Service management method and service management device

Abstract

To improve detection accuracy in detecting an occurrence of abnormality in a work cooperative system in which various works are performed in cooperation with each other, using a result of a simulation.SOLUTION: A simulation is performed using a digital space reproduced based on a real space in which a service is provided. Based on a simulation result satisfying a predetermined convergence condition, a threshold for detecting occurrence of an abnormality in one or more works performed in association with provision of the service in the real space is set for each work unit corresponding to the one or more works. In setting the threshold, a time difference between a preset standard working time and a simulated work time included in the simulation result satisfying the convergent condition is calculated. A larger threshold value is assigned to a work unit having a larger time difference than a work unit having a smaller time difference.SELECTED DRAWING: Figure 5

Description

[Technical field]

[0001] The present disclosure relates to a method and apparatus for managing the services that a business provides to its customers. [Background technology]

[0002] Japanese Patent Application Laid-Open Publication No. 2007-041950 discloses a system for performing a simulation for managing a production line. This conventional system has a plurality of models for performing the simulation. These models are constructed based on performance data of an actual production line or prediction data of the actual production line. The conventional system also records information such as components of the actual production line and past simulation results using a model corresponding to this production line. When simulating a new production line, a model suitable for simulating the new production line is identified from among the plurality of models based on this information.

[0003] In addition to JP 2007-041950 A, examples of documents showing the technical state of the technical field related to the present disclosure include JP 2019-139319 A, JP 2004-086358 A, and JP 2018-005550 A. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] JP 2007-041950 A [Patent Document 2] JP 2019-139319 A [Patent Document 3] JP 2004-086358 A [Patent Document 4] JP 2018-005550 A Summary of the Invention [Problem to be solved by the invention]

[0005] In a conventional system, a model suitable for a new production line is identified. The results of a simulation using this suitable model are compared with actual data for the new production line. If there is a discrepancy between the simulation results and the actual data, it is determined that an abnormality has occurred in the new production line.

[0006] Here, let us consider the cause of the new problem in the production line. In the production line, various tasks are performed by multiple workers (multiple humans and / or multiple robots) working together. These tasks are influenced by external factors in addition to internal factors such as the processing capacity of the workers and the content of the tasks. The various tasks include not only tasks that are highly resistant (robust) to external factors, but also tasks that are less resistant to these factors.

[0007] In conventional system simulations, no distinction is made between internal and external factors. Therefore, if the performance data for a new production line is significantly affected by external factors, there is a possibility that an abnormality occurring in the production line cannot be correctly detected. This problem is not limited to production lines, but is common to work-related systems that are easily affected by external factors. Therefore, improvements are needed to improve the accuracy of detecting the occurrence of an abnormality in such systems.

[0008] The present disclosure has been made in consideration of the above problems. One objective of the present disclosure is to provide a technology capable of improving the accuracy of detection when detecting the occurrence of an anomaly in a work-coordinated system in which various works are performed in coordination using the results of a simulation. [Means for solving the problem]

[0009] A first aspect of the present disclosure is a method for managing services provided by a business operator to a customer, and has the following characteristics. The method comprises: A step of performing a simulation using a digital space reproduced based on a real space in which the service is provided; repeating the simulation until a simulation result that satisfies a predetermined convergence condition is obtained; setting a threshold value for detecting an occurrence of an abnormality in one or more tasks performed in association with the provision of the service in the real space, for each task unit corresponding to the one or more tasks, based on a simulation result in which the convergence condition is satisfied; Includes. The step of setting the threshold value includes: calculating, for each task unit, a simulation time difference indicating a time difference between a standard task time set in advance and a simulated task time included in a simulation result that satisfies the convergence condition; a step of assigning a threshold value to the task unit according to the simulation time difference, wherein a threshold value larger than that of a task unit having a small simulation time difference is assigned to the task unit having a large simulation time difference; Includes.

[0010] The second aspect of the present disclosure has the same features as the first aspect, as described below. The task units include collective task units defined for a plurality of tasks performed by a plurality of task subjects in cooperation with each other, and individual task units defined for each task constituting the plurality of tasks. The method comprises: calculating an actual work time for the one or more tasks for each task unit while the service is being provided in the real space; Calculating an actual time difference indicating a time difference between an actual work time for the batch or individual work unit and a standard work time preset for the batch or individual work unit; determining that an abnormality has occurred in the individual work unit when the actual time difference in the batch work unit exceeds the threshold value set for the batch work unit and the actual time difference in the individual work unit exceeds the threshold value set for the individual work unit; Further includes.

[0011] A third aspect of the present disclosure has the same features as the first aspect, as described below. The task units include collective task units defined for a plurality of tasks performed by a plurality of task subjects in cooperation with each other, and individual task units defined for each task constituting the plurality of tasks. The method comprises: calculating an actual work time for the one or more tasks for each task unit while the service is being provided in the real space; Calculating an actual time difference indicating a time difference between an actual work time for the batch or individual work unit and a standard work time preset for the batch or individual work unit; determining that an abnormality has occurred in the batch work unit when the actual time difference in the batch work unit exceeds the threshold value set for the batch work unit and the actual time difference in the individual work unit is below the threshold value set for the individual work unit; Further includes.

[0012] A fourth aspect of the present disclosure has the following further features in the second or third aspect. The method comprises: when it is determined that an abnormality has occurred in the individual task unit or the batch task unit, reallocating resources to be input to the one or more tasks; repeating the simulation using the digital space in which the resources have been reallocated until a new simulation result is obtained in which the convergence condition is satisfied; resetting the threshold for each unit of work based on the new simulation results; Further includes.

[0013] A fifth aspect of the present disclosure is an apparatus for managing services provided from a business operator to a customer, and has the following features. The apparatus includes a processor. The processor, A process of performing a simulation using a digital space reproduced based on a real space in which the service is provided; repeating the simulation until a simulation result that satisfies a predetermined convergence condition is obtained; a process of setting a threshold value for detecting an occurrence of an abnormality in one or more tasks performed in association with the provision of the service in the real space, for each task unit corresponding to the one or more tasks, based on a simulation result in which the convergence condition is satisfied; is configured to run The processor further includes, in the threshold setting process, A process of calculating, for each task unit, a simulation time difference indicating a time difference between a standard task time set in advance and a simulated task time included in a simulation result that satisfies the convergence condition; A process of assigning a threshold value corresponding to the simulation time difference to the task unit; is configured to run In the threshold setting process, a larger threshold is set for the task unit having a larger simulation time difference than for the task unit having a smaller simulation time difference.

[0014] A sixth aspect of the present disclosure has the same features as the fifth aspect and further includes the following features. The task units include collective task units defined for a plurality of tasks performed by a plurality of task subjects in cooperation with each other, and individual task units defined for each task constituting the plurality of tasks. The processor further comprises: calculating an actual work time for the one or more tasks for each task unit while the service is being provided in the real space; Calculating an actual time difference indicating a time difference between an actual work time for the batch or individual work unit and a standard work time preset for the batch or individual work unit; a process of determining that an abnormality has occurred in the individual task unit when the actual time difference in the batch task unit exceeds the threshold value set for the batch task unit and the actual time difference in the individual task unit exceeds the threshold value set for the individual task unit; is configured to run

[0015] A seventh aspect of the present disclosure has the same features as the fifth aspect and further includes the following features. The task units include collective task units defined for a plurality of tasks performed by a plurality of task subjects in cooperation with each other, and individual task units defined for each task constituting the plurality of tasks. The processor further comprises: calculating an actual work time for the one or more tasks for each task unit while the service is being provided in the real space; Calculating an actual time difference indicating a time difference between an actual work time for the batch or individual work unit and a standard work time preset for the batch or individual work unit; A process of determining that an abnormality has occurred in the batch task unit when the actual time difference in the batch task unit exceeds the threshold value set for the batch task unit and the actual time difference in the individual task unit falls below the threshold value set for the individual task unit; is configured to run

[0016] An eighth aspect of the present disclosure has the sixth or seventh aspect further including the following features. The processor further comprises: a process of reallocating resources allocated to the one or more tasks when it is determined that an abnormality has occurred in the individual task unit or the batch task unit; repeating the simulation using the digital space in which the resources have been reallocated until a new simulation result that satisfies the convergence condition is obtained; A process of resetting the threshold for each task unit based on the new simulation result; is configured to run Effect of the Invention

[0017] According to the first or fifth aspect, a threshold for detecting the occurrence of an abnormality in one or more tasks performed in relation to the provision of a service in the real space is set for each task unit corresponding to the one or more tasks. When setting this threshold, a time difference between a standard task time set in advance and a simulated task time included in a simulation result that satisfies a convergence condition (i.e., a simulation time difference) is calculated.

[0018] A large simulation time difference means that the tasks constituting a task unit have low resistance to external factors. In this regard, according to the first or fifth viewpoint, a larger threshold is assigned to a task unit with a large simulation time difference than a task unit with a smaller simulation time difference. Therefore, when multiple tasks are performed by multiple task subjects in cooperation with each other, it is possible to detect the occurrence of an abnormality in a task unit with high accuracy.

[0019] According to the second or sixth aspect, when the actual time difference in a batch work unit exceeds a threshold value set for the batch work unit and the actual time difference in an individual work unit exceeds a threshold value set for the individual work unit, it is possible to determine that an abnormality has occurred in the individual work unit.

[0020] According to the third or seventh aspect, when the actual time difference in a batch work unit exceeds a threshold value set for the batch work unit and the actual time difference in an individual work unit falls below a threshold value set for the individual work unit, it is possible to determine that an abnormality has occurred in the batch work unit.

[0021] According to the fourth or eighth aspect, when it is determined that an abnormality has occurred in an individual or batch task unit, resources input to one or more tasks are reallocated, and the simulation is repeated until a new simulation result that satisfies the convergence condition is obtained. Therefore, even if an abnormality occurs in an individual or batch task unit, it is possible to quickly resolve this abnormal state. [Brief description of the drawings]

[0022] [Figure 1] FIG. 1 is a diagram illustrating the concept of a logistics service, which is an example of a service that a business operator provides to a customer. [Diagram 2] 2 is a diagram illustrating a specific example of the transportation and delivery system described in FIG. 1, and a configuration example of a real space in which logistics-related services are provided. FIG. [Diagram 3] FIG. 2 is a diagram illustrating an example of a unit of work defined in a digital space. [Figure 4] This figure explains an example of the total work time for the product of a batch of work units, when multiple tasks performed consecutively in the digital space described in Figure 3 are treated as a batch of work units, and the standard work time with which the total work time is compared. [Diagram 5] FIG. 13 is a diagram showing an example of a relationship between a simulation time difference and a threshold value. [Figure 6] FIG. 13 is a diagram illustrating an example of the configuration of a management device related to a threshold setting process. [Figure 7] FIG. 2 illustrates an example of the configuration of a management device related to a process for determining whether an abnormality has occurred. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0023] Hereinafter, a service management method and a management device according to an embodiment of the present disclosure will be described with reference to the drawings. The management method according to the embodiment is realized by computer processing performed in the management device according to the embodiment. In each drawing, the same or corresponding parts are given the same reference numerals, and the description thereof will be simplified or omitted.

[0024] 1. Service Examples The management device according to the embodiment is a device for managing services provided by a vendor to a customer. In the embodiment, an example will be described in which the service provided by the vendor to the customer is a "service related to logistics" (hereinafter also referred to as a "logistics service"). In the logistics service, various tasks are performed to deliver the products or goods requested by the customer to the customer. The "vendor" referred to here may be an individual business owner or a corporate business owner. If the "vendor" is a corporate business owner, the "vendor" may be composed of a single company or may be a collection of multiple companies. Furthermore, the "customer" includes not only individual customers but also corporate customers.

[0025] Fig. 1 is a diagram for explaining the concept of a logistics service. Fig. 1 illustrates a TMS system (transportation and delivery system) 100 as an example of a system that provides a logistics service LS. In the example illustrated in Fig. 1, the TMS system 100 includes a server group 10, a logistics center group 20, and a customer group 30. The server group 10 is made up of a plurality of servers. Each server that constitutes the server group 10 is directly or indirectly connected to each computer of the logistics center group 20 and the customer group 30 via a network (not shown).

[0026] Some or all of the servers constituting the server group 10 are managed, for example, by a business operator that oversees "logistics-related services." Any of the servers constituting the server group 10 accepts order information for the product PD from a computer of a customer belonging to the customer group 30. This order information is composed of, for example, information on the number of products PD, the delivery destination, and the scheduled delivery date. The server that accepts the order for the product PD places an order for the product PD with a computer of any of the logistics centers constituting the logistics center group 20 (for example, a logistics center close to the delivery destination of the product PD). This order information includes, for example, the same information as the information constituting the order information accepted by the server.

[0027] The computer of the logistics center that receives an order for the product PD, for example, checks the stock of the product PD. If there is stock of the product PD, the computer of the logistics center performs processing to deliver the product PD. If there is no stock of the product PD, the computer of the logistics center performs processing to replenish the product PD. Examples of processing to replenish the product PD include placing an order to the producer and placing an order to another logistics center.

[0028] In the process for delivering the product PD, the computer at the logistics center transmits instructions for work such as picking the product PD and processing it for delivery to the work robots and mobile terminals of workers in the logistics center. In the process for delivering the product PD, instructions for loading the packing box PK containing the product PD onto a mobile body are also transmitted to the work robots. In the process for delivering the product PD, information on the destination of the product PD, information on the route to the destination, etc. are further transmitted to the mobile body on which the packing box PK is loaded.

[0029] 2. Simulation using digital space 2-1. Real Space In the embodiment, a simulation is performed using a digital space in which the logistics service LS described in Fig. 1 is provided (hereinafter, also referred to as "digital twin simulation" or "DTS"). This digital space is reproduced based on the real space in which the logistics service LS is provided. Fig. 2 is a diagram for explaining a specific example of the TMS system 100 described in Fig. 1 and a configuration example of the real space in which the logistics service LS is provided.

[0030] In the example shown in Fig. 2, the server group 10 includes a central server 11 and management servers 12 to 15. The central server 11 manages the management servers 12 to 15. The management server 12 is assigned to a logistics center group 20. The management server 13 is assigned to a customer group 30. The management server 14 is assigned to a mobile object group 40. The management server 15 is assigned to an infrastructure group 50. The logistics center group 20, the customer group 30, the mobile object group 40, and the infrastructure group 50 exist in the real space RSP, and are entities, objects, or environments involved in the provision of the logistics service LS.

[0031] The management servers 12-15 transmit information to the central server 11. Examples of information transmitted from the management servers 12-15 to the central server 11 include various types of information collected by each management server from the group (such as the logistics center group 20) to which it is assigned. This information is stored in a database held by the central server 11 and used for the DTS.

[0032] The management servers 12 and 14 also receive information from the central server 11. An example of the information received from the central server 11 is allocation information of resources (Assets) input into work carried out in relation to the provision of the logistics service LS. The allocation information is generated based on the results of the DTS (hereinafter also referred to as "simulation results"). The management server 13 receives information on the delivery status of the product PD from the central server 11. The information on the delivery status is generated based on, for example, information on the shipping status of the product PD received by the central server 11 from the management server 12, location information of a moving object received by the central server 11 from the management server 14, etc.

[0033] The group of logistics centers 20 includes logistics centers DC1, DC2, ..., DCm (m ≥ 3). Robots RB and workers WK are stationed at logistics center DC1 and are engaged in various tasks performed at logistics center DC1. The robots RB and workers WK are the "work subjects" of various tasks performed at logistics center DC1 in relation to the provision of logistics services LS, and are also the "resources" input to these tasks. Like logistics center DC1, robots RB and workers WK are also stationed at logistics centers DC2, ..., DCm. Hereinafter, logistics centers DC1, DC2, ..., DCm are also collectively referred to as "logistics centers DC."

[0034] The logistics center DC exchanges various information with the management server 12. Examples of information transmitted from the logistics center DC to the management server 12 include monitoring information of the product PD and the work subjects (i.e., the robot RB and the worker WK) at the logistics center DC. Examples of the monitoring information of the product PD include position information of the product PD. This position information is obtained, for example, by reading information of a wireless tag (BLE, RFID, etc.) attached to the product PD using a tag reader installed at each location in the logistics center DC. Examples of the monitoring information of the work subjects include status, position, and movement information of the work subjects. This information is obtained, for example, from a visible light camera and an infrared camera installed at each location in the logistics center DC. This information may be obtained based on information from various sensors mounted on the robot RB and information from a wearable terminal worn by the worker WK.

[0035] On the other hand, the information transmitted from the management server 12 to the logistics center DC is, for example, allocation information of resources (i.e., robots RB and workers WK). This allocation information is information for determining the content of the work that the resources should be engaged in, the location in the logistics center DC where this work will be performed, the time period during which this work will be performed, etc., and is generated based on the simulation results.

[0036] The customer group 30 includes destinations DS1, DS2, ..., DSn (n ≥ 3) of the product PD. The destinations DS1, DS2, ..., DSn are typically the residences of individual customers, the offices of corporate customers, warehouses, etc. An order for the product PD is placed from a computer of a customer belonging to the customer group 30. Examples of the customer's computer include a terminal UI such as a smartphone or tablet carried by the customer. Hereinafter, the destinations DS1, DS2, ..., DSn are also collectively referred to as "destinations DS."

[0037] The customer's computer exchanges various types of information with the management server 13. An example of the information transmitted from the customer's computer to the management server 13 is order information for the product PD. The order information is composed of, for example, the number of products PD, the delivery destination DS, and the scheduled delivery date. On the other hand, an example of the information transmitted from the management server 13 to the customer's computer is information on the delivery status of the product PD.

[0038] The group of mobile objects 40 includes mobile objects MB1, ..., MBp (p >= 2) that transport the product PD from a starting point (i.e., a logistics center DC) to a destination (i.e., a delivery destination DS). Hereinafter, the mobile objects MB1, ..., MBp are also collectively referred to as "mobile object MB." The mobile object MB is the "work subject" of the delivery of the product PD carried out in connection with the provision of the logistics service LS, and is also the "resource" inputted into this delivery.

[0039] The mobile body MB is configured to move autonomously on land or in the air. A part or all of the movement of the route from the starting point to the destination may be performed under remote support by an operator. Examples of remote support by an operator include remote driving of the mobile body MB, support for the mobile body MB in recognizing the outside world, and support for the mobile body MB in making decisions regarding the actions to be taken.

[0040] The mobile body MB exchanges various information with the management server 14. Examples of information transmitted from the mobile body MB to the management server 14 include monitoring information of the mobile body MB. Examples of the monitoring information of the mobile body MB include status and position information of the mobile body MB. This information is acquired from various sensors mounted on the mobile body MB. Examples of the various sensors include a sensor that detects the remaining charge of a battery that supplies power to the motor that drives the mobile body MB, a sensor that detects the acceleration of the mobile body MB, a sensor that detects changes in the rotation angle of the mobile body MB in the X-, Y-, and Z-axis directions, a sensor that receives radio waves from a GPS satellite, and the like.

[0041] On the other hand, the information transmitted from the management server 14 to the mobile unit MB is exemplified by resource (i.e., mobile unit MB) allocation information. This allocation information is information for determining the content of the delivery for which the mobile unit MB is responsible, the destination to which the mobile unit MB will head to perform this delivery (e.g., the waiting area of ​​the logistics center DC), the time period for which this delivery will be performed, and the like, and is generated based on the simulation results. The information transmitted from the management server 14 to the mobile unit MB also includes charging command information. The charging command information is generated based on the remaining battery level information acquired by the management server 14 from the mobile unit MB. The charging command information includes, for example, location information of the charging facility and location information of the destination to which the mobile unit MB will head after charging is completed (e.g., the waiting area of ​​the logistics center DC).

[0042] The infrastructure group 50 includes infrastructures IS1,...,ISq (q≧2). The infrastructures IS1,...,ISq are installed, for example, on a road provided in the real space RSP or on a structure facing the road. The infrastructures IS1,...,ISq may be installed inside (e.g., indoors) or outside (e.g., rooftop) of a building present in the real space RSP. Hereinafter, the infrastructures IS1,...,ISq are also collectively referred to as "infrastructure IS".

[0043] Examples of the infrastructure IS include a wireless communication base station and a camera having a communication function. The base station as the infrastructure IS performs wireless communication with moving bodies other than the moving body MB (for example, ground moving bodies such as pedestrians, bicycles, and vehicles, and air moving bodies such as drones) and detects these moving bodies. The camera as the infrastructure IS performs recognition processing of objects included in the camera image, thereby detecting moving bodies other than the moving body MB included in the camera image. The infrastructure IS generates information on roads and aerial routes provided in the real space RSP (for example, congestion information, traffic regulation information, etc.) based on detection information of moving bodies other than the moving body MB, and transmits it to the management server 15. The infrastructure IS can also generate information on routes within a building (for example, congestion information) based on detection information of moving bodies other than the moving body MB.

[0044] 2-2. Unit of Work In the digital space reproduced based on the real space RSP, a "work unit" is defined that is performed in relation to the provision of the logistics service LS. In the real space RSP, a plurality of tasks is performed in relation to the provision of the logistics service LS by the cooperation of a plurality of task subjects. Therefore, a work unit is defined for a plurality of tasks that are performed in cooperation. However, a work unit may also be defined for each task that constitutes a plurality of tasks that are performed in cooperation. Hereinafter, for convenience of explanation, a work unit defined for the former is also referred to as a "batch working unit." Moreover, a work unit defined for the latter is also referred to as an "individual working unit."

[0045] Fig. 3 is a diagram for explaining an example of a work unit defined in a digital space. Fig. 3 illustrates an example of work performed at a logistics center DC1. In the example shown in Fig. 3, "receiving", "inspection", "processing for storage", "storage", "picking", "processing for delivery", "packing" and "shipping" are performed at the logistics center DC1. A work unit is defined for each work.

[0046] Examples of the collective work units performed in the logistics center DC1 include work including "receiving", "inspection", "processing for storage", and "storage", and work including "picking", "processing for delivery", "packing", and "shipping". The reason for this is that the logistics center DC1 is an "inventory-type logistics center" that temporarily stores received products PD (PD1, PD2, and PD3) and ships the products PD in response to orders from customers 2. If the logistics center DC1 were a "transit-type logistics center" that mainly delivers products PD, the work of "processing for storage", "storage", and "picking" would not be performed. In this case, a collective work unit is defined for the work including "receiving", "inspection", "processing for delivery", "packing", and "shipping".

[0047] In the example shown in FIG. 3, robot RB1 is responsible for the "receiving" of product PD and the transportation of this product PD from "receiving" to "inspection". Furthermore, worker WK1 is responsible for "inspection", and robot RB2 is responsible for the transportation from "inspection" to "processing for storage", or from "inspection" to "storage". Furthermore, worker WK2 is responsible for "processing for storage", and robot RB3 is responsible for the transportation from "processing for storage" to "storage". Digital space DSP1 is a reproduction of the real space where work from "receiving" to "storage" is carried out.

[0048] In the example shown in FIG. 3, the robot RB5 is responsible for "picking" the product PD and transporting the product PD from "picking" to "processing for delivery". The worker WK3 is responsible for "processing for delivery", and the robot RB6 is responsible for transporting the product PD from "processing for delivery" to "packing". The worker WK4 is responsible for "packing", and the robot RB7 is responsible for transporting the product PD from "packing" to "shipping" and for "shipping". The mobile body MB1 is responsible for delivering the packing box PK1 containing the products PD1 and PD2, and the mobile body MB2 is responsible for delivering the packing box PK2 containing the products PD2 and PD3. The digital space DSP2 is a reproduction of the real space in which the work from "picking" to "delivery" is performed.

[0049] 2-3.Prescribed convergence conditions In the DTS, the central server 11 inputs time series information acquired in real time from the management servers 12-15, or virtually generated time series information, into the digital space DSP. Then, a simulation is performed on the future operating status of the logistics service when resources such as robots RB, workers WK, and mobile objects MB stationed in the logistics center DC are input into the digital space DSP and operated. The simulation result includes information on the future operating status. Examples of the information on the future operating status include the status, position, and movement information of the work subjects (robots RB and workers WK), the status and position information of the work subjects (mobile objects MB), and the position information of the products PD moving within the digital space DSP.

[0050] Here, the time series information of the location of the product PD is useful as an index for evaluating whether the logistics service LS is being smoothly provided by the resources input into the digital space DSP. Therefore, in the embodiment, based on the time series information of the location of the product PD processed in a batch work unit performed in the digital space DSP, the total work time for this product PD (hereinafter referred to as "total work time" or "TWT") is calculated. For example, the TWT is calculated for all products SD processed in the batch work unit. The TWT may be calculated focusing only on a specific product PD (for example, product PD1). When the TWT is calculated for multiple products PD, the average value of these times is calculated.

[0051] Consider a batch task unit that groups together multiple tasks that are performed consecutively in the real space RSP from the first task to the last task. For example, the tasks including "receiving," "inspection," "processing for storage," and "storage" described in Figure 3 correspond to multiple tasks that are performed consecutively. In this case, "receiving" corresponds to the first task, and "storage" corresponds to the last task. A task including "picking," "processing for delivery," "packing," "shipping," and "delivery" is also an example of multiple tasks that are performed consecutively. In this case, "picking" corresponds to the first task, and "delivery" corresponds to the last task.

[0052] If the first task to the last task are grouped together, the total time required to complete all tasks that make up the batch work unit can be considered as the time required to complete all tasks performed in the digital space DSP that reproduces this real space RSP. In the DTS, the TWT for the product PD in such a batch work unit is compared with a standard work time (hereinafter also referred to as "SWT_b") that is set in advance. Then, the adjustment (allocation) of resources input to the digital space DSP, the calculation of the TWT, and the evaluation of this TWT are repeated until a TWT shorter than SWT_b is obtained.

[0053] The fact that TWT is shorter than SWT_b means that the "predetermined convergence condition" for DTS is satisfied. When it is determined that TWT is shorter than SWT_b as a result of comparing TWT with SWT_b, the simulation result is saved. The simulation result is saved in association with, for example, information on the digital space DSP that is the target of DTS, resource allocation information in this digital space DSP, definition information for the batch work unit, information on the future time period that is the target of DTS, and the like.

[0054] FIG. 4 is a diagram for explaining an example of TWT and SWT_b when a plurality of tasks performed consecutively in the digital space DSP1 described in FIG. 3 are regarded as a batch task unit. FIG. 4 shows the times at which one product PD is processed. Specifically, "receiving" is performed between times T1 and T2, "inspection" is performed between times T5 and T6, and "processing for storage" is performed between times T9 and T10. Transportation from "receiving" to "inspection" is performed between times T4 and T5, transportation from "inspection" to "processing for storage" is performed between times T7 and T8, and transportation from "processing for storage" to "storage" is performed between times T11 and T12.

[0055] Depending on the processing speed of the task entity and the allocation of resources, there will be times when the product PD waits for processing to begin. The times T2 to T3, T6 to T7, and T10 to T11 correspond to times when the product PD waits for transportation to begin. The time from T4 to T5 corresponds to the time when the product PD waits for "inspection" to begin, and the time from T8 to T9 corresponds to the time when the product PD waits for "processing for storage" to begin.

[0056] As already explained, "receiving", "inspection", "processing for storage" and "storage" are multiple tasks that are performed consecutively in the digital space DSP1. In addition, tasks that accompany these tasks (i.e., transportation between two consecutive tasks) are also multiple tasks that are performed consecutively in the digital space DSP1. Therefore, if a batch task unit is defined for these tasks, the elapsed time from time T1 to T12 can be calculated as TWT. If this elapsed time is shorter than SWT_b, the simulation result is saved.

[0057] 4, the information on the digital space DSP1, the resource allocation information in this digital space DSP1, the information that the batch work unit is defined for a series of operations from "receiving" to "storage", and the information on the elapsed time from time T1 to T12 are saved as the simulation results. Information on the future time period that was the subject of the simulation is also added to the simulation results.

[0058] Incidentally, the DTS such as the calculation of TWT in the digital space DSP2, the judgment of the convergence condition, and the adjustment (allocation) of the resources input to the digital space DSP2 described in Fig. 3 are performed in the same manner as that in the digital space DSP1 described in Fig. 4. When the convergence condition for the DTS in the digital space DSP2 is satisfied (i.e., when it is judged that the TWT in the digital space DSP2 is shorter than SWT_b), the simulation result is saved.

[0059] 3. Determining the occurrence of abnormalities 3-1.Work time threshold What should be noted here is that the sum of the work times tp (tp1 to tp11) for each individual task unit corresponds to TWT. In addition, the length of this work time tp is thought to vary depending on internal factors such as the content of the tasks that make up the individual task unit (i.e., a single task) and the processing capacity of the task subject, but it is also thought to vary depending on external factors such as a flood of orders for the product PD and congestion on the route along which the robot RD and mobile body MB transport the product PD.

[0060] Therefore, in the embodiment, a "threshold TH" is set for the task time for an individual task unit based on the length of task time tp for the individual task unit when the simulation results are saved. In setting the threshold TH, first, a standard task time (hereinafter also referred to as "SWT_i") for this individual task unit is calculated based on internal factors that affect the tasks that make up the individual task unit. Next, the time difference (simulation time difference) Δts between the task time tp for the individual task unit when it is determined that TWT is shorter than SWT_b and SWT_i for this individual task unit is calculated.

[0061] A small time difference Δts means that the work constituting the individual work unit is highly resistant to external factors, and a large time difference Δts means that the work constituting the individual work unit is less resistant to external factors. The threshold value TH is set, for example, so that the threshold value TH increases as the time difference Δts increases. Figure 5 is a diagram showing an example of the relationship between the time difference Δts and the threshold value TH. In the example shown in Figure 5, the value of the threshold value TH increases in proportion to the time difference Δts (=tp-SWT_i).

[0062] 3-2. Judgment using threshold value TH In the embodiment, the occurrence of an abnormality in the work carried out in relation to the provision of the logistics service LS in the real space RSP is detected using a threshold value TH set according to the time difference Δts. The occurrence of an abnormality is detected by focusing on the individual task unit for which the threshold value TH is set. As already explained, in the real space RSP, monitoring information of the work subjects (i.e., the robot RB, the worker WK, and the mobile body MB) engaged in the work carried out in relation to the provision of the logistics service LS is acquired. Then, based on this monitoring information, the actual work time (hereinafter also referred to as "AWT") for the individual task unit is calculated, and the time difference (actual time difference) Δta between the AWT and the standard work time for this individual task unit (i.e., SWT_i) is calculated.

[0063] When the time difference Δta exceeds the threshold TH, there is a high probability that an abnormality has occurred in the individual task unit. However, when the load on the tasks that make up an individual task unit is temporarily high, the time difference Δta is expected to exceed the threshold TH, but this high load state is also expected to be resolved in the near future. Therefore, in the embodiment, when it is determined that an abnormality has occurred in an individual task unit, the time difference Δta is calculated with further attention to the batch task unit that includes this individual task unit.

[0064] The time difference Δta in a batch task unit can be calculated, for example, based on the AWT in the batch task unit and the standard task time in this batch task unit. The threshold value TH (TH_b) of the batch task unit is calculated, for example, by accumulating the standard task time in the individual task units that make up this batch task unit. Note that the threshold value TH (TH_b) of the batch task unit that groups together the first task to the last task of multiple tasks that are performed consecutively in the real space RSP is the same value as the above-mentioned SWT_b. In the embodiment, if the time difference Δta in both the individual task units and the batch task unit exceeds the threshold value TH, it is determined that an abnormality has occurred in the individual task unit.

[0065] Here, even if it is determined that no abnormality has occurred in an individual task unit, a case is assumed in which an abnormality has occurred in a batch task unit including this individual task unit. Therefore, in an embodiment, regardless of the result of the abnormality determination in the tasks constituting an individual task unit, the time difference Δta may be calculated by further focusing on the batch task unit including this individual task unit. Then, if the time difference Δta in the individual task unit is below the threshold value TH(TH_i) but the time difference Δta in the batch task unit is above the threshold value TH(TH_b), it may be determined that an abnormality has occurred in the batch task unit.

[0066] In this manner, according to the embodiment, the threshold value TH is set according to the resistance to external factors, and therefore, when multiple tasks are performed by multiple task subjects in cooperation with each other, it becomes possible to detect the occurrence of an abnormality in each individual task or in a batch task with high accuracy.

[0067] 4. Example of management device configuration Next, a specific configuration example of the management device according to the embodiment will be described with reference to Figures 6 and 7. Figure 6 is a diagram showing a configuration example of the management device related to the setting process of the threshold value TH.

[0068] 6, the central server 11 includes various databases 61a to 61h, a resource allocation unit 62, a DTS execution unit, a result evaluation unit 64, an allocation determination unit 65, and a threshold setting unit 66. The functional units 62 to 66 shown in FIG. 6 are realized by a processor included in the central server 11 executing a predetermined program stored in a storage device of the central server 11.

[0069] The various databases 61a to 61h are formed in a predetermined area of ​​the storage device of the central server 11. The database 61a stores order information DOD (30, 10) of a product PD from a customer. This order information (30, 10) is information transmitted from the customer's computer to the central server 11 via the management server 13. The order information (30, 10) may be virtually generated in the central server 11 or an external server.

[0070] The database 61b stores order information DOD (10, 20) for the product PD that the central server 11 transmits to the logistics center DC via the management server 12. The order information (10, 20) may be virtually generated in the central server 11 or an external server.

[0071] The database 61c stores information DDC of the logistics center DC received from the management server 12. The information DDC may be virtually generated in the central server 11 or an external server. The information DDC includes monitoring information of the product PD and the work subjects (i.e., the robot RB and the worker WK) at the logistics center DC. An example of the monitoring information of the product PD is position information of the product PD. An example of the monitoring information of the work subjects is status, position and movement information of the work subjects.

[0072] The database 61d stores the information DMB of the moving object MB received from the management server 14. The information DMB may be virtually generated in the central server 11 or an external server. The information DMB includes monitoring information of the moving object MB. Examples of the monitoring information of the moving object MB include the state and location information of the moving object MB.

[0073] The database 61e stores information DIS received from the management server 15. The information DIS may be virtually generated in the central server 11 or an external server. The information DIS includes information on detection of moving objects by the infrastructure IS, information on roads and air routes provided in the real space RSP, and the like.

[0074] The database 61f stores resource information DAS. This information DAS includes information on resources that can be input to work performed in relation to the provision of the logistics service LS (resource information) and information on resources generated based on the simulation results (allocation information). The resource information and allocation information are set, for example, for each space (e.g., DSP1, DSP2) of the digital space DSP.

[0075] The database 61g stores information DMD of various models used in the execution of the DTS. Examples of the various models include behavior models constructed in consideration of the content of work performed in relation to the provision of the logistics service LS in the real space RSP, the movement of the work subject, and the behavior of mobile objects other than the work subject. Note that the various models are periodically verified and updated as appropriate in order to properly represent the latest state of the real space RSP.

[0076] The database 61h stores information DTH on the threshold TH for the work time. This threshold TH is set for individual and batch work units. The threshold TH may be associated with definition information for the individual and batch work units and information on future time periods. Associating the definition information for the individual and batch work units with the threshold TH makes it easier to identify the threshold TH. Associating information on future time periods with the threshold TH makes it possible to detect the occurrence of an abnormality by switching the threshold TH depending on the future time period in which the individual work unit or batch work unit is performed.

[0077] The resource allocation unit 62 adjusts the resources to be input to the digital space DSP. The resource adjustment is performed by arbitrarily allocating the resources that can be input to the digital space DPS where DTS is performed to individual task units and batch task units based on the resource information stored in the database 61f. In order to increase the satisfaction of the convergence condition, allocation information generated based on past simulation results may be used when adjusting the resources. The resource allocation unit 62 transmits information on the adjusted resources to the DTS execution unit 63.

[0078] The DTS execution unit 63 executes the DTS. The execution of the DTS is performed, for example, for one segment of the space of the digital space DSP. In this case, various models used for executing the DTS for one segment of the digital space DSP are extracted from the database 61g. Then, resource information received from the resource allocation unit 62 and time series information acquired in real time from the management servers 12 to 15 are input to these models. Virtually generated time series information may be input to these models instead of the real time information.

[0079] Then, the TWT for a batch of tasks that are performed consecutively in one section of the digital space DSP is calculated. The DTS execution unit 63 transmits this TWT to the result evaluation unit 64 together with information on the digital space DSP that was the subject of the DTS.

[0080] The result evaluation unit 64 compares the TWT received from the DTS execution unit 63 with SWT_b. If the TWT is shorter than the SWT_b, the result evaluation unit 64 determines that the convergence condition is satisfied, and transmits the simulation result to the allocation determination unit 65 and the threshold setting unit 66. If not, the result evaluation unit 64 transmits a resource readjustment command to the resource allocation unit 62. In this case, the resource allocation unit 62 readjusts the resources to be input to the digital space DSP, and the DTS execution unit 63 executes the DTS based on the information of the readjusted resources.

[0081] The allocation determination unit 65 generates allocation information of resources to be put into the real space RSP for a future time period based on the simulation results received from the result evaluation unit 64, and transmits the resource allocation information to the management servers 12 and 14. In this case, the management servers 12 and 14 allocate new resources and convert resources that have already been allocated based on the allocation information. The allocation determination unit 65 also writes the determined resource allocation information into the database 61f.

[0082] The threshold setting unit 66 sets a threshold TH for the task time for individual and batch task units in a future time period based on the simulation results received from the result evaluation unit 64. The threshold TH (TH_i) for the individual task unit is, for example, a value obtained by multiplying the time difference Δts for the individual task unit described in FIG. 4 by a coefficient k (k>1.0) according to the magnitude of the time difference Δts (TH_i=Δts·k). The threshold TH (TH_b) for the batch task unit is, for example, an integrated value of the thresholds TH for the individual task units (TH_b=ΣΔts·k). The threshold setting unit 66 also writes information about the set threshold TH to the database 61h.

[0083] Fig. 7 is a diagram showing a configuration example of a management device related to the process of determining the occurrence of an abnormality. In the example shown in Fig. 7, the central server 11 includes an actual information collection unit 71, an abnormality determination unit 72, an alert generation unit 73, and a resource reallocation unit 74. The functional units 71 to 74 shown in Fig. 7 are realized by a processor included in the central server 11 executing a predetermined program stored in a storage device of the central server 11.

[0084] The actual information collection unit 71 collects time-series information acquired in real time from the management servers 12 to 15. This real-time information is composed of information transmitted by the logistics center group 20, the customer group 30, the mobile object group 40, and the infrastructure group 50 to the management servers assigned to these groups.

[0085] The abnormality determination unit 72 calculates the actual work time (i.e., AWT) for each individual and batch task unit based on the real-time information collected by the actual information collection unit 71. The AWT is calculated by focusing on the batch task unit for which the threshold value TH is set and the individual task units contained in this batch task unit. After the AWT is calculated, the abnormality determination unit 72 calculates the time difference Δta based on the AWT and the standard work times (i.e., SWT_i and SWT_b) corresponding to the individual task unit and the batch task unit.

[0086] Once the time difference Δta has been calculated, the abnormality determination unit 72 compares the time difference Δta with a threshold value TH. If the time difference Δta between the individual task units exceeds the threshold value TH (TH_i) and the time difference Δta between the batch task units exceeds the threshold value TH (TH_d), the abnormality determination unit 72 determines that an abnormality has occurred in the individual task unit. If the time difference Δta between the individual task units falls below the threshold value TH (TH_i) and the time difference Δta between the batch task units exceeds the threshold value TH (TH_d), the abnormality determination unit 72 may determine that an abnormality has occurred in the batch task unit.

[0087] When it is determined that an abnormality has occurred, the abnormality determination unit 72 generates abnormality occurrence information and transmits it to the alert generation unit 73. The abnormality occurrence information includes, for example, information on the time when the abnormality occurred and information identifying the individual or batch task unit in which the abnormality occurred. When the task constituting the individual task unit in which the abnormality has occurred is the delivery of a product PD by a moving object MB, information identifying this moving object MB may be generated.

[0088] Furthermore, when it is determined that an abnormality has occurred, the abnormality determination unit 72 transmits a resource readjustment command to the resource reallocation unit 74. The basic functions of the resource reallocation unit 74 are common to those of the resource allocation unit 62. Therefore, when a resource readjustment command is received, the resource reallocation unit 74 readjusts the resources to be input to the digital space DSP that reproduces the real space RSP including the individual or batch task unit in which it has been determined that an abnormality has occurred, and the DTS execution unit 63 executes the DTS based on the information of the readjusted resources. In other words, when it is determined that an abnormality has occurred, the DTS is executed.

[0089] As already explained, when DTS is executed, the TWT is calculated and evaluated. Furthermore, until the convergence condition is satisfied, the adjustment (allocation) of the resources to be input to the digital space DSP, the calculation of the TWT, and the evaluation of the TWT are repeated. Then, when the convergence condition is satisfied, allocation information of the resources to be input to the real space RSP in the future time period is generated and transmitted to the management servers 12 and 14. In this case, the management servers 12 and 14 allocate new resources and convert already allocated resources based on the allocation information.

[0090] The alert generation unit 73 generates alert information based on the abnormality occurrence information received from the abnormality determination unit 72, and transmits the alert information to the management server 12 or 14. Since the abnormality occurrence information includes information identifying the individual or batch task unit in which the abnormality occurred, the alert generation unit transmits the alert information to the management server 12 or 14 that has jurisdiction over the tasks that make up this individual or batch task unit.

[0091] 5.Effects According to the embodiment described above, the threshold value TH is set according to the resistance to external factors. Therefore, when multiple tasks are performed by multiple task subjects in cooperation with each other, it is possible to detect the occurrence of an abnormality in individual or batch tasks with high accuracy. Furthermore, when an abnormality occurs in an individual or batch task, the DTS is executed, and allocation information of resources to be input to the real space RSP in the future time period is generated. Therefore, even if an abnormality occurs in an individual or batch task, it is possible to quickly resolve this abnormal state.

[0092] 6.Other Services In the embodiment, an example of DTS using a digital space where a logistics service LS is provided has been described. However, the present disclosure can also be applied to other services provided by a business operator (vendor) to a customer (customer). Examples of other services include a service related to the supply of a product PD and a service related to the recycling of unnecessary items. In the service related to the supply of a product PD, for example, various operations such as production, subdivision, and packaging of the product PD requested by a customer (for example, a corporate customer) are performed at the business operator's base (for example, a factory). In addition, the delivery of this product PD to a destination DS (for example, a logistics center group 20) is performed by a mobile object. In the service of unnecessary items, for example, collection of an item determined to be unnecessary by a customer (for example, an individual customer) and delivery to a destination DS (for example, a business operator's factory) are performed by a mobile object. In addition, various operations such as disassembly, repair, and remanufacturing of the collected item are performed at the destination DS (for example, a business operator's factory). [Explanation of symbols]

[0093] 10 Servers 11 Control Server 12~15 Management Server 20 Logistics Centers 30 customer groups 61a~61h Database 62 Resource Allocation Department 63 DTS Executive Department 64 Results Evaluation Section 65 Allocation Decision Department 66 Threshold setting unit 71 Actual Information Collection Department 72 Abnormality determination section 73 Alert Generation Unit 74 Resource Reallocation Department 100 TMS Systems LS Logistics Services TH Threshold TH_b Bulk work unit threshold TH_i Individual work unit threshold RSP Real Space DSP Digital Space SWT_b, SWT_i Standard working time tp Working time for individual operations Δts Simulation time difference Δta real time difference

Claims

1. A method for managing services provided by a business to a customer, comprising: A step in which a computer performs a simulation using a digital space reproduced based on a real space in which the service is provided; The computer repeats the simulation until a simulation result that satisfies a predetermined convergence condition is obtained; a step of setting, by the computer, a threshold value for detecting occurrence of an abnormality in one or more tasks performed in association with the provision of the service in the real space, for each task unit corresponding to the one or more tasks, based on a simulation result in which the convergence condition is satisfied; Including, The step of setting the threshold value comprises: calculating, for each task unit, a simulation time difference indicating a time difference between a standard task time set in advance and a simulated task time included in a simulation result that satisfies the convergence condition; a step of assigning a threshold value to the task unit according to the simulation time difference, the threshold value being larger for the task unit having a larger simulation time difference than for the task unit having a smaller simulation time difference; A service management method comprising:

2. 2. The method of claim 1 , The task unit includes a collective task unit defined for a plurality of tasks performed by a plurality of task subjects in cooperation with each other, and an individual task unit defined for each task constituting the plurality of tasks; A step in which the computer calculates an actual work time for the one or more tasks for each task unit while the service is being provided in the real space; A step in which the computer calculates an actual time difference indicating a time difference between an actual work time for the batch or individual work unit and a standard work time previously set for the batch or individual work unit; The computer determines that an abnormality has occurred in the individual work unit when the actual time difference in the batch work unit exceeds the threshold value set for the batch work unit and the actual time difference in the individual work unit exceeds the threshold value set for the individual work unit; The service management method further comprising:

3. 2. The method of claim 1 , The task unit includes a collective task unit defined for a plurality of tasks performed by a plurality of task subjects in cooperation with each other, and an individual task unit defined for each task constituting the plurality of tasks; A step in which the computer calculates an actual work time for the one or more tasks for each task unit while the service is being provided in the real space; A step in which the computer calculates an actual time difference indicating a time difference between an actual work time for the batch or individual work unit and a standard work time previously set for the batch or individual work unit; The computer determines that an abnormality has occurred in the batch work unit when the actual time difference in the batch work unit exceeds the threshold value set for the batch work unit and the actual time difference in the individual work unit falls below the threshold value set for the individual work unit; The service management method further comprising:

4. 4. The method according to claim 2 or 3, When it is determined that an abnormality has occurred in the individual task unit or the batch task unit, the computer reallocates resources input to the one or more tasks; repeating the simulation by the computer using the digital space in which the resources have been reallocated until a new simulation result in which the convergence condition is satisfied is obtained; The computer resets the threshold for each unit of work based on the new simulation result; The service management method further comprising:

5. A device for managing services provided by a business operator to a customer, comprising: A process of performing a simulation using a digital space reproduced based on a real space in which the service is provided; repeating the simulation until a simulation result that satisfies a predetermined convergence condition is obtained; a process of setting a threshold value for detecting an occurrence of an abnormality in one or more tasks performed in association with the provision of the service in the real space, for each task unit corresponding to the one or more tasks, based on a simulation result in which the convergence condition is satisfied; a processor configured to execute The processor, in the process of setting the threshold value, further A process of calculating, for each task unit, a simulation time difference indicating a time difference between a standard task time set in advance and a simulated task time included in a simulation result that satisfies the convergence condition; A process of assigning a threshold value corresponding to the simulation time difference to the task unit; configured to run In the threshold setting process, a larger threshold is set for the task unit having a larger simulation time difference than for the task unit having a smaller simulation time difference. A service management device comprising:

6. 6. The apparatus of claim 5, The task unit includes a collective task unit defined for a plurality of tasks performed by a plurality of task subjects in cooperation with each other, and an individual task unit defined for each task constituting the plurality of tasks; The processor further comprises: calculating an actual work time for the one or more tasks for each task unit while the service is being provided in the real space; A process of calculating an actual time difference indicating a time difference between an actual work time for the batch or individual work unit and a standard work time previously set for the batch or individual work unit; a process of determining that an abnormality has occurred in the individual task unit when the actual time difference in the batch task unit exceeds the threshold value set for the batch task unit and the actual time difference in the individual task unit exceeds the threshold value set for the individual task unit; A service management device configured to execute the above-mentioned procedure.

7. 6. The apparatus of claim 5, The task unit includes a collective task unit defined for a plurality of tasks performed by a plurality of task subjects in cooperation with each other, and an individual task unit defined for each task constituting the plurality of tasks; The processor further comprises: calculating an actual work time for the one or more tasks for each task unit while the service is being provided in the real space; Calculating an actual time difference indicating a time difference between an actual work time for the batch or individual work unit and a standard work time preset for the batch or individual work unit; A process of determining that an abnormality has occurred in the batch task unit when the actual time difference in the batch task unit exceeds the threshold value set for the batch task unit and the actual time difference in the individual task unit falls below the threshold value set for the individual task unit; A service management device configured to execute the above-mentioned procedure.

8. 8. An apparatus according to claim 6 or 7, comprising: The processor further comprises: a process of reallocating resources to be input to the one or more tasks when it is determined that an abnormality has occurred in the individual task unit or the batch task unit; repeating the simulation using the digital space in which the resources have been reallocated until a new simulation result that satisfies the convergence condition is obtained; A process of resetting the threshold for each task unit based on the new simulation result; A service management device configured to execute the above-mentioned procedure.

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