a to generate disaster information including the extent of the disaster at the location of the elevator equipment. The disaster record database 6a may be, for example, a database managed by the Japan Meteorological Agency. Further, the training data generating unit 41 may acquire location information indicating the location of the building where the elevator equipment is installed (that is, the location of the elevator equipment) from the elevator equipment installation information database 6b. The elevator equipment installation information database 6b may be, for example, a database managed by a business establishment that undertakes the installation of elevator equipment. Further, the teaching data generation unit 41 may acquire operating status information indicating the operating status of the elevator equipment when past disasters occurred from the operating status information database 6c. The operating status information database 6c may be, for example, a database managed by an office that undertakes management and inspection of elevator equipment.

Specific examples of disaster information, location information, and driving status information will be described below.

[Disaster Information]
First, disaster information will be described using FIG. 2 while referring to FIGS. 3 and 4. FIG. FIG. 2 is a diagram showing an example of data stored in the disaster record database 6a. Here, an earthquake is taken as an example for explanation, but the present invention is not limited to this. Disasters may be, for example, heavy rains, typhoons, tsunamis, volcanic activity, and the like. These can be disasters that may cause the power supply to the elevator equipment to stop or the elevator equipment to stop in an emergency. In the disaster record database 6a, data relating to the date and time of occurrence, the name of the epicenter, the maximum seismic intensity, the epicenter and the depth of the epicenter, the seismic intensity 61 of each place, and the characteristics 62 of shaking are recorded in correspondence with each disaster. As shown in FIG. 2, each disaster may be given a disaster ID, which is a unique identification number. The disaster ID may be a nickname given to each disaster. For example, if the disaster is a typhoon, each typhoon may be given a unique name.

Here, a more specific description will be given by taking as an example an earthquake assigned a disaster ID of "EQ2003**" (hereinafter referred to as "earthquake EQ2003**") in FIG. Earthquake EQ2003** is an earthquake that occurred "off the coast of Z prefecture" on "March 25, 2020." The maximum seismic intensity of earthquake EQ2003** is "4", and the magnitude indicating the scale of the earthquake is "6.2". The epicenter of the earthquake EQ2003** is "North latitude, Zzz degree east longitude", and the depth of the epicenter is "40km".

The seismic intensity 61 in each place may be seismic intensity information observed at various observation points when the earthquake EQ2003** occurred, and as shown in FIG. Municipalities may be associated with each other. According to Figure 3, a maximum seismic intensity of 4 was observed in "Z Prefecture ** City" and "Z Prefecture A City", etc., and a seismic intensity of 3 was observed in "Z Prefecture D City" and "Z Prefecture B City". .

The sway characteristics 62 may include information indicating the sway direction, acceleration, and sway period observed in earthquake EQ2003**. As shown in FIG. 4, the shake characteristic 62 records the acceleration of the shake observed when the earthquake EQ2003** occurred for each of the north-south component, east-west component, and vertical component. In the example shown in FIG. 4, the sway characteristics 62 include the combined maximum acceleration of the sway "( **Gal)” is also recorded. The sway characteristics 62 may include observed sway magnitude (amplitude), sway period, and the like. In the example shown in FIG. 4, the shaking characteristic 62 records that the shaking period was "0.8 sec." Note that the shaking characteristics 62 may record the shaking characteristics in each region where the shaking was observed for each region.

Elevator equipment may be provided with a sway sensor that detects the magnitude of the sway and the acceleration of the sway. Therefore, the teacher data generator 41 may use the magnitude and acceleration of the shaking detected by the shaking sensor provided in the elevator equipment as the degree of the disaster. On the other hand, in the case of an elevator facility that is not equipped with such sensors, the training data generation unit 41 may calculate the extent of the disaster based on the disaster record and the location information described later.

[Location information]
Next, location information will be described using FIG. 5 while referring to FIG. FIG. 5 is a diagram showing an example of data stored in the elevator equipment installation information database 6b. In the elevator equipment installation information database 6b, the location of the building where the elevator equipment is installed is recorded in association with each installed elevator equipment. In addition, as shown in FIG. 5, an elevator equipment ID, which is a unique identification number, may be assigned to each installed elevator equipment. According to FIG. 5, the elevator equipment whose elevator equipment ID is "EV001" (hereinafter referred to as elevator equipment EV001) is installed in "Building B" in "1-chome A-cho, ** city, Z prefecture." It is An elevator facility with an elevator facility ID of "EV026" (hereafter referred to as elevator facility EV026) is installed in "L Heights" in "2*No.*, D City, Z Prefecture".

FIG. 6 is an image diagram showing the positional relationship between epicenters of past earthquakes and elevator equipment. Figure 6 shows the epicenter (indicated by "X" in the figure) of earthquake EQ2003** (see Figure 2), "Z Prefecture ** City" facing "XX Sea", and "Z Prefecture ** City". ”, “D city in Z prefecture” and “F city in Z prefecture” are shown. FIG. 6 also shows the locations of the elevator installation EV001 and the elevator installation EV026. Note that major roads are also illustrated in FIG. In FIG. 6, the distance from the epicenter of earthquake EQ2003** to the elevator installation EV001 is shorter than the distance from the epicenter of earthquake EQ2003** to the elevator installation EV026. A seismic intensity of "4" was observed in "Z Prefecture ** City", which is close to the epicenter, and a seismic intensity of "3" was observed in "Z Prefecture D City" (see Figure 3).

The training data generation unit 41 may use the seismic intensity at the location of each elevator installation, which is specified based on the seismic intensity of each place included in the disaster information, as the degree of the disaster. Alternatively, the training data generation unit 41 may generate (1) the location of the epicenter, the magnitude indicating the scale of the earthquake, and the depth of the epicenter included in the disaster information, and (2) the distance between the location of each elevator equipment and the epicenter. You may use the magnitude|size of the shaking in the location of each elevator installation calculated from , as a degree of disaster.

[Driving status information]
Next, the driving situation information will be explained using FIG. 7 while referring to FIG. 8 . FIG. 7 is a diagram showing an example of data stored in the driving situation information database 6c. The operation status information database 6c records the operation status of elevator equipment for each disaster that occurred in the past.

The driving situation 63 when earthquake EQ2003** occurs will be described as an example with reference to FIG. FIG. 8 is a diagram showing an example of the data structure of the driving situation 63. As shown in FIG. Earthquake EQ2003**, as shown in FIG. 2, is an earthquake that occurred "off the coast of Z prefecture" on "March 25, 2020." The operating status 63 records the operating status of each elevator equipment when EQ2003** occurs. Here, the operating status 63 may include at least normal operation and stop. Note that the operation status 63 may record the results of work (for example, recovery work) performed on each elevator installation. For example, FIG. 8 records that the elevator installation EV001 stopped when the earthquake EQ2003** occurred, and that restoration work was performed on March 27, 2020. In addition, FIG. 8 records that the elevator equipment EV026 was not stopped when the earthquake EQ2003** occurred and was operating normally, and that only inspection was performed without restoration work being performed. .

Elevator equipment includes monitored equipment whose operating conditions can be remotely monitored and non-monitored equipment whose operating conditions cannot be remotely monitored. There is no need to actually go to the location to check the operating status of the equipment to be monitored. On the other hand, in the case of facilities not subject to monitoring, the operator accepts calls (callbacks) regarding the operating status from the owner or user of the facility via telephone or other means of communication, or the workers at the office actually visit the location. It is necessary to confirm the driving situation and the damage situation.

(Processing for generating learning model 451)
Next, processing for generating the learning model 451 will be described using FIG. FIG. 9 is a flowchart showing an example of the flow of processing for generating the learning model 451 by the learning model generation device 4. As shown in FIG.

First, the training data generator 41 acquires a disaster record, location information indicating the location of the elevator equipment, and operating status information indicating the operating status of the elevator equipment when the disaster occurred (step S41).

Subsequently, the training data generation unit 41 generates training data including location information, disaster information including the extent of the disaster at the location of the elevator equipment, and driving status information (step S42).

Next, the learning unit 42 inputs disaster information and location information to learning model candidates. Here, the learning model candidate is intended to be a learning model for which machine learning has not been completed. When predetermined machine learning is completed, the learning model candidate is stored in the storage unit 45 as a learning model 451 (learned model). Here, the machine learning algorithm for generating the learning model 451 is not limited to this, but for example, a neural network can be used.

The learning unit 42 obtains an estimation result obtained by the learning model candidate estimating the operation status of the elevator equipment corresponding to the input disaster information and location information, and the operation of the elevator equipment associated with the input disaster information and location information. The error is calculated by comparing with the situation information (step S44). The learning unit 42 updates the learning model candidates so that the error calculated in step S44 is minimized (step S45).

Updating the learning model candidate may include performing the following so as to minimize the error between the estimation result estimated by the learning model candidate and the driving situation information.
- Updating learning model candidates by updating weights between nodes, hyperparameters, etc. - Generating new learning model candidates To update learning model candidates, an error backpropagation method or the like may be applied.

When the predetermined machine learning is completed, the learning unit 42 stores the learning model candidate at that point in the storage unit 45 as the learning model 451 .

The learning model generation device 4 includes location information indicating the location of the elevator equipment, disaster information including the extent of the disaster at the location, and operating status information indicating the operating status of the elevator equipment when the disaster occurred in the past. A learning model 451 is generated by machine learning using data. When a new disaster occurs, the learning model 451 generated in this way estimates the operating status of the elevator equipment in response to input of the location information of the elevator equipment and the disaster information of the disaster that has occurred. You can output the result. The learning model 451 can be applied to the operating status estimation device 5 that estimates the operating status of each elevator facility when a disaster occurs based on the operating status of each elevator facility when a disaster occurred in the past. The driving situation estimation device 5 will be described later (see FIG. 14).

[Embodiment 2]
A learning model generation device 4a capable of generating a learning model 451a capable of more accurately estimating the operating conditions of elevator equipment when a disaster occurs will be described with reference to FIGS. 10 to 13. . For convenience of description, members having the same functions as those of the members described in the above embodiments are denoted by the same reference numerals, and description thereof will not be repeated.

(Configuration of learning model generation device 4a)
The configuration of the learning model generation device 4a that performs machine learning for generating the learning model 451a that outputs the operating status of the elevator equipment using the location information of the elevator equipment and the disaster information as input data will be described with reference to FIG. explain. FIG. 10 is a block diagram showing an example of a schematic configuration of a learning model generation device 4a according to Embodiment 2 of the present invention.

The learning model generation device 4 a may include a control section 40 a and a storage section 45 . The control unit 40a may be, for example, a CPU. The control unit 40a controls to execute processing of each function provided in the learning model generation device 4a. The storage unit 45 is a storage device that stores various computer programs read by the control unit 40a, data used in various processes executed by the control unit 40a, and the like.

The control unit 40a includes a teacher data generation unit 41a and a learning unit 42a.

The learning unit 42a performs machine learning using the teacher data to generate a learning model 451a that outputs the operating status of the elevator equipment of interest, using the location information of the elevator equipment of interest and the disaster information as input data. The training data may include at least one of facility information, building information, and driving situation information in addition to location information, disaster information, and driving situation information.

Here, the equipment information is information indicating at least one of the model and specifications of the elevator equipment. The building information is information indicating at least one of the construction completion date and earthquake resistance specifications of the building in which the elevator equipment is installed. The peripheral operating status information is information indicating the operating status of peripheral facilities, which are elevator facilities located within a predetermined range from the elevator facility and whose operating status can be remotely monitored, when a disaster occurs.

FIG. 10 shows a learning model generation device 4a capable of generating teacher data including location information, disaster information, driving situation information, facility information, building information, and peripheral driving situation information. The teacher data generation unit 41a generates teacher data for generating the learning model 451a. For example, the training data generation unit 41a may acquire location information, facility information, and building information indicating the location of the building where the elevator facility is installed (that is, the location of the elevator facility) from the elevator facility installation information database 6b. Further, the teacher data generator 41 may acquire the driving situation information and the peripheral driving situation information from the driving situation information database 6c.

Elevator equipment includes elevator equipment that has a controlled operation function to make an emergency stop in the event of a disaster, and elevator equipment that does not have a controlled operation function. Therefore, the training data used to generate the learning model 451 may further include equipment information indicating at least one of the model and specifications of the elevator equipment.

Seismic standards that buildings must meet are reviewed and subject to change. Buildings completed before the change in earthquake resistance standards meet the old earthquake resistance standards, and buildings completed after the change in earthquake resistance standards meet the new earthquake resistance standards. Thus, if the completion date of a building is known, it is possible to determine whether the earthquake resistance standard applied to the building is the old earthquake resistance standard or the new earthquake resistance standard. Seismic specifications include seismic isolation and seismic structures. Seismic resistance grades 1 to 3 can be applied to housing earthquake resistance specifications. Even buildings to which the old seismic standards were applied may meet the new seismic standards by implementing seismic reinforcement work. Therefore, the training data used to generate the learning model 451 may include building information indicating at least one of the construction completion date and earthquake resistance specifications of the building in which the elevator equipment is installed.

In addition, when a disaster occurs, the extent to which the disaster affects the operating conditions of elevator equipment is also affected by the type of structure of each building. Examples of structural types include reinforced concrete construction (RC construction), steel frame construction (S construction), steel frame reinforced concrete construction (SRC construction), and the like. Buildings with different structural types have different magnitudes of shaking during an earthquake. Therefore, the building information used for the teacher data used to generate the learning model 451 may include the structural type of the building in which the elevator equipment is installed.

As described above, elevator equipment includes monitored equipment, which is elevator equipment whose operating conditions can be remotely monitored, and unmonitored equipment, which is elevator equipment whose operating conditions cannot be remotely monitored. Therefore, the training data used by the learning model generation device 4a to generate the learning model 451a is located within a predetermined range from the elevator equipment, and the operating status of the peripheral equipment, which is the elevator equipment, which can be remotely monitored when a disaster occurs. may include peripheral driving situation information indicating the driving situation of the

The operational status of non-monitored equipment cannot be known until the owner or user of the building contacts him or he actually confirms it on site. However, when a disaster occurs, the damage status and operating status of nearby facilities can be used as a reference for the damage status and operating status. Since the operating status of the monitoring target equipment is constantly monitored remotely, the operating status is also notified to the business office when an earthquake occurs. Therefore, it is possible to improve the certainty of estimating the operating status of the non-monitoring facility by also considering the operating status of the peripheral facilities of the non-monitoring facility.

Specific examples of facility information, building information, and surrounding driving status information will be described below.

[Equipment information and building information]
First, facility information and building information will be described with reference to FIG. FIG. 11 is a diagram showing an example of data stored in the elevator equipment installation information database 6b. In the elevator equipment installation information database 6b, in addition to the location of the building where the elevator equipment is installed, equipment information and building information are recorded in association with each elevator equipment. Each elevator equipment may include information indicating whether it is a monitored equipment that can be remotely monitored or a non-monitored equipment that cannot be remotely monitored.

According to FIG. 11, the elevator equipment EV001 is installed in a “reinforced concrete (RC)” building completed on “**month**day, 1979”. This building complies with the old seismic standards. The model of the elevator equipment EV001 is "A03", and its specification is provided with "controlled operation function". The elevator equipment EV002 is installed in a "reinforced steel concrete (SRC)" building that was completed on "**month**day, 1979". This building complies with the old seismic standards. The model of the elevator equipment EV002 is "C05", and its specification is provided with "controlled operation function". The elevator equipment EV010 is installed in a “reinforced concrete (RC)” building completed on “** month ** day, 2015”. This building complies with the new seismic standards. The model of the elevator equipment EV010 is "D01", and its specification is provided with "controlled operation function". Elevator equipment EV026 is installed in a “steel-framed (S)” building that was completed on “**month**day, 2018”. This building complies with the new seismic standards. The model of the elevator equipment EV026 is "P12", and its specifications do not include the "controlled operation function".

[Peripheral driving status information]
According to FIG. 11, the elevator installation EV002 and the elevator installation EV010 are facilities to be monitored, and the elevator installation EV001 and the elevator installation EV026 are facilities not to be monitored. The peripheral operating status information will be explained using the positional relationship of these elevator installations. FIG. 12 is an image diagram showing the positional relationship between epicenters of past earthquakes and elevator installations EV001, EV002, EV010, and EV026. Both the elevator installation EV001 and the elevator installation EV002 are located in ** city in Z prefecture. The elevator installation EV010 is located in F City, Z Prefecture, and the elevator installation EV026 is located in D City, Z Prefecture. Equipment to be monitored is indicated by black circles, and equipment not to be monitored is indicated by white circles.

As shown in FIG. 12, the elevator installation EV002 is positioned within a predetermined range (indicated by a dashed circle in the figure) from the elevator installation EV001. Moreover, since the elevator installation EV002 is a facility to be monitored, the elevator installation EV002 is a peripheral facility of the elevator installation EV001. Similarly, the elevator installation EV010 is located within a predetermined range (indicated by a dashed circle in the figure) from the elevator installation EV026. Moreover, since the elevator installation EV010 is a facility to be monitored, the elevator installation EV010 is a peripheral facility of the elevator installation EV026.

The teacher data generator 41a may acquire the driving situation information and the peripheral driving situation information from the driving situation information database 6c. FIG. 13 is a diagram showing an example of data stored in the driving situation information database 6c. The operating statuses of the elevator installation EV002 and the elevator installation EV010 are peripheral operating status information of the elevator installation EV001 and the elevator installation EV026, respectively.

[Embodiment 3]
By adopting the learning models 451 and 451a generated by the learning model generation devices 4 and 4a according to the above-described embodiments, it is possible to realize the operating situation estimation device 5 capable of estimating the operating situation of elevator equipment. The driving situation estimation device 5 will be described below with reference to FIGS. 14 to 21. FIG. For convenience of description, members having the same functions as those of the members described in the above embodiments are denoted by the same reference numerals, and description thereof will not be repeated.

(Configuration of Driving Situation Estimating Device 5)
First, using the learning models 451 and 451a, the location information of the elevator installation of interest and the disaster information as input data, the configuration of the operating situation estimation device 5 that estimates the operating situation of the elevator installation of interest will be described with reference to FIG. explain. FIG. 14 is a block diagram showing an example of a schematic configuration of the driving situation estimation device 5 according to Embodiment 3 of the present invention. Here, the driving situation estimation device 5 to which the learning model 451a is applied will be described as an example. Each function of the driving situation estimation device 5 can be realized by replacing the learning model 451a with the learning model 451 in the following description.

The driving situation estimation device 5 may include a control section 50 and a storage section 54 . The control unit 50 may be, for example, a CPU. The control unit 50 controls to execute processing of each function provided in the driving situation estimation device 5 . The storage unit 54 is a storage device in which various computer programs read by the control unit 50, data used in various processes executed by the control unit 50, and the like are stored.

In this specification, the driving situation estimation device 5 having the function of generating input data will be described as an example, but the present invention is not limited to this. For example, the driving situation estimation device 5 may be configured to acquire input data generated in advance by another device and input this data to the learning model 451a. When this configuration is adopted, the learning section 42 may read out and use the teacher data stored in the storage section 45 . Therefore, in the driving situation estimation device 5, the later-described input data generation unit 51 is not an essential component.

The controller 50 includes an input data generator 51 , an estimator 52 and an output controller 53 .

The input data generator 51 generates input data to be input to the learning model 451a. For example, the input data generation unit 51 may use the disaster occurrence information about the disaster that has occurred from the disaster occurrence information distribution device 6d to generate disaster information including the extent of the disaster at the location of the elevator installation of interest. The disaster occurrence information distribution device 6d may be a device that quickly distributes information on disasters that have occurred. The disaster occurrence information may be, for example, information included in an emergency bulletin distributed by the Meteorological Agency. The input data generation unit 51 may also acquire peripheral operating status information indicating the operating status of peripheral facilities located within a predetermined range from the elevator facility of interest from the elevator facility remote monitoring device 6e. The elevator equipment remote monitoring device 6e may be, for example, a device managed by a business office that undertakes management of the equipment to be monitored. The input data generating unit 51 may also acquire the location information, building information, and equipment information of the elevator equipment of interest from the elevator equipment installation information database 6b.

The estimation unit 52 estimates the probability of the operating status of the elevator installation of interest. The estimating unit 52 inputs input data to the learning model 451a, and outputs output data that is the result of estimating the operation status of the elevator installation of interest.

The output control unit 53 outputs the output data from the estimation unit 52 to an external device. For example, the output control unit 53 causes the display device 9 to display the estimation result output by the estimation unit 52 . Here, the display device 9 may be a display that is communicably connected to the driving situation estimation device 5 by wire or wirelessly. In one example, the driving situation estimation device 5 may be a personal computer and a tablet terminal, and in this case, the display device 9 may be a display included in the personal computer and the tablet terminal. Further, the output control unit 53 may store the estimation result output by the estimation unit 52 in the storage unit 54 of the driving situation estimation device 5 or another storage device.

[Disaster occurrence information]
The disaster occurrence information will be described below using FIG. 15 while referring to FIGS. 16 and 17. FIG. FIG. 15 is a diagram showing an example of the data structure of disaster occurrence information delivered from the disaster occurrence information delivery device 6d. The information distributed from the disaster occurrence information distribution device 6d includes the date and time of occurrence, the name of the epicenter, the maximum seismic intensity, the epicenter and the depth of the epicenter, the disaster ID, the seismic intensity of each place, and the characteristics of the shaking. can be included.

FIG. 15 shows disaster occurrence information for an earthquake with a disaster ID of "EQ2106**" (hereinafter referred to as earthquake EQ2106**). Earthquake EQ2106** is an earthquake that occurred on "June **, 2021" off the coast of Z Prefecture. The maximum seismic intensity of earthquake EQ2106** is "4", and the magnitude indicating the scale of the earthquake is "3.8". The epicenter of the earthquake EQ2106** is "Non latitude, East longitude mmm", and the depth of the epicenter is "30km".

The seismic intensity 61a in each place is the seismic intensity information observed at the observation points in each place when the earthquake EQ2106** occurred. As shown in FIG. may be associated with. According to Figure 16, a maximum seismic intensity of 4 was observed in "Z prefecture ** city" and "Z prefecture A city", etc., and a seismic intensity of 3 was observed in "Z prefecture F city" and "Z prefecture B city". is shown.

The sway characteristics 62a may include information indicating the sway direction, acceleration, and sway period observed in earthquake EQ2106**. As shown in FIG. 17, the shake characteristic 62a shows the acceleration of the shake observed when the earthquake EQ2106** occurred for each of the north-south component, east-west component, and vertical component. The sway characteristics 62a may include the observed sway magnitude (amplitude), sway period, and the like. In the example shown in FIG. 17, the shaking characteristic 62a indicates that a shaking period of "1.2 sec" was measured. Note that the shaking characteristic 62a may be distributed for each area in which shaking is observed in each area.

Next, the location information, building information, and equipment information of the elevator equipment of interest will be described using FIG. 18 while referring to FIG. 19 . FIG. 18 is a diagram showing an example of the location information, building information, and equipment information of the elevator equipment of interest.

FIG. 19 is an image diagram showing the positional relationship between the epicenter of earthquake EQ2106** and elevator equipment. FIG. 19 shows the epicenter (indicated by “X” in the figure) of earthquake EQ2106** (see FIG. 15). FIG. 19 also shows the locations of the elevator installation EV001, the elevator installation EV002, the elevator installation EV010, the elevator installation EV026, and the elevator installation EV050. Note that major roads are also illustrated in FIG.

The input data generation unit 51 may use the seismic intensity at the location of each elevator installation, which is specified based on the seismic intensity of each place included in the disaster occurrence information, as the extent of the disaster. Alternatively, the training data generation unit 41 may generate (1) the location of the epicenter, the magnitude indicating the scale of the earthquake, and the depth of the epicenter included in the disaster information, and (2) the distance between the location of each elevator equipment and the epicenter. You may use the magnitude|size of the shaking in the location of each elevator installation calculated from , as a degree of disaster.

The input data may include operating conditions at the time of the disaster, which are obtained by remotely monitoring peripheral equipment located within a predetermined range from the elevator equipment of interest. In FIG. 19, elevator installation EV002 is peripheral equipment of elevator installation EV001, and elevator installation EV010 is peripheral equipment of elevator installation EV026 and elevator installation EV050. Also, the input data may further include at least one of facility information of the elevator installation of interest and building information of the elevator installation of interest. By inputting these pieces of information into the learning model 451a together with location information, disaster information, and driving situation information, the driving situation estimation device 5 can output more reliable estimation results.

(Processing executed by driving situation estimation device 5)
Next, processing executed by the driving situation estimation device 5 will be described using FIG. 20 while referring to FIG. 21 . FIG. 20 is a flowchart showing an example of the flow of processing for estimating the operating condition of the elevator installation of interest by the operating condition estimation device 5 .

First, the input data generation unit 51 acquires disaster occurrence information, peripheral operating status information, location information of the elevator equipment of interest, building information, and equipment information (step S51).

Subsequently, the input data generator 51 generates input data including disaster information and location information of the elevator installation of interest (step S52).

On the other hand, the estimation unit 52 reads the learning model 451a from the storage unit 54 (step S53). Subsequently, the estimating unit 52 inputs the input data generated in step S52 to the learning model 451a, and estimates the operation status of the elevator installation of interest (step S54: estimating step).

The estimation unit 52 outputs the estimation result (step S55). FIG. 21 is a diagram showing an example of an estimation result output from the driving situation estimation device 5. As shown in FIG. The estimation result may be the probability of the operating status of the elevator installation of interest. For example, the operating condition estimating device 5 may output the operating condition of each elevator installation as a probability of stopping as shown in FIG. 21 or as a probability of normal operation. According to FIG. 21, when a disaster (e.g. earthquake EQ2106**) occurs, the probability that the elevator equipment EV001 is stopped is "80%", and the probability that the elevator equipment EV026 is stopped is "15%". ”. The probability related to the operating condition output as the estimation result serves as a reference in determining the necessity of secondment for restoration work. For example, dispatching for restoration work on elevator equipment EV001, which has an 80% probability of being stopped, should be prioritized over dispatching for restoration work on elevator equipment EV026, which has a 15% probability of being stopped. be. The estimation result output from the estimation unit 52 may be output to the display device 9 via the output control unit 53, or may be output to the secondment planning system 10 described later.

Here, the driving situation estimation device 5 that employs the learning model 451 a has been described as an example, but the driving situation estimation device 5 may employ the learning model 451 . In this case, the operating condition estimating device 5 may input the location information of the elevator equipment of interest and the disaster information to the learning model 451 to estimate the operating condition of the elevator equipment of interest.

[Embodiment 4]
Other embodiments of the invention are described below. For convenience of description, members having the same functions as those of the members described in the above embodiments are denoted by the same reference numerals, and description thereof will not be repeated.

<Overview of maintenance system>
An embodiment of the present invention will be described in detail below. FIG. 22 is a block diagram showing an overview of the maintenance system 1000. As shown in FIG. The maintenance system 1000 is a system for supporting recovery work for a plurality of recovery targets at different locations where an event requiring recovery work has occurred. In this embodiment, restoration targets are typically elevator equipment such as passenger conveyors and elevators. An example of an event that requires recovery work is a stoppage or failure of elevator equipment.

Maintenance system 1000 includes at least dispatch support system 100 . The secondment support system 100, for example, the front-end system 1, the damage information providing system 200, the map information providing system 300, the office device 2, and the terminal device 3 (information terminal) via a communication network such as the Internet It is communicatively connected to another device.

(Regarding secondment support system)
In the maintenance system 1000, the dispatch support system 100 has a function of dispatching each of work groups (hereinafter simply referred to as "groups") that perform restoration work on a plurality of restoration targets. The dispatch support system 100 has, as an example, a dispatch plan planning function for formulating a dispatch plan for dispatching each group to a plurality of restoration targets. A configuration group of hardware and software for realizing this transfer planning function is referred to as a transfer planning system 10 . The details of the configuration of the secondment planning system 10 will be described in detail later in this embodiment, but the secondment planning system 10 according to this embodiment typically includes the driving situation estimation device described in the above embodiment. 5.

In the maintenance system 1000, the secondment support system 100 arranges the secondment of each group based on the prepared secondment plan, manages the progress of recovery work, and adjusts the secondment plan according to the ever-changing disaster situation. It has a secondment arrangement function to review the A configuration group of hardware and software for realizing this dispatch arrangement function is referred to as a dispatch arrangement system 20 .

The secondment planning system 10 and the secondment arrangement system 20 of the present disclosure may be configured by one information processing device having a configuration group of hardware and software, or may be configured by a plurality of information processing devices. . A configuration example of the information processing apparatus will be described later with reference to FIG.

A part of the hardware and software configuration group described above may be a configuration for realizing both the secondment planning function and the secondment arrangement function. That is, part of the configuration group that implements the secondment planning system 10 may be part of the configuration group that implements the secondment arrangement system 20 .

(Regarding secondment plan)
The secondment plan drawn up by the secondment planning system 10 defines, for each group, the combination of the secondment targets, which are scheduled to be seconded by the group for recovery work, and the order of the secondment. The secondment planning system 10 may draw up a secondment plan for an area managed by one business office that has a plurality of groups. Further, the secondment planning system 10 may draw up a secondment plan for each office under the jurisdiction of the maintenance company.

In this embodiment, as an example, it is assumed that the secondment planning system 10 draws up a secondment plan for each office under the jurisdiction of the maintenance company. The staffing planning system 10 may operate according to instructions from the front-end system 1 (output unit) operated by an operator who works at a maintenance company. In this case, the secondment planning system 10 may be incorporated in an information processing device that constitutes the front-end system 1, or may be a separate information processing device that is communicably connected to the front-end system 1 as an input/output device. may be configured.

In addition, when the secondment planning system 10 draws up a secondment plan for an area managed by one business establishment, the secondment planning system 10 is a business office device operated by an operator working at the business establishment. 2 (output section). In this case, the secondment planning system 10 may be incorporated in the office device 2 as an information processing device, or may be configured by another information processing device communicably connected to the office device 2 as an input/output device. may be

(for other devices)
The front-end system 1 is, as described above, a system composed of one or more information processing devices operated by an operator who works for a maintenance company. In this embodiment, the front-end system 1 is communicably connected to a secondment support system 100 including a secondment planning system 10 and a secondment arrangement system 20 . As an input/output device, the front-end system 1 assists the operator in inputting information to the seconding support system 100, acquires information output from the seconding support system 100, and presents it to the operator. The front-end system 1 and the secondment support system 100 are connected by an arbitrary communication network. The communication network may be a LAN (Local Area Network) or a wide area network including the Internet.

The office device 2 is a device operated by an operator who works at one office, as described above. In this embodiment, the office device 2 may be communicably connected to the temporary transfer support system 100 and the terminal device 3 via any communication network.

The terminal device 3 is a device operated by the group leader of the group. The terminal device 3 is assumed to be, for example, a mobile terminal such as a smart phone or a tablet PC. In this embodiment, the terminal device 3 is communicably connected to the temporary transfer support system 100 via any communication network. The terminal device 3 may be communicably connected to the office device 2 .

The damage information providing system 200 monitors the elevator equipment maintained by the maintenance company, collects information on each elevator equipment, and provides it to the secondment support system 100 . Specifically, when a disaster such as an earthquake occurs, the damage information providing system 200 collects information on the damaged elevator equipment. Then, when events such as stoppages or failures occur simultaneously in a large number of elevator equipment, the damage information providing system 200 generates operating status information indicating the operating status of the elevator equipment in the disaster area. The operating status information generated here indicates whether the operating status corresponds to "stopped" or "normal operation" for each elevator facility located in the disaster area, similar to the operating status information shown in FIG. It may be information. The driving status information is transmitted from the damage information providing system 200 to the dispatch support system 100 via the communication network.

The map information providing system 300 provides the secondment support system 100 with map information. The map information providing system 300 may provide map information to the front-end system 1 , office device 2 and terminal device 3 . If necessary, the map information providing system 300 may grasp road traffic conditions in various places in real time and provide each device with map information to which information such as traffic jams or road closures is added. Further, the map information providing system 300 may receive a starting point and a destination from a client, and provide a possible travel route from the starting point to the destination, a moving distance, a moving time, and the like. Here, the clients are the dispatch support system 100, the front-end system 1, the office device 2, the terminal device 3, and the like.

(Processing flow of secondment support system)
FIG. 23 is a flow chart showing the processing executed by the secondment support system 100. As shown in FIG.

In step S1, the secondment support system 100 stores in advance the number of groups that can respond to emergencies for each office. The secondment support system 100 sets a group leader for each group of each office, and stores the contact information of the group leader for each office. A list storing the number of groups for each office and the contact information of the group leader of each group may be created in advance by the operator and stored in the storage device of the secondment support system 100 .

The process of step S1 is preferably executed in advance before a disaster actually occurs.

When an event such as a failure or stoppage is detected in a large number of elevator equipment at the same time due to the occurrence of a disaster, the damage information providing system 200 generates a list of the entire elevator equipment that requires restoration work. When the entire list is provided from the damage information providing system 200 to the seconding support system 100, the seconding support system 100 starts the processing from step S2 onward.

The damage information providing system 200 may directly communicate with each of the elevator installations to be remotely monitored, and add the elevator installations determined to require restoration work to the above-described overall list as restoration targets. Further, in the damage information providing system 200, an operator may be arranged to receive a failure report (callback) from the owner or user of the elevator equipment not subject to remote monitoring via communication means such as a telephone. The operator who has received the callback registers the elevator equipment that is not subject to remote monitoring in the damage information providing system 200 as a restoration target. In this way, the damage information providing system 200 may add the elevator equipment for which the callback has been received to the above-described overall list as restoration targets.

In step S2, the secondment support system 100 divides the operating status information including the operating status of many elevator facilities in the disaster area for each office. The division of driving situation information may be performed based on geographical conditions. For example, the secondment support system 100 grasps in advance the area managed by each office, and depending on which area the location of the elevator equipment belongs to, the elevator equipment in the operating status information is assigned to each office. can be associated. Hereinafter, the operation status information of the elevator equipment in the region corresponding to the office, which is divided for each office, is referred to as an operation status list for each office. Note that the office-by-office operating status list may be created according to manual input work by the operator. The office-by-office operating status list obtained in this manner indicates the operating status of elevator equipment whose status is actually grasped. Elevator equipment whose operating status is known refers to elevator equipment that is subject to remote monitoring and elevator equipment that is not subject to remote monitoring, and whose status is known by receiving a callback from the owner or user. Refers to elevator equipment. The operational status may include at least normal operation and shutdown. In other words, the office-by-office operation status list is a list indicating at least whether the elevator equipment is in normal operation or abnormally stopped for each elevator equipment in the region under the jurisdiction of the office. This enables the dispatch planning system 10 to determine whether recovery work is necessary.

In step S3, the operating status estimation device 5 of the temporary staffing planning system 10 estimates the operating status of elevator equipment that is not subject to remote monitoring and whose operating status is not known. Specifically, step S3 includes an operating status acquisition step (S3-1) for acquiring an operating status from a monitoring target facility, which is an elevator facility capable of remotely monitoring the operating status among a plurality of elevator facilities located at different locations; and an operating condition estimation step (S3-2) for estimating the operating condition of non-monitored equipment, which is elevator equipment whose operating condition cannot be remotely monitored. The process of estimating the driving situation executed by the driving situation estimating device 5 in step S3 has been explained in the third embodiment, so detailed explanation will not be repeated in this embodiment.

In step S4, the secondment planning system 10 of the secondment support system 100 searches for an optimal secondment plan from several conceivable secondment plan candidates. An optimal seconding plan is an optimal or sub-optimal solution of a seconding plan. In this embodiment, the secondment planning system 10 searches for a secondment plan with a relatively early estimated completion time at which restoration of all the secondment targets handled by the office is completed, as the optimal secondment plan. A genetic algorithm can be applied as an example of a search method, but other algorithms for solving combinatorial optimization problems may also be applied.

Specifically, step S4 includes a restoration target identification step (S4-1) for identifying a restoration target from the elevator equipment, and a restoration target identified in the restoration target identification step as a secondment target, and a combination and secondment thereof. and a search step (S4-2) for searching for the optimal seconding plan in order.

In the recovery target identification process, when a disaster occurs, the temporary staffing planning system 10 specifies recovery targets from the monitoring target equipment according to the operation status acquired in the operation status acquisition process, and Depending on the operating conditions estimated in the operating condition estimation step, the equipment to be restored is identified from among the non-monitoring equipment.

In the search process, the dispatching planning system 10 optimizes a dispatching plan in which a combination of dispatched targets, which are scheduled to be dispatched by a group consisting of one or more workers to perform restoration work, and the order of dispatching are determined for each group. Search for the optimal dispatch plan that is the solution or sub-optimal solution.

In this embodiment, the secondment planning system 10 searches for the optimal secondment plan for each office owned by the maintenance company. That is, the dispatch planning system 10 includes, for each office, an operating status acquisition step (S3-1), an operating status estimation step (S3-2), a restoration target identification step (S4-1), a search step (S4 -2) and are repeatedly executed. In another example, the temporary staffing planning system 10 targets the entire disaster area, prior to step S2, performs a driving status acquisition step (S3-1), a driving status estimation step (S3-2), and a recovery target A specifying step (S4-1) may be performed. Then, in step S2, the personnel transfer planning system 10 divides the list of restoration targets for the entire disaster area into regions under the jurisdiction of each business establishment, and then creates an optimal personnel transfer plan with the restoration targets for each business establishment as the transfer targets. The search step (S4-2) may be repeated for each office.

In addition, when the business office proceeds with the recovery work according to the optimum transfer plan corresponding to the business office, the temporary transfer planning system 10 completes the recovery work for all restoration targets assigned to the business office. The estimated time may be output as the estimated completion time of the office.

Furthermore, the secondment planning system 10 virtually changes the affiliation of groups between offices, simulates secondment arrangements, and produces a better and optimal secondment plan that shortens the estimated completion time of each office. You can search every place. The secondment planning system 10 may propose to the operator a group allocation pattern for each office that will yield a better and more optimal secondment plan.

The staffing plan system 10 identifies the optimal staffing plan adopted by the operator as the final optimal staffing plan. The operator may adopt the optimum dispatch plan searched in step S3, or may select the optimum dispatch plan to be adopted from several simulated optimum dispatch plans.

The secondment planning system 10 saves the identified final optimal secondment plan in the storage device of the secondment support system 100 for each office. In this embodiment, the optimal secondment plan for each office may include, for each group, a queue in which the secondment targets, which are the restoration targets to which the group is scheduled to be seconded, are arranged in a line in the order of their secondment.

In step S5, the secondment arrangement system 20 of the secondment support system 100 arranges secondment according to the stored optimum secondment plan. First, the secondment arrangement system 20 may confirm whether or not the secondment target can be seconded with respect to the group with which the secondee target is associated. The secondment arrangement system 20 may manage a seconded subject informed by the group that the seconded subject is available as a confirmed seconded subject, distinguishing it from other unconfirmed seconded subjects.

In step S6, the secondment arrangement system 20 may manage the progress of the restoration work for each secondment confirmation target. Then, the secondment arrangement system 20 updates the above-mentioned queue according to the ever-changing situation, such as the progress of restoration work and the addition of new restoration targets.

In step S7, the staffing plan system 10 monitors updates in the operating status list by business site and determines whether re-searching for the optimal staffing plan is necessary. If it is determined that re-search is necessary (YES in S7), the process returns to step S3, acquires the updated operating status of the monitored equipment, estimates the operating status of the non-monitored equipment, and restores. The target is respecified, and the search for the optimal secondment plan is repeated for the restoration target.

In step S8, the secondment arrangement system 20 determines whether or not the recovery work for all the secondment targets, ie, the recovery targets, has been completed in all the offices. When the restoration work has been completed for all restoration targets (YES in S8), the secondment support system 100 terminates the series of processes. Note that, if there are still restoration targets for which restoration work has not been completed (NO in S8), the secondment arrangement system 20 returns to step S6 and continues progress management.

<Configuration of Temporary Transfer Planning System 10>
FIG. 24 is a block diagram showing the main configuration of the secondment planning system 10. As shown in FIG. The dispatch planning system 10 includes at least a driving condition acquisition unit 11 , a driving condition estimation device 5 , a restoration target identification unit 14 , and a search unit 12 . FIG. 24 representatively shows only the estimating unit 52 of the driving situation estimating device 5, but the driving situation estimating device 5 may include each unit of the driving situation estimating device 5 shown in FIG.

The operating status acquisition unit 11 acquires the operating status from a monitoring target facility, which is an elevator facility whose operating status can be remotely monitored among a plurality of elevator facilities located at different locations. The operating status acquisition unit 11 may directly communicate with each of the monitoring target facilities to acquire their respective operating statuses, or may collect the operating status of each monitoring target facility aggregated in the damage information providing system 200 as damage information. They may be collectively acquired from the provision system 200 . Further, the driving condition acquisition unit 11 may acquire the driving condition for each office. For example, the operating status acquisition unit 11 acquires an operating status list for each business office that indicates the operating status of elevator equipment in an area under the jurisdiction of one business office, from the operating status information provided by the damage information providing system 200, as damage information. It may be obtained from the provision system 200 or the secondment support system 100 . The operating status list by business site includes the operating status of non-monitored facilities whose actual status is known based on callbacks from owners or users. may

The estimating unit 52 (operating condition estimating unit) of the operating condition estimating device 5 estimates the operating condition of non-monitoring equipment, which is elevator equipment whose operating condition cannot be remotely monitored. The estimating unit 52 may estimate the operating status of the non-monitoring equipment based on the operating status of the monitoring target equipment included in the above-mentioned office-specific operating status list. Specifically, the input data generating unit 51 generates input data to be input to the learning model 451a using the operating conditions of the monitoring target equipment included in the operating condition list for each office. The estimation unit 52 inputs the generated input data to the learning model 451a and obtains the output data, thereby estimating the operational status of the non-monitoring equipment. The output data may be the estimation result described in the first to third embodiments, and the estimation result may be information indicating the operating status estimated for each non-monitoring facility. As shown in FIG. 21, the estimation result may be information indicating the outage probability estimated for each non-monitored facility. The output control unit 53 outputs the estimated operational status of the non-monitoring equipment to the restoration target identification unit 14 . Hereinafter, the estimated operating status of the non-monitoring equipment is referred to as an estimated operating status to distinguish it from the actually grasped operating status acquired by the operating status acquisition unit 11 .

The restoration target identification unit 14 identifies a restoration target from the elevator equipment for which the operating conditions or estimated operating conditions are indicated. Specifically, the restoration target identification unit 14 identifies the restoration target from the monitoring target equipment according to the operation status acquired when the disaster occurs, and when the disaster occurs, based on the degree of the disaster According to the estimated operating status estimated by

For example, the recovery target specifying unit 14 may create a recovery target list showing information about the plurality of recovery targets, which are specified as described above and in which an event requiring recovery work has occurred and which is located at a different location. can be generated for each The recovery target identification unit 14 outputs the recovery target list generated for each office to the search unit 12 .

The searching unit 12 searches for an optimal seconding plan, which is an optimal solution or a quasi-optimal solution for the seconding plan. As described above, the secondment plan defines for each group the combination of seconded targets, which are scheduled to be seconded by a group consisting of one or more workers to perform recovery work, and the order of the seconded workers. In the present embodiment, the searching unit 12 searches for the optimum seconding plan with the recovery target specified by the recovery target specifying unit 14 as the seconding target.

According to the above-described configuration, the operating status at the time of disaster is estimated for the non-monitored equipment whose operating status cannot be grasped until it is contacted because it is not subject to remote monitoring. As a result, it is possible to specify not only monitoring target equipment whose operating status can be grasped in real time by remote monitoring, but also non-monitoring equipment, to specify recovery targets. In this way, it is possible to draw up an accurate secondment plan that takes into account the operational status of facilities not subject to monitoring when a disaster occurs.

After a disaster occurs, especially in the early stages, it is difficult to quickly grasp the overall picture of the suspended elevator equipment, and the secondment plan drawn up at this stage may lack accuracy. Therefore, in the early stages of a disaster, utilizing the dispatch planning system 10 of the present invention enables us to quickly grasp the overall picture of the elevator equipment that has stopped, and to formulate a highly accurate dispatch plan from the initial stage of the disaster. This is especially advantageous because it enables

As an example, in this embodiment, a plurality of patterns are created for the secondment plan. Each pattern differs in the combination of seconded subjects and the seconded order. The pattern described above is hereinafter referred to as a dispatch pattern. The process of generating a plurality of secondment plans with different secondment patterns may be executed by the searching unit 12 . In the present embodiment, the searching unit 12 selects, from among a plurality of temporary assignment plans with various different temporary assignment patterns, a temporary assignment plan with a relatively early estimated completion time for completion of restoration of all the temporary assignment targets handled by the business establishment as the most suitable one. You may search as a secondment plan. In the present embodiment, the estimated completion time may be estimated by taking into account at least the total travel time to go to the seconded target and the total work time required for the recovery work of the seconded target. The estimation of the estimated completion time may be performed by the searching unit 12 . The search unit 12 may output, for example, numerical values indicating the date and hour and minute as the estimated completion time. The search unit 12 may output numerical values indicating the year, month, day and hour, minute, and second as the estimated completion time.

According to the above-described configuration, the search unit 12 searches for the optimum secondment plan for a plurality of recovery targets with different locations. The optimal temporary assignment plan is an optimal or quasi-optimal temporary assignment plan among the temporary assignment plans in which a combination of temporary assignment targets, which are restoration targets to which the group is scheduled to be seconded, and an order of assignment are determined for each group. In other words, the searching unit 12 searches for a temporary temporary transfer plan with a relatively early estimated completion time at which restoration of all the temporary temporary transfer targets handled by the office is completed, as the optimal temporary temporary transfer plan. In this way, there is an effect that it is possible to draw up a dispatch plan that shortens the time for completing all of the restoration work.

The dispatch planning system 10 may further include one or more of the travel time acquisition unit 13, the output control unit 15, the disaster information acquisition unit 16, and the confinement information acquisition unit 17, if necessary.

The above-mentioned units (driving status acquisition unit 11, estimation unit 52, restoration target identification unit 14, search unit 12, travel time acquisition unit 13, output control unit 15, disaster information acquisition unit 16, and confinement information acquisition unit 17) is a control block implemented by a control device provided in an information processing device that implements secondment planning system 10 and a storage device that stores programs.

Further, the secondment planning system 10 may store the latest secondment plan database 31 (the latest secondment plan DB 31) in the storage device described above.

The travel time acquisition unit 13 acquires the travel time required for the worker to travel from the starting point to the destination. For example, the travel time acquisition unit 13 transmits a request including a query designating the location of the first person to be seconded as the starting point and the location of the next person to be seconded as the destination to the map information providing system 300 . Then, the travel time acquisition unit 13 may acquire the travel time from the departure point to the destination from the map information providing system 300 . As a result, the search unit 12 can estimate the total travel time required to move the seconded targets in the order of arrival as the total travel time.

The travel time acquisition unit 13 may acquire an average travel time calculated by the map information providing system 300 as the travel time described above. Alternatively, the travel time acquisition unit 13 may acquire the travel time calculated by the map information providing system 300, taking into consideration road traffic conditions. The travel time that takes road traffic conditions into account may be the travel time calculated taking into account the degree of road congestion, or if the shortest route is closed to traffic, it is calculated based on the travel distance of an alternative route. It may be the travel time that is set.

The dispatch planning system 10 may acquire position information indicating the current position of a predetermined leader among the workers belonging to the group. For example, the secondment planning system 10 may communicate with the terminal device 3 of each group leader of each office and acquire the current location information of the group leader from the terminal device 3 .

As a result, the searching unit 12 can determine the current location of the group leader as the departure point of the group to which the group leader belongs, for each of a plurality of secondment plans with various different secondment patterns. Then, the searching unit 12 can estimate the travel time from the departure point to the location of the first person to be seconded in order of arrival.

The output control unit 15 outputs the search result executed by the search unit 12 to the output unit. In this embodiment, the output unit is the front-end system 1 or the office device 2 as an example.

In this embodiment, as described above, each of the elevator installations to be restored is associated with one of the business establishments that perform the maintenance to be restored. Each group belongs to one of the offices. The search unit 12 searches for an optimal secondment plan for each business office, targeting groups belonging to the business office. Through this search, the optimum secondment plan is searched for for each office together with the estimated completion time.

The output control unit 15 outputs each of the estimated completion times in the optimum secondment plan searched for each office to the output unit.

As a result, the operator can easily grasp when the restoration work for all restoration targets assigned to each office will be completed for each office. Presenting the estimated completion time for each office can contribute to the prompt transmission of the outlook for restoration work to relevant parties. By presenting the prospect of recovery in this way, it is possible to give a sense of security to the user or owner of the recovery object. Furthermore, the operator can contribute to expedite dispatch arrangements based on the optimal dispatch plan. Alternatively, it can help the operator to quickly make a decision to revise a more optimal dispatch plan.

As an example, the output control unit 15 may output to the front-end system 1 each of the estimated completion times in the optimum secondment plan searched for each office for all offices under the jurisdiction of the maintenance company. good. Further, a seconding pattern in which a combination of seconded subjects and a seconding order indicated by the optimal seconding plan are defined for each group may be output in addition to the estimated completion time. For example, the output control unit 15, for the office device 2, the optimum dispatch plan of the office where the office device 2 is installed, that is, the above-mentioned dispatch pattern of the office and the estimated completion time of the office may be output.

The disaster information acquisition unit 16 acquires information indicating the degree of disaster for each region. For example, when a disaster occurs, the disaster information acquisition unit 16 may acquire information indicating the extent of the disaster for each region from the damage information providing system 200 or another disaster information providing system (not shown). . Information that indicates the extent of disasters in each region is not limited to information that directly indicates the extent of disasters in each region, but is indirect information that makes it possible to specify or estimate the extent of disasters based on such information. may

If the disaster is an earthquake, for example, the extent of the disaster is calculated from (1) the seismic intensity at the location of the elevator equipment, or (2) the magnitude of the epicenter, the distance from the epicenter, and the depth of the epicenter. , the magnitude of shaking at the location of the elevator equipment, and the like. Alternatively, the severity of the hazard may be (3) characteristics of the sway at the location, such as pitch and roll. When an earthquake occurs, the disaster information acquiring unit 16 may acquire at least one of the above information (1) to (3) from the damage information providing system 200 or another information providing system.

According to the above-described configuration, the restoration target identification unit 14 can identify, as a restoration target, elevator equipment located in an area where a specified degree of disaster has occurred.

For example, the restoration target identification unit 14 can identify, as a restoration target, elevator equipment located in an area where an earthquake of a predetermined seismic intensity or more occurred. For example, the restoration target identification unit 14 designates elevator equipment located in an area where the magnitude of shaking calculated from the magnitude of the epicenter, the distance from the epicenter, and the depth of the epicenter is greater than or equal to a predetermined value as the restoration target. can be specified. In addition, for example, the restoration target identification unit 14 can identify, as a restoration target, elevator equipment located in an area in which characteristic shaking that seriously affects the operation of the elevator equipment has occurred.

As a result, even if the elevator equipment is non-monitored equipment that is not subject to remote monitoring, it may be affected by the disaster, and in the temporary staffing planning system 10, the non-monitored equipment is subject to recovery or recovery. It can be treated as a target candidate. As a result, it is possible to formulate an accurate dispatch plan that takes into account the operational status of equipment not subject to monitoring when a disaster occurs. In addition, out of a huge number of non-monitored facilities that are taken into account in drafting the secondment plan, elevator facilities located in areas where disasters of a specified degree have occurred are narrowed down. be Therefore, it is possible to prevent the drafting of an inefficient secondment plan in which elevator equipment that is less necessary to be seconded is included as a secondment target.

The confinement information acquisition unit 17 acquires confinement information indicating whether or not the user is confined in the restoration target. For example, the confinement information acquisition unit 17 may acquire confinement information for each monitored facility from the damage information providing system 200 . In other examples, confinement information may be included in driving situation information. Specifically, in the operating status information, confinement information may be associated with each monitored facility. In this case, the confinement information acquisition unit 17 may extract the confinement information of each monitoring target facility from the operating status list for each office acquired by the operating status acquisition unit 11 .

According to the above configuration, it is possible to make a secondment plan in consideration of whether or not the user is confined. Specifically, the searching unit 12 can generate a dispatch plan in which the dispatch order of dispatch targets in which confinement of the user has occurred is earlier than the dispatch order of dispatch targets in which confinement has not occurred. . As a result, a secondment plan is drawn up that allows restoration work to be carried out, giving top priority to restoration targets in which users are confined.

<S4: Search for Optimal Secondment Plan>
(Regarding input information)
Input information that is input to the search unit 12 for searching for the optimal secondment plan for one office (for example, office A) will be described below. For example, the number of groups belonging to the office A, the position information of the group leader of each group belonging to the office A, and the recovery target list of the office A are input to the search unit 12 as input information. . The recovery target list for the office A is generated by the recovery target specifying unit 14 in the recovery target specifying step S4-1.

The number of groups may be pre-registered in the storage device of the secondment planning system 10, or designated by the operator. For the position information of the group leader, for example, the information provided to the dispatch planning system 10 from the terminal device 3 of the group leader immediately before the search process can be adopted.

FIG. 25 is a diagram illustrating an example of the data structure of a restoration target list. As an example, first, the restoration target identification unit 14 selects elevators whose operating status is indicated as "stopped" from the operating status list (Fig. The facility is specified as a restoration target and added to the restoration target list shown in FIG. 25 . Here, the recovery target specifying unit 14 adds non-monitoring facilities that have been found to be stopped by a callback from the owner or user to the recovery target list. good too.

Next, the restoration target identifying unit 14 identifies elevator equipment that satisfies a predetermined condition as restoration targets from the estimated operating conditions ( FIG. 21 ) output by the estimating unit 52 of the operating condition estimation device 5 , and the restoration target list described above. Add to For example, the estimating unit 52 estimates the probability of the operating status of non-monitored equipment, and the recovery target identifying unit 14 may identify non-monitored equipment with a probability exceeding a specified value as a restoration target. good.

According to the above-described configuration, the operating status at the time of disaster occurrence is estimated as a probability for non-monitored equipment whose operating status cannot be grasped until it is contacted because it is not subject to remote monitoring. As a result, it is possible to specify not only monitoring target equipment whose operating status can be grasped in real time by remote monitoring, but also non-monitoring equipment, to specify recovery targets. In particular, non-monitored equipment that is highly likely to require restoration work can be added to restoration targets. As a result, it is possible to draw up a more accurate dispatch plan that takes into account the operational status of the non-monitoring equipment and its probability in the event of a disaster.

Specifically, the probability of the operating status estimated by the estimation unit 52 may be the probability that the non-monitoring equipment is stopped. Below, the said probability is called a stop probability. The restoration target identification unit 14 may identify non-monitored equipment whose outage probability exceeds a predetermined value as a restoration target. Assuming that the predetermined value is 75%, for example, in the estimated operating conditions shown in FIG. 21, the non-monitoring equipment with the elevator equipment ID "EV001" has a failure probability exceeding 75%. Therefore, the recovery target specifying unit 14 can specify the non-monitoring facility with the elevator facility ID "EV001" as a recovery target, and add the non-monitoring facility to the recovery target list.

For example, as shown in FIG. 25, the restoration target specifying unit 14 generates a restoration target list, which is a list of restoration targets assigned to each business establishment, for each business establishment. Assume that the recovery target list shown in FIG. 25 is the recovery target list for office A, as an example. The generated recovery target list is handed over to the search unit 12 of the secondment planning system 10 . Also, the restoration target list may be provided to the front-end system 1 . Also, the restoration target list of the office A may be provided to the office device 2 of the office A. FIG.

The recovery target list may include, for example, the following items: target ID, location, confinement/presence, recovery priority, number of locations requiring work, and stop probability.

The target ID is identification information for uniquely identifying the restoration target. Unique identification information is given to one elevator installation. In the present embodiment, one elevator facility is treated as one recovery target (seconded target) regardless of how many elevators the one elevator facility is composed of. As the object ID, the elevator equipment ID used in the first to third embodiments may be used as it is.

The location is information indicating the location to be restored, and includes a place name, an address, a building name, and the like.

The presence/absence of confinement is information indicating whether or not an event in which the user is confined in the recovery target has occurred due to the failure or stoppage of the recovery target. In this embodiment, the presence or absence of confinement indicates whether or not the user is confined in any of the elevators belonging to the elevator equipment to be restored. In the illustrated example, "yes" indicates that there are passengers trapped in the elevator and "no" indicates that there are no such passengers. The restoration target specifying unit 14 can reflect the contents of the confinement information acquired by the confinement information acquiring unit 17 in the item of presence or absence of confinement.

The presence or absence of confinement in the elevator equipment is information that is known only in the monitored equipment or in the non-monitored equipment that has received a callback to the effect that confinement has occurred. Therefore, confinement information is not associated with unmonitored equipment whose operational status is unknown.

The recovery priority is information indicating the recovery priority set for the recovery target. In this embodiment, as an example, the recovery priority of the recovery target in which the user is confined is set to the highest (for example, priority S). Then, for recovery targets for which confinement has not occurred, the predetermined recovery priority may be adopted as it is. Restoration priorities set in advance for restoration targets may include, for example, three levels of priorities A to C, excluding priority S. For each restoration target, one of A, B, and C is set in advance in descending order of restoration priority.

For example, the restoration priority may be determined according to the functional properties of the building in which the elevator equipment to be restored is installed. For example, in society, a high restoration priority (priority A) may be set for elevator equipment that operates in facilities that play an important role, especially when a disaster occurs. Facilities that play an important role are, for example, medical institutions such as general hospitals, news organizations such as television stations, and administrative agencies such as city and ward offices. Alternatively, the restoration priority may be set according to the rank of the maintenance contract concluded between the manager of the building in which the elevator equipment is installed and the maintenance company.

The number of places requiring work is information indicating the number of places where restoration work by workers is required in the elevator equipment to be restored. For example, the number of places requiring work may be the number of floors where an elevator stops for a user to get on and off (hereinafter referred to as the number of getting on and off floors) in elevator equipment. Alternatively, the number of places requiring work may be the number of bases of elevators included in the elevator equipment×the number of floors to get on and off. For example, in an elevator facility that is installed in a five-story building and configured with four elevators that stop at each floor, the number of locations where work is required may be 4 units×5 floors=20 locations.

The outage probability is the outage probability estimated by the estimating unit 52 for the non-monitored equipment identified as the restoration target. The recovery target specifying unit 14 can reflect the outage probability estimated by the estimation unit 52 in the outage probability item.

Note that the outage probability of elevator equipment is information estimated for non-monitoring equipment whose operating status is unknown. Therefore, no outage probability is associated with elevator installations whose operational status is known, such as by remote monitoring or callbacks.

(About exploration)
FIG. 26 and FIG. 27 are diagrams showing an example of the procedure for searching for the optimal seconding plan, which is executed by the searching section 12 in the searching step S4-2. It should be noted that the maps M1 to M8 shown in FIGS. 26 and 27 are merely information obtained by visualizing the information held inside when the search unit 12 performs a search, in order to explain the search procedure in an easy-to-understand manner. Therefore, the search unit 12 does not actually need to generate the visualization information shown in the maps M1 to M8.

As shown in the map M1, the searching unit 12 is provided with the locations of all restoration targets included in the restoration target list, whether or not the restoration targets are confined, and the priority of restoration. Further, the search unit 12 is given the number of groups of the office A and the position information of the group leader of each group. Since the search unit 12 generates a seconding pattern with the recovery target as the seconding target, the term "seconding target" is used for the restoration target in the following description.

As shown in the map M2, first, the search unit 12 narrows down to the seconded targets with the highest recovery priority, and sets the estimated completion times of all the seconded targets to be earlier, preferably the earliest. Assign each of the secondees to a group so that: Hereinafter, the seconded target with the highest recovery priority, that is, the seconded target with the priority S in which confinement has occurred is referred to as the seconded target S. For example, the search unit 12 may generate several dispatch patterns targeting only the dispatch target S, and search for the dispatch pattern that is the optimal solution or the semi-optimal solution from among them. The search unit 12 may execute a genetic algorithm, which will be described later, to search for a secondment pattern that is an optimal solution or a quasi-optimal solution.

As an example, the map M2 indicates that the search unit 12 has searched for a secondment pattern in which the seconded target OS1 is first assigned to the group W and the seconded target OS2 is first assigned to the group T as the optimum or quasi-optimal solution. ing. The seconded target OS1 is the first seconded target assigned to the group W, and the seconded target OS2 is the first seconded target assigned to the group T in the seconded order. In this way, in the dispatch plan output by the searching unit 12, the dispatch order of the dispatch target S, in which the user is confined, is earlier than the dispatch order of the dispatch targets A to C, in which confinement does not occur. . As a result, a dispatch plan is generated that allows restoration work to be performed with top priority given to restoration targets in which users are confined.

As shown in the map M3, the search unit 12 then virtually shifts the status of all seconded targets S to the restoration work completed state. In addition, the search unit 12 sets the location of the seconded subject S scheduled to be seconded last as the latest current location for each of the groups.

Subsequently, as shown in the map M4, the search unit 12 narrows down the seconded targets with the priority A next to the priority S (hereinafter referred to as seconded targets A) so that the estimated completion time of all seconded targets A is earlier. Secondly, preferably, each seconded subject A is assigned to a group so that the estimated completion time is the earliest. The search unit 12 generates several dispatch patterns targeting only the secondee target A, similar to the secondee target S, and executes a genetic algorithm, which will be described later, from among them to obtain an optimal or quasi-optimal solution. You may search for a secondment pattern.

According to the map M4, as an example, these two seconded targets A are assigned to the group T in the order of seconded targets OA2 and seconded targets OA3. The seconding target OA2 is the second second in the order of seconding assigned to group T, and the third second in the order of seconding assigned to group T is the seconding target OA3. Since the seconded target S is not assigned to the group U, the seconded target OA4 is the first seconded target assigned to the group U in the order of seconding.

As shown in the map M5, the search unit 12 virtually shifts the status of all seconded targets A to the restoration work completion state, as in the case of priority S. FIG. In addition, the search unit 12 sets the location of the seconded candidate A who is scheduled to be seconded last to be the latest current location for each of the groups.

Subsequently, as shown in the map M6, the search unit 12 narrows down to seconded targets with priority B next to priority A (hereinafter referred to as seconded targets B) so that the estimated completion times of all seconded targets B are earlier. Secondly, preferably, each seconded target B is assigned to a group so that the estimated completion time is the earliest. The searching unit 12 generates several dispatch patterns targeting only the secondee target B as well as the secondee target S and the secondee target A, and among them, executes a genetic algorithm described later to find an optimal solution or a semi-optimal solution. A seconding pattern that is the optimum solution may be searched for.

According to the map M6, as an example, these three seconded targets B are assigned to the group W in the order of seconded targets OB1, seconded targets OB2, and seconded targets OB3. At this point, seconding targets OB1, seconding targets OB2, and seconding targets OB3 are assigned to group W in third to fifth positions in the order of seconding, following seconding target OS1 and seconding target OA1.

As shown in the map M7, the search unit 12 virtually shifts the status of all seconded targets B to the restoration work completion state, as in the case of the priority S and the priority A. FIG. In addition, the search unit 12 sets the location of the secondee B, who is scheduled to be seconded last, to be the latest current location for each of the groups.

Subsequently, as shown in the map M8, the search unit 12 narrows down to seconded targets with priority C next to priority B (hereinafter referred to as seconded targets C) so that the estimated completion times of all seconded targets C are earlier. In addition, preferably, each seconded subject C is assigned to a group so that the estimated completion time is the earliest. The search unit 12 generates several dispatch patterns targeting only the secondee target C in the same way as the secondee target S, the secondee target A, and the secondee target B, and executes a genetic algorithm to be described later from among them, A seconding pattern that is an optimal solution or a quasi-optimal solution may be searched for.

According to the map M8, at this point in time, the group W includes seconded targets OS1, seconded targets OA1, seconded targets OB1, seconded targets OB2, and seconded targets OB3. OC1, seconded target OC2, and seconded target OC3 are assigned respectively. In this way, in the dispatch plan output by the searching unit 12, the dispatch targets A to C in which the user is not confined are arranged in order of earlier dispatch as the restoration priority is higher. As a result, for the rest of the recovery targets excluding the recovery target in which the user is confined, a secondment plan is generated in which recovery work can be performed in descending order of predetermined recovery priority.

As described above, the searching unit 12 may search for the optimum seconding plan by setting only restoration targets associated with designated restoration priorities as seconding targets. As a result, among restoration targets with the same restoration priority, dispatch patterns in which the estimated completion time is relatively early are searched for, and by concatenating these in order of restoration priority, , a dispatch plan capable of performing recovery work is efficiently generated.

Finally, the searching unit 12 can obtain an optimal temporary worker transfer plan for the office A by combining the temporary worker dispatch patterns searched for each restoration priority from priority S to priority C, starting from the one with the highest restoration priority.

(About output information)
The output information output from the searching unit 12 that has searched for the optimal secondment plan for the office A will be described below. For example, the search unit 12 outputs, as output information, the optimal secondment plan for the office A obtained according to the above-described search procedure, and the estimated completion time of the company A based on the optimal secondment plan.

Output Information: Optimal Secondment Plan FIG. 28 is a diagram showing an example of the data structure of the optimal secondment plan. The optimal secondment plan shown in FIG. 28 is the optimal secondment plan for office A having group W, group T, and group U. FIG. The optimal secondment plan includes a group-specific secondment pattern 71 that defines, for each group, the combination of secondment targets to which the recovery work group is scheduled to be seconded and the order of the secondment. Since the office A has three groups, group W, group T, and group U, the optimal secondment plan for the office A includes three group-specific secondment patterns 71 . The group-by-group seconding pattern 71 includes information for uniquely identifying the seconded subject assigned to the group, and the order of arrival of each assigned seconded subject.

Note that the group-by-group dispatch pattern 71 shown in FIG. 28 is merely information visualized so that the combination of dispatch targets assigned to the group and the dispatch order can be easily visually recognized. Therefore, the search unit 12 does not actually need to generate the visualization information of the seconding pattern by group 71 as shown in FIG. 28 .

Output information: Estimated completion time Further, the search unit 12 may output the estimated completion time of the office A in the searched optimal secondment plan together with the optimal secondment plan. The searching unit 12 can estimate the estimated completion time for each temporary transfer plan based on the map information provided from the map information providing system 300 in the above-described search process.

For example, the searching unit 12 may estimate, for each group, the time at which the recovery work for the last seconded target in the order of seconded is completed for each of the seconded plans of a plurality of seconded patterns. Then, the search unit 12 sets the latest time of the estimated times for each group as the estimated completion time in the above-described secondment plan. This makes it possible to grasp the time of complete restoration at the office. Hereinafter, the time estimated for each group of the recovery work completion time of the last dispatched target will be referred to as the group-by-group estimated completion time.

For example, in the optimal dispatch plan shown in FIG. 28, assume that the estimated completion time for each group of group W, that is, the estimated completion time of the recovery work for the seconded target OC3, which is the last in the order of dispatch, is 10:48. Assume that the estimated completion time for each group of group T, that is, the time at which group T is estimated to complete the recovery work of the seconded target OC 6 last in the order of arrival is 10:26. Assume that the estimated completion time for each group of group U, that is, the time at which group U is estimated to complete the recovery work for the last dispatched target OC8 is 10:12. In this case, the search unit 12 determines that the latest estimated completion time of the three groups, ie, "10:48", is the estimated completion time for the entire office A in the optimal secondment plan shown in FIG. do. The searching unit 12 may output the estimated completion time “10:48” together with the optimal secondment plan shown in FIG. 28 .

As an example, the searching unit 12 calculates the estimated completion time for each group for obtaining the estimated completion time of the place of business, the total travel time for the group to be seconded to the seconded target, and the total required recovery work for the seconded target for the group. At least take into account the working hours and guess. The total travel time is, for example, the total sum of travel times required for a group to travel to a visiting target assigned to its own group in accordance with the order of arrival. The total work time is, for example, the sum of the work times required for the group to perform recovery work for each seconded target. For example, the search unit 12 may calculate the estimated completion time for each group by adding the above total travel time and the above total work time to the current time.

A procedure for calculating the total travel time of the group by the search unit 12 will be described by taking as an example a case of calculating the total travel time of the group W based on the optimal seconding plan shown in FIG. 28 .

First, the search unit 12 determines the moving distance from the current location of the group leader of group W (map M1 in FIG. 26) to the location of the first seconded target assigned to group W (seconded target OS1 in map M2). Acquire the corresponding travel time MT1. Note that the travel time acquired by the search unit 12 may be acquired from the map information providing system 300 by the travel time acquisition unit 13 . Further, the travel time described above may be an average travel time based on the travel distance, or may be a travel time in consideration of traffic conditions. The same applies to various travel times acquired by the search unit 12 thereafter.

Thereafter, the searching unit 12 repeats the process of acquiring the travel time MTn from the location of the n-1th seconded target to the location of the nth seconded target (n is an integer equal to or greater than 2). In the example of group W, the search unit 12 repeats the above-described processing until it acquires the travel time MT8 from the second target OC2 to the second target OC3, which is the last travel route.

Then, the search unit 12 calculates the sum of the travel times MT1, MT2, . . . , MTn as the total travel time of the group W.

A procedure for calculating the total work time of the group by the search unit 12 will be described. The search unit 12 identifies the work time WT for each seconded subject according to the number of places requiring work determined for each seconded subject. In this way, by accurately estimating the work time to be restored according to the situation at the site, it is possible to further reduce the error in the estimated completion time.

The searching unit 12 can refer to the recovery target list (FIG. 25) generated by the recovery target specifying unit 14 and specify the number of places requiring work for secondment (recovery target). It should be noted that the seconded target, which is the recovery target, can be uniquely identified by the target ID, for example.

The search unit 12 can calculate the working time WT of one seconded target based on the following formula, as an example.
Formula: work time WT=number of places requiring work×unit time+fixed time The unit time is the average work time required for restoration for one place requiring work, and is, for example, 3 minutes. The fixed time is a fixed work time, for example, 5 minutes, for the restoration of one restoration target, that is, one elevator installation, regardless of the scale of the number of work-required locations.

For example, if the number of places requiring work of the first seconded target OS1 in the group W is 20, the searching unit 12 calculates the work time WT1 of the seconded target OS1 as 20 places x 3 minutes + 5 minutes = 65 minutes. do. In this way, the searching unit 12 calculates the work time WT for each of the n-th dispatched subjects assigned to the group W (work time WT1, WT2, . . . , WTn).

Then, the searching unit 12 calculates the total work time WT1, WT2, .

Finally, the search unit 12 adds the total travel time and the total work time calculated as described above to the current time to calculate the group-by-group estimated completion time of the group W. FIG. The searching unit 12 similarly calculates the estimated completion time for each group for the other group T and group U of the office A as well. Then, the latest time among the three estimated completion times for each group is set as the estimated completion time in the optimal secondment plan shown in FIG.

The searching unit 12 stores the optimal secondment plan for the office A shown in FIG. 28 and the estimated completion time of the optimal secondment plan for the office A estimated as described above in the latest secondment plan DB 31 . The search unit 12 searches for the optimal temporary assignment plan, calculates the estimated completion time in the optimal temporary assignment plan, and stores them in the latest temporary assignment plan DB 31 for each of the offices corresponding to the disaster that occurred. run to

(An example of search: genetic algorithm)
The search unit 12 may generate each of a plurality of secondment patterns of secondment plans by alternation of generations according to a genetic algorithm.

For example, the search unit 12 executes (step 1) initialization, (step 2) evaluation, (step 3) selection, (step 4) crossover, and (step 5) mutation. The search unit 12 repeats each step from step 2 to step 5 until the number of generations specified in advance has passed. The number of generations may be specified in advance by the operator.

In the initial setting of step 1, the searching unit 12 randomly generates individuals so as to satisfy the first condition that at least one seconded target is assigned to all groups in the office, for example. The first condition described above may be specified in advance by the operator, for example.

In this embodiment, identification of dispatch patterns according to the genetic algorithm is performed for each recovery priority. Therefore, an individual is generated as information indicating to which group of business establishments a predetermined number of secondment targets with a certain recovery priority are assigned.

When assigning Y groups to X seconded subjects, the search unit 12 randomly generates individuals having the following data structure (X and Y are integers of 2 or more).
[G ₁ , G ₂ , . . . , G _x ]
Here, G _i is a value for identifying a group to be assigned to the i-th seconded target, and is an integer of 0 or more and less than Y (i is an integer of 1 or more and X or less).

For example, when assigning three groups (first to third groups) to ten seconded targets (first to tenth seconded targets), an example of an individual generated by the search unit 12 is [1, 0, 2, 2, 1, 0, 0, 2, 0, 1]. The three numbers "0", "1", and "2" indicate the first group, the second group, and the third group, respectively. That is, this individual assigns the second group to the first, fifth and tenth seconded subjects, the first group to the second, sixth, seventh and ninth seconded subjects, and the third, It shows assigning the third group to the fourth and eighth seconded subjects.

The search unit 12 generates a plurality of different individuals (for example, 300) and uses them as an initial group of individuals. The number of initial populations (second condition) may be specified in advance by the operator.

In the evaluation of step 2, the search unit 12 calculates, for each generated individual, the estimated completion time for completing the recovery work for all the seconded targets to which each group is assigned, and calculates the estimated completion time for the latest group. Correlate as the estimated completion time of the individual. As described above, the estimated completion time for each group is obtained by adding, to the current time, the total sum of the travel time MT and the total sum of the work time WT when all the assigned secondment targets are visited.

In the selection of step 3, the search unit 12 compares the estimated completion time of each individual by a tournament method, and selects several (for example, 3) individuals with the earliest estimated completion times as parent individuals of the next generation. do.

In the crossover of step 4, the search unit 12 randomly crosses the selected parent individuals such that the first condition is satisfied.

In the mutation in step 5, the searching unit 12 causes each individual to mutate with a predetermined probability (eg, 5%). The probability of causing mutation may be specified in advance by the operator.

The search unit 12 repeats the processes from step 2 to step 5 for the above-mentioned number of generations specified in advance, and selects the individuals remaining after the repetition as the optimal or quasi-optimal seconded target group with a certain recovery priority. Output as a temporary transfer pattern.

The search unit 12 executes the search according to the genetic algorithm consisting of steps 1 to 5 above for each restoration priority, and outputs the optimum or quasi-optimal dispatch pattern for each restoration priority.

<Screen example of optimal secondment plan>
The output control unit 15 provides the front-end system 1 or the office device 2 with a dispatch plan screen for presenting to the operator the optimum dispatch plan for each office searched by the search unit 12 in step S4. good too. FIG. 29 is a diagram showing an example of a secondment plan screen showing details of an optimal secondment plan for one office. The output control unit 15 generates a secondment plan screen 700 based on the optimal secondment plan stored in the latest secondment plan DB 31 and the secondment confirmation target managed by the secondment arrangement system 20 . The output control unit 15 transmits the generated secondment plan screen 700 to an output unit such as the front-end system 1 or office device 2, for example. The secondment plan screen 700 is, for example, a screen for presenting the optimum secondment plan searched for office A. FIG.

The secondment plan screen 700 may include basic information 701 of the place of business. The basic information 701 includes, for example, the number of groups belonging to the business office, the number of all workers assigned to the business office, and the number of elevators for which restoration work has not been completed among the restoration targets assigned to the business office. number of facilities, etc. In the present embodiment, the basic information 701 may include an estimated number of stoppages as the number of non-monitored installations estimated to be stopped by the operating condition estimation device 5 .

Also, the basic information 701 may include estimated completion time. The estimated completion time is estimated by the searching unit 12 based on the optimal seconding plan searched by the searching unit 12 . The estimated completion time refers to the estimated time at which all the recovery work for the entire business is expected to be completed when the business is engaged in recovery work according to the optimal secondment plan with the current power.

The basic information 701 may be designed to represent the latest information regarding basic information relating to the organization and progress of restoration work at the business establishment. For example, the travel plan screen 700 may include a latest button 702 . When the latest button 702 is operated by the operator, an update instruction is transmitted from the front-end system 1 or office device 2 to the secondment support system 100 . Upon receiving the update instruction, the secondment planning system 10 of the secondment support system 100 reads out the latest optimum secondment plan of the office A from the latest secondment plan DB 31, and counts the number of secondment targets whose work has not been completed. Count the number of incompletes where The output control unit 15 provides the front-end system 1 or office device 2 with a dispatch plan screen 700 reflecting the latest number of incomplete jobs.

When the list of operating conditions by business establishment or the estimated operating condition is updated according to changes in the situation, the recovery target identification unit 14 updates the recovery target list. In response to the operation of the latest button 702, the recovery target identification unit 14 updates the number of recovery targets or the estimated stop count displayed in the basic information 701 to the number counted based on the updated recovery target list. may

When the optimum secondment plan stored in the latest secondment plan DB 31 is updated, the search unit 12 updates the estimated completion time displayed in the basic information 701 in response to the operation of the latest button 702 to the updated one. It may be updated to the estimated completion time in the optimal secondment plan.

The secondment plan screen 700 may include a list box 703 indicating the secondment pattern for each group, that is, the combination of secondment targets assigned to the group and the order of secondment. The list box 703 may include the order of visits, property names for visits, and the like. Also, the list box 703 may reflect the work progress of each seconded target. In the illustrated example, the background color of the order of arrival is color-coded according to work progress. The work progress of each secondee is managed by the secondment arrangement system 20 .

The secondment plan screen 700 may include a map image 704 in which the information of the secondment target is reflected on the map. As an example, the map image 704 may reflect information about seconded targets assigned to a specific group selected on the seconded plan screen 700 . In the illustrated example, the list box 703 of group U is selected. Therefore, on the map image 704, along with the boundary line representing the area in charge of Group U, the icon of the seconded target assigned to Group U may be plotted. A number indicating the order of dispatch may be assigned to the icon of the dispatch target.

By displaying the dispatch plan screen 700 as described above on the front-end system 1 or office device 2, the operator can grasp the progress of recovery work for each office in real time.

<Modification>
(Narrowing down recovery targets)
The restoration target identification unit 14 may identify the elevator equipment located in the specified area as the restoration target. As a result, the non-monitoring facilities considered in drafting the secondment plan are narrowed down to the elevator facilities located in the specified area from among a very large number of non-monitoring facilities. Therefore, it is possible to prevent the drafting of an inefficient secondment plan, in which elevator facilities in areas where secondment is not required are included as secondment targets. Operators can judge areas where there is a high need for secondment and specify those areas, thereby facilitating an efficient secondment plan that considers the operating status of equipment not subject to monitoring only in that area. It is possible to make a proposal.

A restoration priority is associated with the elevator equipment, and the restoration target identifying unit 14 may identify the elevator equipment associated with the designated restoration priority as a restoration target. As a result, the non-monitoring facilities considered in drafting the secondment plan are narrowed down to the elevator facilities with the specified recovery priority from among a very large number of non-monitoring facilities. Therefore, it is possible to prevent the establishment of an inefficient secondment plan in which elevator facilities in areas with a low restoration priority and a low need for secondment are included as secondment targets. Conversely, since the operational status is taken into account only for non-monitoring facilities with high recovery priority, it is possible to easily formulate an efficient secondment plan.

(Estimation of driving conditions)
The estimating unit 52 uses teacher data including location information indicating the location of the elevator equipment, disaster information including the extent of the disaster at the location, and operating status information indicating the operating status of the elevator equipment when the disaster occurred. A learning model generated by performing machine learning may be used to estimate the operating status of the non-monitoring facility using the location information of the non-monitoring facility and the disaster information as input data.

If the disaster is an earthquake, for example, the extent of the disaster included in the disaster information is (1) the seismic intensity at the location of the elevator equipment, or (2) the magnitude of the epicenter, the distance from the epicenter, and the depth of the epicenter. It may be the magnitude of the shaking at the location calculated from the location. Alternatively, the severity of the hazard may be (3) characteristics of the sway at the location, such as pitch, roll, and the like.

The training data further includes peripheral operating status information indicating the operating status of peripheral equipment, which is monitored equipment located within a predetermined range from the elevator equipment, when a disaster occurs. It may further include operating conditions obtained by remotely monitoring peripheral equipment located within the range.

The teacher data may further include facility information indicating at least one of the model and specifications of the elevator facility, and the input data may further include facility information of the non-monitored facility.

The teacher data may further include building information indicating at least one of the date of completion and seismic specifications of the building in which the elevator facility is installed, and the input data may further include building information of the elevator facility of interest (equipment not to be monitored). good.

The building information indicates, for example, the construction (completion) year, structure type, earthquake resistance specifications, and the like. The structure type may be information indicating whether the building in which the elevator facility is installed corresponds to any of the reinforced concrete (RC), steel (S), and steel reinforced concrete (SRC) types. . The seismic specification may be information indicating the seismic isolation, seismic resistance (only houses are seismic resistance class), specifications conforming to each local government, and the like, for the building in which the elevator facility is installed.

For example, it is possible to determine which of the old earthquake resistance standards and the new earthquake resistance standards is applied by the completion date. In addition, it is possible to judge the seismic isolation structure and earthquake resistance structure of the building from the seismic specifications. For example, it is possible to determine the seismic resistance grades 1 to 3 of a house, or to determine the history of seismic reinforcement work performed to meet the new seismic standards in a building that complies with the old seismic standards. In this way, by considering the strength against disaster in the building in which the elevator equipment is installed, it becomes possible to more accurately estimate the operation status of the elevator equipment installed in the building when a disaster occurs.

The learning model may output the probability of the operating status of the non-monitored equipment. The probability may be a stoppage probability that indicates the probability that the non-monitored facility is stopped.

<effect>
According to the dispatch planning system 10 of the present invention, even if a large number of events such as stoppages or failures occur simultaneously in a wide area due to a disaster such as an earthquake, the time when all recovery work by a plurality of work groups is completed can be determined. It is possible to draw up a dispatch plan to accelerate.

In addition, according to the secondment planning system 10 of the present invention, not only the monitoring target equipment whose operating status is immediately grasped, but also the non-monitored equipment whose operating status cannot be grasped are restored based on the estimated operating status. It is possible to judge whether work is necessary or not. Therefore, it is possible to generate an accurate secondment plan that matches the disaster situation. As a result, it is possible to improve the accuracy of the secondment plan of the work group. In this way, it is possible to accurately instruct recovery work to each group or each worker according to an accurate secondment plan that takes into consideration the operational status of facilities not subject to monitoring.

In addition, it is possible to present the prospect of recovery to related parties by utilizing the estimated completion time obtained for each dispatch plan. For example, it is possible to provide the users or owners who are waiting for restoration of restoration targets with estimated completion times obtained in accurate dispatch plans that take into consideration the operational status of non-monitored equipment. By presenting the prospect of recovery in this way, it is possible to give a sense of security to the user or owner of the recovery object.

As described above, the secondment planning system 10 of the present invention is a system that brings about an excellent effect of early recovery from a disaster with respect to facilities such as elevators that form the basis of life. Therefore, the secondment planning system 10 of the present invention can contribute to the development of high-quality infrastructure with excellent disaster mitigation or disaster prevention performance, and by extension, the Sustainable Development Goals (SDGs), such as Goal 11 ( We can contribute to the achievement of sustainable city development.

[Example of realization by software]
FIG. 30 is a block diagram showing an example of the hardware configuration of the learning model generation device 4, the learning model generation device 4a, the driving situation estimation device 5, and each device or system included in the maintenance system 1000. As shown in FIG.

The function of one or a plurality of information processing devices that realize the learning model generation device 4, the learning model generation device 4a, the driving situation estimation device 5, the secondment planning system 10, and the secondment arrangement system 20 causes a computer to function as the information processing device. It can be realized by a program for This program can be realized by a program for causing a computer to function as each control block of the information processing apparatus described above. The control blocks described above include, in particular, each unit of the control unit 40, each unit of the control unit 40a, each unit of the control unit 50, the driving situation acquisition unit 11, the search unit 12, the travel time acquisition unit 13, the restoration target identification unit 14, They are an output control unit 15 , a disaster information acquisition unit 16 and a confinement information acquisition unit 17 .

In this case, the information processing device includes a computer 910 having at least one control device (eg processor 911) and at least one storage device (eg memory 912) as hardware for executing the above program. . The memory 912 stores, for example, the program 921 as the above program. Each function described in each of the above-described embodiments is realized by executing a program using the above-described control device and storage device.

The program described above may be recorded on one or more computer-readable recording media (for example, the recording media 931) instead of being temporary. The recording medium may or may not be included in the information processing apparatus described above. In the latter case, the above program may be supplied to the information processing device via any wired or wireless transmission medium.

Also, part or all of the functions of each control block described above can be realized by a logic circuit. For example, an integrated circuit in which logic circuits functioning as the control blocks described above are formed is also included in the scope of the present invention. In addition, it is also possible to implement the functions of the control blocks described above, for example, by a quantum computer.

Also, each process described in each of the above-described embodiments may be executed by AI (Artificial Intelligence). In this case, the AI may operate on the control device, or may operate on another device (for example, an edge computer or a cloud server).

The present invention is not limited to the above-described embodiments, but can be modified in various ways within the scope of the claims, and can be obtained by appropriately combining technical means disclosed in different embodiments. is also included in the technical scope of the present invention.

1 front-end system 2 office equipment 3 terminal equipment (information terminal)
4, 4a Learning model generation device 5 Operational situation estimation device 6a Disaster record database 6b Elevator equipment installation information database 6c Operational condition information database 6d Disaster occurrence information distribution device 6e Elevator equipment remote monitoring device 9 Display device 10 Secondment planning system 11 Operational condition acquisition Unit 12 Search unit 13 Travel time acquisition unit 14 Restoration target identification unit 15 Output control unit 16 Disaster information acquisition unit 17 Confinement information acquisition unit 20 Temporary transfer arrangement system 31 Latest temporary transfer plan database 40, 40a, 50 Control unit 41, 41a Teacher data generation Units 42, 42a Learning units 45, 54 Storage unit 51 Input data generation unit 52 Estimation unit 53 Output control unit 100 Secondment support system 200 Damage information providing system 300 Map information providing system 451, 451a Learning model 910 Computer (information processing device)
911 processor (control device)
912 memory (storage device)
921 program 931 recording medium

Claims (19)

an operating status acquisition unit that acquires an operating status from a monitoring target facility that is the elevator facility that can remotely monitor the operating status of a plurality of elevator facilities located at different locations;
an operating status estimating unit for estimating the operating status of non-monitored equipment, which is the elevator equipment whose operating status cannot be remotely monitored among the elevator equipment;
a restoration target identification unit that identifies a restoration target from among the elevator equipment;
An optimal solution or a quasi-optimal solution of a dispatch plan in which a combination of dispatch targets, which are recovery targets, to which a group consisting of one or more workers to perform restoration work is scheduled to be dispatched, and a dispatch order are determined for each group. A search unit for searching for a secondment plan,
The restoration target identification unit identifies the restoration target from the monitoring target equipment according to the operation status acquired when the disaster occurs, and based on the degree of the disaster when the disaster occurs A secondment planning system that identifies the recovery target from the non-monitored equipment according to the estimated operating condition. The operating status estimating unit estimates the probability of the operating status of the non-monitored equipment,
2. The personnel dispatch planning system according to claim 1, wherein said recovery target specifying unit specifies said non-monitored equipment having said probability exceeding a specified value as said recovery target. further comprising a disaster information acquisition unit that acquires information indicating the degree of disaster for each region,
3. The personnel dispatch planning system according to claim 1, wherein said recovery target identifying unit specifies said elevator equipment located in an area where a disaster of said specified degree has occurred as said recovery target. 4. The personnel dispatch planning system according to any one of claims 1 to 3, wherein said restoration target identification unit identifies said elevator equipment located within a designated area as said restoration target. A recovery priority is associated with the elevator equipment,
5. The dispatch planning system according to any one of claims 1 to 4, wherein said restoration target identifying unit identifies said elevator equipment associated with said designated restoration priority as said restoration target. The operating status estimation unit stores location information indicating the location of the elevator equipment, disaster information including the extent of the disaster at the location, and operating status information indicating the operating status of the elevator equipment when the disaster occurred. Using a learning model generated by performing machine learning using training data including the above, the operating status of the non-monitored equipment is calculated using the location information of the non-monitored equipment and the disaster information as input data. The temporary staffing planning system according to any one of claims 1 to 5, which estimates. The training data further includes peripheral operating status information indicating the operating status of peripheral equipment, which is the monitoring target equipment located within a predetermined range from the elevator equipment, when the disaster occurs,
7. The staffing planning system according to claim 6, wherein said input data further includes operating conditions obtained by remotely monitoring said peripheral equipment located within said predetermined range from said non-monitored equipment. The training data further includes equipment information indicating at least one of the model and specifications of the elevator equipment,
8. The staffing planning system according to claim 6, wherein said input data further includes said facility information of said non-monitored facility. The training data further includes building information indicating at least one of the completion date and earthquake resistance specifications of the building in which the elevator equipment is installed,
9. The staffing planning system according to any one of claims 6 to 8, wherein said input data further includes said building information of said equipment not subject to monitoring. 10. The staffing planning system according to any one of claims 6 to 9, wherein said learning model outputs a probability of the operating status of said non-monitored equipment. The search unit estimates completion of completion of restoration of all of the seconded target, which is estimated by considering at least a total travel time for seconding to the seconded target and a total work time required for the recovery work of the seconded target. 11. The dispatch planning system according to any one of claims 1 to 10, wherein the dispatch plan with a relatively earlier time among the plurality of patterns of dispatch plans with different times is searched for as the optimum dispatch plan. The search unit estimates, for each of the plurality of patterns of the dispatch plans, a time at which the recovery work for the seconded target whose dispatch order is the last is completed for each of the groups, and 12. The dispatch planning system according to claim 11, wherein the late time is used as the estimated completion time. 13. The secondment planning system according to claim 11, wherein said search unit generates each of said plurality of patterns of said secondment plans by alternation of generations according to a genetic algorithm. further comprising a confinement information acquisition unit that acquires information indicating whether or not the user is confined in the restoration target;
14. The seconding plan according to any one of claims 1 to 13, wherein the seconding target for whom confinement of a user has occurred is earlier than the seconding target for whom confinement has not occurred. The secondment planning system according to item 1. further comprising a confinement information acquisition unit that acquires information indicating whether or not the user is confined in the restoration target;
A recovery priority is associated with the recovery target,
15. The dispatching plan system according to claim 1, wherein the dispatching plan is such that the higher the recovery priority, the earlier the dispatching order of the dispatching targets for which no user confinement has occurred. . 16. The staffing planning system according to any one of claims 1 to 15, wherein said operational status includes at least normal operation and shutdown. the disaster is an earthquake;
The degree of the disaster is (1) the seismic intensity at the location, or (2) the magnitude of the shaking at the location calculated from the magnitude of the epicenter, the distance from the epicenter, and the depth of the epicenter. A secondment planning system according to any one of claims 1 to 16. A control method executed by one or more information processing devices,
an operating status acquisition step of acquiring an operating status from a monitoring target facility, which is the elevator facility capable of remotely monitoring the operating status of a plurality of elevator facilities located at different locations;
an operating status estimation step of estimating the operating status of non-monitored equipment, which is the elevator equipment whose operating status cannot be remotely monitored among the elevator equipment;
a restoration target identification step of identifying a restoration target from among the elevator equipment;
An optimal solution or a quasi-optimal solution of a dispatch plan in which a combination of dispatch targets, which are recovery targets, to which a group consisting of one or more workers to perform restoration work is scheduled to be dispatched, and a dispatch order are determined for each group. a searching step of searching for a secondment plan;
In the restoration target identification step, the restoration target is identified from the monitoring target equipment according to the operation status acquired when the disaster occurs, and the operation status estimated when the disaster occurs. A control method, wherein the recovery target is specified from among the non-monitoring facilities according to the above. 2. A program for causing a computer to function as the secondment planning system according to claim 1, the program for causing the computer to function as the operating condition acquiring unit, the operating condition estimating unit, the restoration target identifying unit, and the searching unit. program.

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