Work status monitoring system, work status monitoring method, and work status monitoring program

Abstract

To provide a work state monitoring system, a work state monitoring method, and a work state monitoring program that can prevent difficulty in specifying a notable event.SOLUTION: A work state monitoring system according to the present disclosure comprises: an event detection unit that detects a plurality of events that have occurred in a work area; a network generation unit that generates an event network configured by a plurality of nodes representing the plurality of events detected by the event detection unit and a plurality of edges representing an occurrence order of the plurality of nodes; an adjustment unit that adjusts a resolution of the event network generated by the network generation unit to a designated resolution; a converting unit that converts the event network whose resolution has been adjusted by the adjustment unit into information representing a relation of the generation order of the plurality of events; and an output section that outputs a conversion result by the converting unit.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The present disclosure relates to a work status monitoring system, a work status monitoring method, and a work status monitoring program. [Background technology]

[0002] In recent years, there has been a demand for efficient monitoring of the status of multiple tasks in a work area. Related technology is disclosed in, for example, Patent Document 1.

[0003] Patent Document 1 discloses a work analysis device that analyzes work that includes multiple steps. This work analysis device includes a receiving unit that receives captured images of a work area, a detection unit that analyzes the captured images and detects the position and orientation of a worker working in the work area, a determination unit that determines the step that the worker is working on based on the position and orientation of the worker, and a generation unit that measures the work time for each step and generates a time chart showing the steps of the work performed by the worker. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] JP 2020-184250 A Summary of the Invention [Problem to be solved by the invention]

[0005] However, the work analysis device disclosed in Patent Document 1 had a problem in that, for example, when a task involving many steps is performed by multiple workers, the amount of information shown on the time chart becomes large, making it difficult to identify noteworthy events, such as the occurrence of an abnormality.

[0006] The present disclosure has been made in consideration of the above background, and aims to provide a work status monitoring system, a work status monitoring method, and a work status monitoring program that are capable of preventing it from becoming difficult to identify noteworthy events. [Means for solving the problem]

[0007] The work status monitoring system according to the present disclosure includes an event detection unit that detects a plurality of events occurring in a work area, a network generation unit that generates an event network composed of a plurality of nodes representing the plurality of events detected by the event detection unit and a plurality of edges representing the order of occurrence of the plurality of nodes, an adjustment unit that adjusts the resolution of the event network generated by the network generation unit to a specified resolution, a conversion unit that converts the event network whose resolution has been adjusted by the adjustment unit into information representing the relationship between the order of occurrence of a plurality of events, and an output unit that outputs the conversion result by the conversion unit. This work status monitoring system adjusts the resolution of information on the work status, such as a DSM, presented to a user to a desired resolution, thereby making it possible to prevent difficulty in identifying noteworthy events, such as the occurrence of an abnormality, even when, for example, a plurality of tasks are performed in a work area by a plurality of workers or work robots.

[0008] The conversion unit may convert the event network, whose resolution has been adjusted by the adjustment unit, into a Design Structure Matrix (DSM), which is information representing the relationship between the order of occurrence of the multiple events, and the output unit may output information regarding the DSM.

[0009] The output unit may output, as information relating to the DSM, the DSM generated based on the plurality of events detected by the event detection unit, and a preset reference DSM.

[0010] The output unit may output, as information related to the DSM, a change in the DSM that accompanies repetition of a task.

[0011] The output unit may cause information relating to the DSM to be displayed on a monitor.

[0012] The adjustment unit may group together, among the plurality of nodes, nodes of events related to each other within a specified range of a degree of relatedness into one node.

[0013] The adjustment unit may determine whether a first event represented by a first node, which is an arbitrary node among the multiple nodes, and a second event represented by a second node, which is another arbitrary node, are related within the specified range of relatedness based on at least any of objects involved in the occurrence of the first and second events, times of occurrence of the first and second events, and locations of occurrence of the first and second events.

[0014] The event detection unit may detect the multiple events that have occurred in the work area from the detection results of a ranging sensor or images captured by a camera, for example, using a trained model such as a neural network that has been trained through deep learning.

[0015] In the work status monitoring method according to the present disclosure, a computer detects a plurality of events occurring in a work area, generates an event network consisting of a plurality of nodes representing the detected plurality of events and a plurality of edges representing the occurrence order of the plurality of nodes, adjusts the resolution of the generated event network to a specified resolution, converts the event network with the adjusted resolution into information representing the relationship between the occurrence order of the plurality of events, and outputs the information representing the relationship between the occurrence order of the plurality of events. By adjusting the resolution of information related to the work status such as a DSM presented to a user to a desired resolution, this work status monitoring method can prevent difficulty in identifying noteworthy events such as the occurrence of an abnormality, even when, for example, a plurality of tasks are performed in a work area by a plurality of workers or work robots in a complex manner.

[0016] The work status monitoring program according to the present disclosure causes a computer to execute the following processes: detecting a plurality of events that have occurred in a work area; generating an event network composed of a plurality of nodes representing the detected plurality of events and a plurality of edges representing the order of occurrence of the plurality of nodes; adjusting the resolution of the generated event network to a specified resolution; converting the event network with the adjusted resolution into information representing the relationship between the order of occurrence of the plurality of events; and outputting the information representing the relationship between the order of occurrence of the plurality of events. By adjusting the resolution of information on the work status, such as a DSM, presented to a user to a desired resolution, the work status monitoring program can prevent difficulty in identifying noteworthy events, such as the occurrence of an abnormality, even when, for example, a plurality of tasks are performed in a complex manner by a plurality of workers or work robots in a work area. Effect of the Invention

[0017] The present disclosure makes it possible to provide a work status monitoring system, a work status monitoring method, and a work status monitoring program that are capable of preventing it from becoming difficult to identify noteworthy events. [Brief description of the drawings]

[0018] [Figure 1] 1 is a block diagram showing a configuration example of a work status monitoring system according to a first embodiment. [Diagram 2] 2 is a diagram showing an example of a work area to which the work status monitoring system shown in FIG. 1 is applied. [Diagram 3] 2 is a conceptual diagram showing an example of multidimensional array data, which is a recording format of events detected in the work status monitoring device shown in FIG. 1. [Figure 4] FIG. 13 is a diagram illustrating an example of an event log represented by referring to multidimensional array data. [Diagram 5] 2 is a diagram showing an example of an event network generated in the work status monitoring device shown in FIG. 1. [Figure 6] 2 is a diagram showing an example of adjustment contents of the resolution of the event network adjusted in the work status monitoring device shown in FIG. 1. FIG. [Figure 7] 2 is a diagram showing an example of a DSM (Design Structure Matrix) generated in the work status monitoring device shown in FIG. 1. [Figure 8] FIG. 1 is a diagram for explaining how to view a DSM. [Figure 9] FIG. 1 is a diagram for explaining how to view a DSM. [Figure 10] FIG. 1 is a diagram for explaining how to view a DSM. [Figure 11] FIG. 13 is a diagram showing an example of a DSM accumulated by repeating a task. [Figure 12] 2 is a flowchart showing the operation of the work status monitoring system shown in FIG. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0019] The present invention will be described below through embodiments of the invention, but the invention according to the claims is not limited to the following embodiments. In addition, not all of the configurations described in the embodiments are necessarily essential means for solving the problems. For clarity of explanation, the following description and drawings are omitted and simplified as appropriate. In each drawing, the same elements are given the same reference numerals, and repeated explanations are omitted as necessary.

[0020] <Embodiment 1> FIG. 1 is a block diagram showing an example of the configuration of a work status monitoring system 1 according to a first embodiment. FIG. 2 is a diagram showing an example of a work area to which the work status monitoring system 1 is applied. The work status monitoring system 1 according to this embodiment is a system that monitors the work status of a plurality of works performed in a predetermined work area such as a factory. Here, the work status monitoring system 1 according to this embodiment adjusts the resolution of information related to the work status such as DSM presented to the user to a desired resolution, thereby making it possible to prevent difficulty in identifying noteworthy events such as the occurrence of an abnormality even when, for example, a plurality of works are performed in a work area by a plurality of workers or work robots in a complex manner.

[0021] Specifically, the work status monitoring system 1 is applied to the work area A1, and includes n (n is an integer equal to or greater than 1) sensors 11_1 to 11_n, a work status monitoring device 12, an operation terminal 13, and a network 50. The work status monitoring device 12 can be referred to as a work status monitoring system by itself. The work status monitoring device 12, the sensors 11_1 to 11_n, and the operation terminal 13 are configured to be able to communicate with each other via a wired or wireless network 50. Note that, in this embodiment, an example will be described in which the work status monitoring device 12 and the operation terminal 13 are provided separately, but this is not limiting, and for example, the work status monitoring device 12 may have the function of the operation terminal 13. In other words, the work status monitoring device 12 and the operation terminal 13 may be formed integrally.

[0022] The operation terminal 13 is a communication-capable terminal that is owned by the user or temporarily assigned to the user, and is, for example, a PC (Personal Computer) terminal, a mobile terminal such as a smartphone or a tablet terminal, or a dedicated communication terminal prepared for this system.

[0023] For example, a user such as a manager who monitors the status of work in a work area to which this system is applied operates the operation screen, keyboard, etc. of the operation terminal 13 to input information such as the work content of each work, workers, work robots, mobile objects, equipment such as work benches and parts storage areas, and work objects to the operation terminal 13. The operation terminal 13 accepts this information and transmits it to the work status monitoring device 12 via the network 50. The operation terminal 13 also receives information related to the work status in the work area, such as a DSM (Design Structure Matrix) output from the work status monitoring device 12, via the network 50, and displays it on a monitor, etc.

[0024] The sensors 11_1 to 11_n are installed on the ceiling or the like of the work area A1, and detect workers, work robots, moving objects, equipment, work objects, and the like that exist in the work area A1.

[0025] The mobile body is, for example, a vehicle such as a forklift or a mobile cart for transporting products or parts thereof, or a vehicle (AGV: Automatic Guided Vehicle) set to automatically travel along a predetermined travel route, etc. Furthermore, the work robot is, for example, an autonomously mobile work robot (AMR: Autonomous Mobile Robot) set to automatically perform a predetermined task, etc.

[0026] In the example of Fig. 2, a worker W1, a worker W2, mobile objects M1-M3 which are AGVs, and a work robot RB are present in a work area A1. The mobile objects M1-M3 are used as mobile carts which carry a work target and move along a loop-shaped moving route R1. Note that Fig. 2 shows a detection area A11 of a sensor 11_1 and a detection area A12 of a sensor 11_2 as an example.

[0027] The sensors 11_1 to 11_n are, for example, cameras and are installed so as to be able to capture images of the work area A1. The sensors 11_1 to 11_n are not limited to cameras and may be any type of sensor, such as a distance measuring sensor, that can detect workers, work robots, moving objects, equipment, and work objects in the work area A1.

[0028] The work status monitoring device 12 monitors the work status of a plurality of works performed in the work area A1. Specifically, the work status monitoring device 12 includes an acquisition unit 121, an event detection unit 122, a recording unit 123, a network generation unit 124, an adjustment unit 125, a conversion unit 126, and an output unit 127.

[0029] The acquisition unit 121 acquires information transmitted from the operation terminal 13. Specifically, the acquisition unit 121 acquires information such as the work content of each work, the worker, the work robot, the mobile object, the equipment such as the work bench and the parts storage area, and the work target. The information on the worker may include the proficiency of the worker. Note that, if the work status monitoring device 12 has a function of automatically extracting the information acquired by the acquisition unit 121, the acquisition unit 121 may not be provided.

[0030] The event detection unit 122 detects a plurality of events that have occurred in the work area A1 based on the detection results of the sensors 11_1 to 11_n. Here, an event refers to, for example, a predetermined task performed by any of the workers W1 and W2, the work robot RB, and the mobile bodies M1 to M3. An event includes an object (including the worker, the work robot, and the mobile body) that caused the event to occur, the location where the event occurred, the time when the event occurred, and the work object on which the predetermined task was performed.

[0031] Specifically, the event detection unit 122 periodically extracts objects (workers, work robots, mobile objects, equipment such as workbenches and parts storage areas, and work objects, etc.) in the work area A1, and detects events caused by the objects from the periodically extracted information (e.g., changes in the state of the objects).

[0032] For example, the event detection unit 122 detects, as an event, that the worker W1 (LP) has performed a predetermined process on a work object placed on any of the moving bodies M1 to M3 parked at the position s23 or the position s25. The event detection unit 122 also detects, as an event, that the worker W2 (RP) has performed a predetermined process on a work object placed on any of the moving bodies M1 to M3 parked at the position s14 or the position s12. Alternatively, the event detection unit 122 detects, as an event, that the workers W1 and W2 have cooperated to perform a predetermined process on a work object placed on any of the moving bodies M1 to M3 parked at the position k3.

[0033] The event detection unit 122 may use a trained model to identify each object from the detection results of the sensors 11_1 to 11_n and detect an event. Here, the trained model is a neural network trained using teacher data that is a combination of the detection results of the sensors 11_1 to 11_n and the correct values ​​of the objects included in the detection results. The trained model is preferably a neural network trained by deep learning.

[0034] Alternatively, the event detection unit 122 may refer to the information on each object acquired by the acquisition unit 121, identify each object from the detection results of the sensors 11_1 to 11_n, and detect an event.

[0035] A plurality of events detected by the event detection unit 122 are recorded in the recording unit 123 in the form of multidimensional array data.

[0036] FIG. 3 is a conceptual diagram showing an example of multidimensional array data, which is a recording format of an event detected by the event detection unit 122. Multidimensional array data is also called tensor data. FIG. 3 shows three-dimensional array data as an example of multidimensional array data. Referring to FIG. 3, in three-dimensional array data related to a "person" such as a worker, the first item indicates the "person"'s ID (Identification), the second item indicates the "person"'s proficiency, and the third item indicates the group to which the "person" belongs. In addition, in three-dimensional array data related to an "object," the first item indicates which of multiple moving objects the "object" corresponds to, the second item indicates which of multiple parts the "object" corresponds to, and the third item indicates which of multiple pieces of equipment the "object" corresponds to. In addition, in the three-dimensional array data regarding "area", the first item indicates which of the multiple areas constituting the work area A1 the "area" in which the event occurred corresponds to, the second item indicates the content of the specific event that occurred in the "area" in which the event occurred, and the third item indicates the degree of deviation between the "area" in which the event occurred and the area in which the event occurred under normal circumstances. Furthermore, in the three-dimensional array data regarding "time", the first item indicates the time period in which the event occurred, the second item indicates which takt time the event occurred in, and the third item indicates the time at which the event occurred. These three-dimensional array data are associated with each other. Note that each item of the multidimensional array data can be set arbitrarily. Each event detected by the event detection unit 122 is recorded in the recording unit 123 in the form of multidimensional array data as shown in FIG. 3.

[0037] FIG. 4 is a diagram showing an example of an event log represented with reference to multidimensional array data. Referring to FIG. 4, an event "RP_s14" occurs at 7:03:17 on November 8, 2021. Here, the event "RP_s14" represents that work was performed at position s14 by worker W2. In addition, an event "SV_s14" occurs at 7:03:23 on November 8, 2021. Here, the event "SV_s14" represents that the moving body M1 has moved from position s14 (for example, to position s15). An event "RP_s15" occurs at 7:03:41 on November 8, 2021. Here, the event "RP_s15" represents that work was performed at position s15 by worker W2. In addition, an event "LP_k3" occurs at 7:03:55 on November 8, 2021. Here, the event "LP_k3" represents that work was performed at position k3 by worker W1.

[0038] The network generation unit 124 refers to the multidimensional array data recorded in the recording unit 123 and generates an event network NW composed of a plurality of nodes Nd representing a plurality of events detected by the event detection unit 122 and a plurality of edges Ed representing the occurrence order of the plurality of nodes Nd.

[0039] FIG. 5 is a diagram showing an example of an event network. The lower diagram of FIG. 5 shows an example of an event network NW for a predetermined workflow consisting of multiple work processes in a work area A1. In the lower diagram of FIG. 5, "s" represents the start point of the workflow, and "e" represents the end point of the workflow. In addition, the upper diagram of FIG. 5 shows an enlarged view of a part (area surrounded by a dotted line) of the event network NW shown in the lower diagram of FIG. 5. As shown in FIG. 5, the event network NW is composed of multiple nodes Nd representing multiple events detected by the event detection unit 122, and multiple edges Ed representing the occurrence order of the multiple nodes Nd.

[0040] 5, one of the multiple nodes Nd represents the event "RP_s14" described in FIG. 4, and another represents the event "SV_s14" described in FIG. 4. "(8)" written in the node Nd of the event "RP_s14" represents the number of times the event "RP_s14" has occurred. Similarly, "(2)" written in the node Nd of the event "SV_s14" represents the number of times the event "SV_s14" has occurred. Furthermore, one of the multiple edges Ed extends in an arrow shape from the node Nd of the event "RP_s14" to the node Nd of the event "SV_s14". "2" written in this edge Ed represents the number of times the event "SV_s14" has occurred after the event "RP_s14" has occurred.

[0041] The adjustment unit 125 adjusts the resolution of the event network NW detected by the network generation unit 124 to a resolution designated by a user or the like.

[0042] FIG. 6 is a diagram showing an example of the content of adjustment of the resolution of the event network NW by the adjustment unit 125. As shown in FIG. 6, the higher the resolution, the greater the number of nodes Nd constituting the event network NW, and the lower the resolution, the fewer the number of nodes Nd constituting the event network NW. In other words, the higher the resolution, the greater the amount of information represented by the event network NW, and the lower the resolution, the less the amount of information represented by the event network NW. The greater the amount of information, the more detailed the event can be analyzed, but if the amount of information is too great, it becomes difficult to identify an event that requires attention, such as the occurrence of an abnormality. Therefore, the adjustment unit 125 makes it possible to adjust the resolution of the event network NW detected by the network generation unit 124 to a resolution specified by a user or the like.

[0043] Here, when the resolution is reduced, the adjustment unit 125 groups together, among the multiple nodes Nd, nodes of events related within a range of a specified degree of relatedness into one node. For example, the adjustment unit 125 determines whether an event (first event) represented by a first node, which is any of the multiple nodes Nd, and an event (second event) represented by a second node, which is any of the other nodes, are related within a range of a degree of relatedness specified by a user or the like, based on at least any of the objects involved in the occurrence of the first and second events, the occurrence times of the first and second events, and the occurrence locations of the first and second events. For example, if the same worker is involved in the occurrence of the first and second events, the occurrence times of the first and second events are close, and the occurrence locations of the first and second events are close, the adjustment unit 125 groups the first and second nodes into one node.

[0044] The conversion unit 126 converts the event network NW adjusted to a desired resolution by the adjustment unit 125 into information that indicates the relationship between the occurrence order of a plurality of events, specifically, a DSM.

[0045] FIG. 7 is a diagram showing an example of a DSM. In the example of the DSM shown in FIG. 7, a plurality of events represented by a plurality of nodes constituting the event network NW are represented as Element001 to Element015. In addition, in the example of the DSM shown in FIG. 7, an event in a column where a "1" is written in the matrix represents an earlier event, and an event in the same row represents a later event. For example, a "1" is written at the intersection of Element002 in the second column and Element001 in the first row, which represents that the event Element001 occurred after the occurrence of the event Element002. In other words, the "1" in the matrix of the DSM corresponds to an edge Ed in the event network NW.

[0046] Next, a way of viewing the DSM will be explained with reference to Figures 8 to 10. Figure 8 shows a simplified view of part of the work area shown in Figure 2.

[0047] In the example of Fig. 8, three moving bodies M1 to M3 used as moving carts move along a loop-shaped moving route R1. Each of the moving bodies M1 to M3 carries a work object to be processed by a work robot RB and workers W1 and W2.

[0048] In the example of FIG. 8, the contents of the multiple tasks that make up the workflow are as follows: Task 1: Workers W1 and W2 process the work object on the moving object M2 at location A23. Task 2: Mobile unit M1 stops at location A22 Task 3: Worker W2 moves to location A22 Task 4: Worker W2 removes part P1 from the work object on moving body M1 at location A22. Task 5: Mobile unit M3 stops at location A21 Task 6: Worker W1 moves to location A21 Task 7: Worker W1 attaches part P2 to the work object on moving body M3 at location A21.

[0049] Fig. 9 shows the workflow of tasks 1 to 7 under normal circumstances, and a DSM generated based on the workflow. Specifically, in the example of Fig. 9, task 1 is executed first, followed by tasks 2 and 5. After task 2 is executed, tasks 3 and 4 are executed in that order. Furthermore, after task 5 is executed, tasks 6 and 7 are executed in that order. No rework has occurred in the DSM at this time.

[0050] FIG. 10 shows a workflow of tasks 1 to 7 that is different from normal, and a DSM generated based on the workflow. Specifically, in the example of FIG. 10, task 2 is executed first, and then tasks 3 and 4 are executed in order. Then, task 1 is executed. After task 1 is executed, tasks 5, 6, and 7 are executed in order. That is, in the example of FIG. 10, since the arrival of worker W1 at location A23 is delayed and it is difficult to execute task 1, tasks 2, 3, and 4 are executed before task 1 is executed. In the DSM at this time, rework has occurred. For example, this rework is acceptable when worker W2 has a high level of proficiency, but is undesirable when worker W2 has a low level of proficiency. For example, a user or the like can investigate the impact of undesirable rework on other tasks from the DSM, or investigate the cause of undesirable rework.

[0051] 11 is a diagram showing an example of a DSM accumulated by repeating a task. The vertical axis represents the amount of "1" (edge ​​Ed in the event network NW) accumulated in the matrix of the DSM.

[0052] The output unit 127 outputs information about the DSM generated by the conversion unit 126, for example, as shown in Fig. 11. The information output by the output unit 127 is transferred to the operation terminal 13, for example, via the network 50, and displayed on the monitor of the operation terminal 13. This enables the user or the like to analyze an event that has occurred as a result of work in the work area A1.

[0053] For example, the output unit 127 may output, as information related to the DSM, a DSM generated based on an actual operation (i.e., a DSM generated based on a plurality of events detected by the event detection unit 122) and a preset reference DSM. This allows a user or the like to compare the DSM generated based on the actual operation with the preset reference DSM and perform an analysis, for example, regarding whether an abnormality has occurred or a delay has occurred in the operation in a portion where there is a large difference.

[0054] Alternatively, the output unit 127 may output a change in the DSM (information accumulation tendency) accompanying the repetition of the work as information regarding the DSM. This allows the user or the like to analyze whether the machine has broken down or the worker has become fatigued, etc., from the change in the work situation accompanying the repetition of the work.

[0055] In this way, the work status monitoring system 1 according to the present embodiment can adjust the resolution of information related to the work status, such as DSM, presented to the user to a desired resolution, thereby preventing difficulty in identifying noteworthy events, such as the occurrence of an abnormality, even in cases where, for example, multiple tasks are being performed in a complex manner by multiple workers or work robots in a work area.

[0056] (Operation of work status monitoring system 1) Next, the operation of the work status monitoring system 1 will be described with reference to Fig. 12. Fig. 12 is a flowchart showing the operation of the work status monitoring system 1.

[0057] In the work status monitoring system 1, the work status monitoring device 12 first acquires information on the work content of each work, workers, work robots, moving objects, equipment such as work benches and parts storage areas, and work objects transmitted from the operation terminal 13 (step S101). Note that the work status monitoring device 12 may acquire this information via the operation terminal 13, or may have a function of automatically extracting this information from the detection results of the sensors 11_1 to 11_n.

[0058] Thereafter, the work status monitoring device 12 detects a plurality of events that have occurred in the work area A1 based on the detection results of the sensors 11_1 to 11_n (step S102).

[0059] Thereafter, the work status monitoring device 12 generates an event network NW that is composed of a plurality of nodes Nd that represent the plurality of detected events and a plurality of edges Ed that represent the occurrence order of the plurality of nodes Nd (step S103).

[0060] Thereafter, the work status monitoring device 12 adjusts the resolution of the event network NW to a resolution designated by a user or the like (step S104).

[0061] Thereafter, the work status monitoring device 12 converts the event network NW adjusted to the desired resolution into a DSM (step S105).

[0062] Thereafter, the work status monitoring device 12 outputs information related to the DSM (step S106). The information related to the DSM output from the work status monitoring device 12 is transferred to the operation terminal 13 via the network 50, for example, and displayed on the monitor of the operation terminal 13.

[0063] As described above, the work status monitoring system 1 according to the present embodiment adjusts the resolution of information related to the work status, such as DSM, presented to the user to a desired resolution, thereby making it possible to prevent difficulty in identifying noteworthy events, such as the occurrence of an abnormality, even in cases where, for example, multiple tasks are being performed in a complex manner by multiple workers or work robots in a work area.

[0064] The present invention is not limited to the above-described embodiment, and can be modified as appropriate without departing from the spirit and scope of the present invention.

[0065] In addition, the present disclosure can be realized by causing a CPU (Central Processing Unit) to execute a computer program, partly or entirely, of the processing of the work status monitoring device 12.

[0066] The above-mentioned program includes a set of instructions (or software code) for making the computer perform one or more functions described in the embodiment when the program is loaded into the computer. The program may be stored in a non-transitory computer-readable medium or a tangible storage medium. By way of example and not limitation, the computer-readable medium or tangible storage medium includes a random-access memory (RAM), a read-only memory (ROM), a flash memory, a solid-state drive (SSD) or other memory technology, a CD-ROM, a digital versatile disc (DVD), a Blu-ray (registered trademark) disk or other optical disk storage, a magnetic cassette, a magnetic tape, a magnetic disk storage or other magnetic storage device. The program may be transmitted on a transitory computer-readable medium or a communication medium. By way of example and not limitation, the transitory computer-readable medium or the communication medium includes an electrical, optical, acoustic, or other form of propagating signal. [Explanation of symbols]

[0067] 1. Work status monitoring system 11_1~11_n Sensor 12 Work status monitoring device 13 Operation terminal 50 Network 121 Acquisition Department 122 Event detection unit 123 Recording Department 124 Network Generation Unit 125 Adjustment section 126 Conversion Unit 127 Output section A1 Work Area A11, A12 detection area M1~M3 Mobile object Nd Node Ed Edge P1, P2 parts RB Work Robot W1, W2 workers

Claims

1. an event detection unit that detects a plurality of events occurring in a working area; a network generation unit that generates an event network including a plurality of nodes that represent the plurality of events detected by the event detection unit and a plurality of edges that represent an occurrence order of the plurality of nodes; an adjustment unit that adjusts a resolution of the event network generated by the network generation unit to a specified resolution; a conversion unit that converts the event network, the resolution of which has been adjusted by the adjustment unit, into information that represents a relationship between the order of occurrence of a plurality of events; an output unit that outputs a result of the conversion by the conversion unit; A work status monitoring system equipped with

2. The conversion unit converts the event network, the resolution of which has been adjusted by the adjustment unit, into a Design Structure Matrix (DSM), which is information representing a relationship between the order of occurrence of the plurality of events; The output unit outputs information related to the DSM. The work status monitoring system according to claim 1 .

3. The output unit outputs, as information related to the DSM, the DSM generated based on the plurality of events detected by the event detection unit and a preset reference DSM. The work status monitoring system according to claim 2 .

4. The output unit outputs a change in the DSM accompanying repetition of the work as information regarding the DSM. The work status monitoring system according to claim 2 .

5. The output unit displays information about the DSM on a monitor. The work status monitoring system according to claim 2 .

6. The adjustment unit aggregates, among the plurality of nodes, event nodes related within a specified range of relevance into one node. The work status monitoring system according to claim 1 .

7. the adjustment unit determines whether a first event represented by a first node, which is an arbitrary node among the plurality of nodes, and a second event represented by a second node, which is another arbitrary node, are related within the specified range of relatedness based on at least any of objects involved in occurrence of the first and second events, occurrence times of the first and second events, and occurrence locations of the first and second events; The work status monitoring system according to claim 6.

8. the event detection unit detects the plurality of events occurring in the work area using at least one of a distance measuring sensor and a camera; The work status monitoring system according to claim 1 .

9. The computer Detecting a plurality of events occurring in the working area; generating an event network including a plurality of nodes representing the plurality of detected events and a plurality of edges representing an occurrence order of the plurality of nodes; Adjusting the resolution of the generated event network to a specified resolution; Converting the event network with adjusted resolution into information representing a relationship between the occurrence order of a plurality of events; outputting information indicating a relationship between the order of occurrence of the plurality of events; How to monitor work status.

10. Detecting a plurality of events occurring in a working area; A process of generating an event network including a plurality of nodes representing the plurality of detected events and a plurality of edges representing an occurrence order of the plurality of nodes; A process of adjusting a resolution of the generated event network to a specified resolution; A process of converting the event network with adjusted resolution into information representing a relationship between the occurrence order of a plurality of events; outputting information indicating a relationship between the order of occurrence of the plurality of events; A work status monitoring program that causes a computer to execute the above.

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