Work condition monitoring system, work condition monitoring method, and storage medium

Abstract

The present disclosure provides a work condition monitoring system, a work condition monitoring method, and a storage medium. The work condition monitoring system includes: an event detection unit that detects a plurality of events that occur in a work area; a network generation unit that generates an event network composed of a plurality of nodes and a plurality of edges, the plurality of nodes representing the plurality of events detected by the event detection unit, and the plurality of edges representing the occurrence order 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 is adjusted by the adjustment unit into information representing the relationship of the occurrence order of the plurality of events; and an output unit that outputs the conversion result of the conversion unit.

Description

Technical Field

[0001] This disclosure relates to a work condition monitoring system, a work condition monitoring method, and a work condition monitoring procedure. Background Technology

[0002] In recent years, there has been a demand for technologies that efficiently monitor the status of multiple tasks within a work area. Related technologies have been disclosed, for example, in Japanese Patent Application Publication No. 2020-184250.

[0003] Japanese Patent Application Publication No. 2020-184250 discloses a work analysis apparatus for analyzing work involving multiple processes. This work analysis apparatus 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 judgment unit that judges the process being performed by the worker based on the worker's position and orientation; and a generation unit that measures the working time for each process and generates a timing diagram representing the process performed by the worker. Summary of the Invention

[0004] However, the work analysis device disclosed in Japanese Patent Application Publication No. 2020-184250 has the following problem: in cases such as when multiple workers perform a work with many procedures, the amount of information shown in the timing diagram increases, making it difficult to identify events that should be of concern, such as the occurrence of anomalies.

[0005] This disclosure was made in view of the above background, and its purpose is to provide a work condition monitoring system, work condition monitoring method, and work condition monitoring procedure that can prevent situations where it is difficult to identify events that should be of concern.

[0006] The work status monitoring system disclosed herein includes: an event detection unit that detects multiple events occurring in a work area; a network generation unit that generates an event network consisting of multiple nodes and multiple edges, wherein the multiple nodes represent the multiple events detected by the event detection unit, and the multiple edges represent the order in which the multiple nodes occur; 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 in which the multiple events occur; and an output unit that outputs the conversion result of the conversion unit. This work status monitoring system, by adjusting the resolution of work status-related information such as the design structure matrix displayed to the user to a desired resolution, prevents situations where it is difficult to determine the occurrence of events that should be of concern, such as anomalies, even in cases where multiple tasks are complexly performed in the work area due to multiple workers or robots.

[0007] Alternatively, the conversion unit can convert the event network, whose resolution has been adjusted by the adjustment unit, into information representing the relationship between the occurrence order of the multiple events, i.e., a design structure matrix, and the output unit can output information related to the design structure matrix.

[0008] Alternatively, the output section may output, as information related to the design structure matrix, the design structure matrix generated based on the plurality of events detected by the event detection unit and a pre-set reference design structure matrix.

[0009] Alternatively, the output unit can output the changes in the design structure matrix as the work is repeated, as information related to the design structure matrix.

[0010] Alternatively, the output unit can display information related to the design structure matrix on a monitor.

[0011] Alternatively, the adjustment unit may aggregate the nodes of events that are associated within a specified degree of association among the plurality of nodes into a single node.

[0012] Alternatively, the adjustment unit may determine whether the first event shown by the first node (which is an arbitrary node) and the second event shown by the second node (which is another arbitrary node) are associated within the specified degree of association, based on at least one of the following: the object related to the occurrence of the first event and the second event, the time of occurrence of the first event and the second event, and the location of occurrence of the first event and the second event.

[0013] Alternatively, the event detection unit may use a learned model, such as a neural network learned through deep learning, to detect the multiple events occurring in the working area based on the detection results of the ranging sensor or the images captured by the camera.

[0014] In the work status monitoring method disclosed herein, a computer detects multiple events occurring in a work area, generates an event network consisting of multiple nodes representing the detected events and multiple edges representing the order of occurrence of the nodes, adjusts the resolution of the generated event network to a specified resolution, converts the resolution-adjusted event network into information representing the relationship between the order of occurrence of the multiple events, and outputs the information representing the relationship between the order of occurrence of the multiple events. This work status monitoring method, by adjusting the resolution of work status-related information such as the design structure matrix displayed to the user to a desired resolution, prevents situations where it is difficult to determine the occurrence of events that should be of concern, such as anomalies, even in cases where multiple tasks are complexly performed in the work area due to multiple workers or robots.

[0015] The work status monitoring program disclosed herein causes a computer to perform the following processes: detecting multiple events occurring in a work area; generating an event network consisting of multiple nodes representing the detected events and multiple edges representing the order of occurrence of the nodes; adjusting the resolution of the generated event network to a specified resolution; converting the resolution-adjusted event network into information representing the relationship between the order of occurrence of the multiple events; and outputting the information representing the relationship between the order of occurrence of the multiple events. This work status monitoring program, by adjusting the resolution of work status-related information such as the design structure matrix displayed to the user to a desired resolution, prevents situations where it is difficult to determine the occurrence of events that should be of concern, such as anomalies, even in cases where multiple tasks are complexly performed in the work area due to multiple workers or robots.

[0016] According to this disclosure, a work condition monitoring system, a work condition monitoring method, and a work condition monitoring procedure can be provided to prevent situations where it is difficult to identify events that should be of concern.

[0017] The above and other objects, features and advantages of this disclosure will become more fully understood from the detailed description and accompanying drawings given below, which are given by way of illustration only and should not be considered as limiting the disclosure. Attached Figure Description

[0018] Figure 1 This is a block diagram illustrating a structural example of the working condition monitoring system according to Embodiment 1.

[0019] Figure 2 To indicate that it has been applied Figure 1 A diagram showing an example of the working area of ​​a work status monitoring system.

[0020] Figure 3 To indicate in Figure 1 The diagram shows an example of a multidimensional arrangement of data, representing the recording format of events detected by the operational status monitoring device.

[0021] Figure 4 A diagram representing an example of a log of events represented by reference to multidimensionally arranged data.

[0022] Figure 5 To indicate in Figure 1 A diagram illustrating an example of an event network generated in a working condition monitoring device.

[0023] Figure 6 To indicate in Figure 1 This diagram shows an example of the adjustment content of the resolution of the event network in the operational status monitoring device.

[0024] Figure 7 To indicate in Figure 1 A diagram showing an example of a DSM (Design Structure Matrix) generated in a working condition monitoring device.

[0025] Figure 8 This is a diagram illustrating how to view the DSM.

[0026] Figure 9 This is a diagram illustrating how to view the DSM.

[0027] Figure 10 This diagram illustrates how to view the DSM.

[0028] Figure 11 A diagram illustrating an example of a DSM accumulated through repeated work.

[0029] Figure 12 To indicate Figure 1 The flowchart shown illustrates the operation of the work status monitoring system. Detailed Implementation

[0030] The present invention will now be described by way of embodiments, but the invention is not limited to these embodiments. Furthermore, the structures described in the embodiments are not necessarily all necessary means of solving the problem. For clarity, the following descriptions and drawings have been appropriately omitted and simplified. In the various drawings, the same elements are labeled with the same symbols, and repeated descriptions have been omitted as necessary.

[0031] <Implementation Method 1>

[0032] Figure 1 This is a block diagram illustrating a structural example of the operational status monitoring system 1 according to Embodiment 1. Furthermore, Figure 2 This diagram illustrates an example of a work area where the work condition monitoring system 1 is applied. The work condition monitoring system 1 of this embodiment is a system for monitoring the work conditions of multiple tasks performed in a predetermined work area, such as a factory. Here, the work condition monitoring system 1 of this embodiment adjusts the resolution of work condition-related information, such as the DSM (Discretionary Management System), displayed to the user to a desired resolution, thereby preventing situations where it is difficult to determine the occurrence of events that should be of concern, such as anomalies, even in cases where multiple tasks are complexly performed by multiple workers or robots in the work area.

[0033] Specifically, the work status monitoring system 1 is applied in the work area A1 and includes n (n is an integer greater than or equal to 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 also be referred to as the work status monitoring system alone. The work status monitoring device 12, the sensors 11_1 to 11_n, and the operation terminal 13 are configured to communicate with each other via a wired or wireless network 50. In this embodiment, the work status monitoring device 12 and the operation terminal 13 are described as separate, but this is not the only possibility. For example, the work status monitoring device 12 may also have the functions of the operation terminal 13. That is, the work status monitoring device 12 and the operation terminal 13 may also be integrated into one unit.

[0034] The operating terminal 13 is a communication terminal owned by the user or temporarily assigned to the user, such as a portable terminal such as a PC (Personal Computer), a smartphone or tablet computer, or a dedicated communication terminal prepared for this system.

[0035] For example, managers and other users who monitor the work status in the work area using this system can input information such as work content, workers, robots, moving parts, workbenches or parts placement locations, and work objects into the operation terminal 13 by operating the operation screen or keyboard. The operation terminal 13 receives this information and sends it to the work status monitoring device 12 via the network 50. In addition, the operation terminal 13 receives information related to the work status in the work area, such as the DSM (Design Structure Matrix), output from the work status monitoring device 12 via the network 50 and displays it on a monitor.

[0036] Sensors 11_1 to 11_n are installed in the ceiling or other locations of the work area A1 to detect workers, robots, moving objects, equipment, and work objects present in the work area A1.

[0037] Mobile bodies include, for example, vehicles such as forklifts or mobile trolleys used to transport products or their parts, or vehicles programmed to move automatically along a pre-defined path (AGV; Automatic Guided Vehicle). Additionally, work robots include, for example, autonomous mobile robots (AMR; Autonomous Mobile Robot) programmed to automatically perform predetermined tasks.

[0038] exist Figure 2 In the example, within the work area A1, there are worker W1, worker W2, mobile bodies M1-M3 (AGVs), and a work robot RB. Mobile bodies M1-M3 are used as mobile trolleys that load work objects and move along a circular path R1. Additionally, in... Figure 2 As an example, the detection area A11 of sensor 11_1 and the detection area A12 of sensor 11_2 are shown.

[0039] Sensors 11_1 to 11_n are, for example, cameras, and are configured to capture images of the work area A1. However, sensors 11_1 to 11_n are not limited to cameras; they can also be any type of sensor capable of detecting workers, robots, moving objects, equipment, and work objects in the work area A1, such as range sensors.

[0040] The work status monitoring device 12 monitors the work status of multiple tasks 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.

[0041] The acquisition unit 121 acquires information sent from the operation terminal 13. Specifically, the acquisition unit 121 acquires information such as the work content of each job, the workers, the work robot, the moving body, the equipment such as the workbench or parts placement location, and the work object. The information of the workers may include the worker's skill level, etc. Alternatively, if the work status monitoring device 12 has the function of automatically extracting the information acquired by the acquisition unit 121, the acquisition unit 121 may not be required.

[0042] The event detection unit 122 detects multiple events occurring in the work area A1 based on the detection results of sensors 11_1 to 11_n. Here, an event refers to, for example, a predetermined task performed by any one of the workers W1 and W2, the work robot RB, and the mobile bodies M1 to M3. An event includes the object that caused the event (including workers, work robots, and mobile bodies), the location of the event, the time of the event, and the work object performing the predetermined task.

[0043] Specifically, the event detection unit 122 periodically extracts objects (workers, work robots, moving bodies, equipment such as workbenches or parts placement areas, and work objects, etc.) in the work area A1, and detects events caused by the objects based on the periodically extracted information (such as changes in the objects).

[0044] For example, the event detection unit 122 detects an event when worker W1 (LP) performs a predetermined processing on a work object placed on any one of the moving bodies M1 to M3 parked at positions s23 and s25. Furthermore, the event detection unit 122 detects an event when worker W2 (RP) performs a predetermined processing on a work object placed on any one of the moving bodies M1 to M3 parked at positions s14 and s12. Alternatively, the event detection unit 122 detects an event when workers W1 and W2 cooperate to perform a predetermined processing on a work object placed on any one of the moving bodies M1 to M3 parked at position k3.

[0045] Alternatively, the event detection unit 122 can also use a learned model to determine each object and detect events based on the detection results of sensors 11_1 to 11_n. Here, the learned model is a neural network that learns from the combination of the detection results of sensors 11_1 to 11_n and the positive value of the objects included in those detection results, i.e., teacher data. Preferably, the learned model is a neural network that has been learned through deep learning.

[0046] Alternatively, the event detection unit 122 may refer to the information related to each object obtained by the acquisition unit 121 and determine each object based on the detection results of the sensors 11_1 to 11_n, and detect the event.

[0047] Multiple events detected by the event detection unit 122 are recorded in the recording unit 123 in the form of multidimensional data.

[0048] Figure 3 This is a schematic diagram illustrating an example of multidimensional permutation data in the form of records of events detected by the event detection unit 122. Multidimensional permutation data is also called tensor data. Figure 3 The image shows a three-dimensional permutation as an example of multidimensional permutation data. (See reference...) Figure 3 In the three-dimensional arrangement data related to "people" such as staff, the first item represents the "person's" ID (Identification), the second item represents the "person's" proficiency, and the third item represents the group to which the "person" belongs. Furthermore, in the three-dimensional arrangement data related to "objects," the first item represents which of several moving bodies the "object" belongs to, the second item represents which of several parts the "object" belongs to, and the third item represents which of several pieces of equipment the "object" belongs to. Additionally, in the three-dimensional arrangement data related to "areas," the first item represents which of the several areas constituting work area A1 the "area" where the event occurred belongs, the second item represents the specific content of the event that occurred in the "area" where the event occurred, and the third item represents the degree of deviation between the "area" where the event occurred and the usual event occurrence area. Moreover, in the three-dimensional arrangement data related to "time," the first item represents the time period of the event, the second item represents the tact time of the event, and the third item represents the moment the event occurred. These three-dimensional arrangement data are interconnected. Furthermore, the individual items of the multi-dimensional arrangement data can be arbitrarily set. Each event detected by the event detection unit 122 is as follows Figure 3 The multidimensional arrangement of data shown is recorded in the recording section 123.

[0049] Figure 4A diagram illustrating an example of a log of events presented by referencing multidimensionally arranged data. (Referencing) Figure 4 At 7:03:17 on November 8, 2021, event "RP_s14" occurred. Event "RP_s14" indicates that worker W2 performed work at position s14. Furthermore, at 7:03:23 on November 8, 2021, event "SV_s14" occurred. Event "SV_s14" indicates that moving body M1 moved from position s14 (to, for example, position s15). At 7:03:41 on November 8, 2021, event "RP_s15" occurred. Event "RP_s15" indicates that worker W2 performed work at position s15. Moreover, at 7:03:55 on November 8, 2021, event "LP_k3" occurred. Event "LP_k3" indicates that worker W1 performed work at position k3.

[0050] The network generation unit 124 refers to the multidimensional arrangement data recorded in the recording unit 123 to generate an event network NW consisting 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.

[0051] Figure 5 This is a diagram illustrating an example of an event network. Figure 5 The diagram below shows an example of an event network NW associated with a predetermined workflow consisting of multiple work steps in work area A1. Figure 5 In the diagram below, "s" represents the start point of the workflow, and "e" represents the end point. Furthermore, in... Figure 5 The image above is enlarged to show... Figure 5 The following diagram shows a portion of the event network NW (the area enclosed by the dashed line). Figure 5 As shown, the event network NW consists 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.

[0052] Reference Figure 5 One of multiple nodes Nd is represented in Figure 4 The event "RP_s14" described in the text, another one indicates in Figure 4The event “SV_s14” is described in the diagram. The “(8)” marked on the node Nd of event “RP_s14” indicates the number of times event “RP_s14” occurs. Similarly, the “(2)” marked on the node Nd of event “SV_s14” indicates the number of times event “SV_s14” occurs. In addition, one of the multiple edges Ed extends from the node Nd of event “RP_s14” to the node Nd of event “SV_s14” in an arrow-like line. The “2” marked on this edge Ed indicates the number of times event “SV_s14” occurred after event “RP_s14” occurred.

[0053] The adjustment unit 125 adjusts the resolution of the event network NW detected by the network generation unit 124 to the resolution specified by the user, etc.

[0054] Figure 6 This diagram illustrates an example of the resolution adjustment content of the event network NW implemented by the adjustment unit 125. (See diagram below.) Figure 6 As shown, the higher the resolution, the more nodes Nd constitute the event network NW; the lower the resolution, the fewer nodes Nd constitute the event network NW. In other words, the higher the resolution, the more information is represented by the event network NW; the lower the resolution, the less information is represented by the event network NW. While more information allows for more detailed event analysis, excessive information makes it difficult to identify events of interest, such as anomalies. Therefore, the adjustment unit 125 can adjust the resolution of the event network NW detected by the network generation unit 124 to a resolution specified by the user.

[0055] Here, the adjustment unit 125, while reducing resolution, aggregates nodes of events associated within a specified degree of association among multiple nodes Nd into a single node. For example, the adjustment unit 125 determines whether an event (first event) shown as a first node (any one of the multiple nodes Nd) and an event (second event) shown as a second node (any other node) are associated within a degree of association specified by the user, based on at least one of the following: the object related to the occurrence of the first event and the second event, the time of occurrence of the first event and the second event, and the location of occurrence of the first event and the second event. For example, if the personnel related to the occurrence of the first event and the second event are the same, the times of occurrence of the first event and the second event are similar, and the locations of occurrence of the first event and the second event are similar, the adjustment unit 125 aggregates the first node and the second node into a single node.

[0056] The conversion unit 126 converts the event network NW, which has been adjusted to the desired resolution by the adjustment unit 125, into information representing the relationship between the occurrence order of multiple events, specifically into a DSM.

[0057] Figure 7 A diagram illustrating an example of a DSM. Figure 7 In the example of the DSM shown, multiple events represented by multiple nodes constituting the event network NW are represented as Element001 to Element015. Furthermore, in... Figure 7 In the example of the DSM shown, the events in the column marked with "1" in the matrix represent the earlier events, and the events in the row at the same position represent the later events. For example, a "1" is marked at the intersection of Element002 in the second column and Element001 in the first row, indicating that event Element001 occurred after event Element002. That is, a "1" in the DSM matrix is ​​equivalent to an edge Ed in the event network NW.

[0058] Next, use Figures 8-10 These are diagrams used to illustrate how to view the DSM. Figure 8 middle, Figure 2 A portion of the work area shown is represented in a simplified manner.

[0059] exist Figure 8 In the example, three mobile bodies M1 to M3, used as mobile trolleys, move along a circular movement path R1. On each mobile body M1 to M3, there is a work object to be processed by the work robot RB and workers W1 and W2.

[0060] Here, in Figure 8 In the example, the contents of the multiple tasks that make up the workflow are as follows.

[0061] Task 1: Workers W1 and W2 process the work object on the moving body M2 at location A23.

[0062] Task 2: Move vehicle M1 to parking location A22.

[0063] Task 3: Staff member W2 moves to location A22

[0064] Task 4: Worker W2 removes part P1 from the work object on the moving body M1 at location A22.

[0065] Task 5: Mobile vehicle M3 stops at location A21.

[0066] Task 6: Staff member W1 moves to location A21

[0067] Task 7: Worker W1 installs part P2 onto the work object on the moving body M3 at location A21.

[0068] exist Figure 9 The diagram illustrates the workflow of tasks 1 through 7 under normal conditions, and the DSM generated based on this workflow. Specifically, in Figure 9 In the example, first, after implementing task 1, tasks 2 and 5 are implemented. After implementing task 2, tasks 3 and 4 are implemented in sequence. Furthermore, after implementing task 5, tasks 6 and 7 are implemented in sequence. No rework occurs in the DSM at this point.

[0069] exist Figure 10 The diagram illustrates the workflow for tasks 1 through 7, which differs from the usual process, and the DSM generated based on this workflow. Specifically, in Figure 10 In the example, first, after implementing task 2, tasks 3 and 4 are implemented sequentially. Then, task 1 is implemented. After implementing task 1, tasks 5, 6, and 7 are implemented sequentially. That is to say, in Figure 10 In the example, because worker W1 arrived at location A23 late, it was difficult to perform task 1. Therefore, tasks 2, 3, and 4 were performed before task 1. In this case, rework occurred according to the DSM. For example, this rework would be permissible if worker W2 had a higher skill level, but not preferred if worker W2 had a lower skill level. Users, for example, can investigate the impact of this undesirable rework on other tasks, or investigate the reasons for its occurrence, based on the DSM.

[0070] Figure 11 This is a diagram illustrating an example of a DSM that accumulates through repeated work. The height axis represents the amount of "1" (edge ​​Ed in the event network NW) accumulated in the matrix of the DSM.

[0071] Output unit 127 outputs, for example, the output generated by conversion unit 126. Figure 11 The information related to the DSM is shown. The information output by the output unit 127 is transmitted to the operation terminal 13 via the network 50, for example, and is displayed on the monitor of the operation terminal 13. As a result, users can analyze events that occur due to work in the work area A1.

[0072] For example, as information related to the DSM, the output unit 127 can also output a DSM generated based on actual work (i.e., a DSM generated based on multiple events detected by the event detection unit 122) and a DSM based on a preset benchmark. Thus, users can compare the DSM generated based on actual work with the DSM based on the preset benchmark, and for example, analyze whether an anomaly or work delay has occurred for locations with large differences.

[0073] Alternatively, as information related to the DSM, the output unit 127 can also output the changes in the DSM that occur with repeated work (the accumulation trend of information). Thus, users can analyze whether the machine is malfunctioning or whether the worker is fatigued based on the changes in the work situation that occur with repeated work.

[0074] In this way, the work status monitoring system 1 according to this embodiment can prevent situations where it is difficult to determine the occurrence of events that should be of concern, such as abnormalities, even in cases where multiple tasks are complicated to be performed in the work area due to multiple workers or work robots, by adjusting the resolution of work status-related information such as DSM that is prompted to the user to the desired resolution.

[0075] (Operation of Operational Status Monitoring System 1)

[0076] Next, use Figure 12 The operation of the working status monitoring system 1 is explained. Figure 12 A flowchart illustrating the actions of the operational status monitoring system 1.

[0077] In the work status monitoring system 1, the work status monitoring device 12 first obtains information from the operation terminal 13 regarding the work content, personnel, work robots, moving bodies, equipment such as workbenches or parts placement locations, and work objects (step S101). Furthermore, the work status monitoring device 12 can obtain this information either through the operation terminal 13 or automatically extract it from the detection results of sensors 11_1 to 11_n.

[0078] Then, the work status monitoring device 12 detects multiple events occurring in the work area A1 based on the detection results detected by the sensors 11_1 to 11_n (step S102).

[0079] Then, the working condition monitoring device 12 generates an event network NW consisting of multiple nodes Nd representing multiple detected events and multiple edges Ed representing the occurrence order of the multiple nodes Nd (step S103).

[0080] Then, the working status monitoring device 12 adjusts the resolution of the event network NW to the resolution specified by the user, etc. (step S104).

[0081] Then, the operational status monitoring device 12 converts the event network NW, adjusted to the desired resolution, into a DSM (step S105).

[0082] Then, the work status monitoring device 12 outputs information related to the DSM (step S106). The DSM-related information output from the work status monitoring device 12 is transmitted to the operation terminal 13 via the network 50, for example, and is displayed on the monitor of the operation terminal 13.

[0083] As described above, the work status monitoring system 1 according to this embodiment adjusts the resolution of work status-related information such as DSM that is prompted to the user to the desired resolution, thereby preventing situations where it is difficult to determine the occurrence of events that should be of concern, such as abnormalities, even in cases where multiple tasks are complicated to be performed in the work area due to multiple workers or work robots.

[0084] This invention is not limited to the above-described embodiments, and appropriate modifications can be made without departing from the spirit of the invention.

[0085] Furthermore, this disclosure enables the operation status monitoring device 12 to perform part or all of its processing by having the CPU (Central Processing Unit) execute a computer program.

[0086] When the above-described program is read by a computer, it includes a set of commands (or software code) for causing the computer to perform one or more functions described in the embodiments. The program may also be stored on a non-transitory computer-readable medium or a tangible storage medium. As a non-limiting example, a computer-readable medium or tangible storage medium includes: RAM (Random-Access Memory), ROM (Read-Only Memory), flash memory, SSD (Solid-State Drive) or other memory technologies, CD-ROM (Read-Only Optical Disc), DVD (Digital Versatile Disc), Blu-ray disc or other optical disc storage, magnetic tape, magnetic tape, disk storage, or other magnetic storage devices. The program may also be transmitted on a temporary computer-readable medium or a communication medium. As a non-limiting example, a temporary computer-readable medium or communication medium includes electrical, optical, acoustic, or other forms of transmission signals.

[0087] Based on the disclosure described herein, it will be apparent that embodiments of this disclosure can be varied in many ways. Such variations should not be considered as departing from the spirit and scope of this disclosure, and all such modifications, which will be apparent to those skilled in the art, are included within the scope of this invention.

Claims

1. A working status monitoring system, comprising: The Incident Detection Department detects multiple incidents occurring in the work area; A network generation unit generates an event network consisting of multiple nodes and multiple edges, wherein the multiple nodes represent the multiple events detected by the event detection unit, and the multiple edges represent the order in which the multiple nodes occur; The adjustment unit adjusts the resolution of the event network generated by the network generation unit to a resolution specified by the user. The conversion unit converts the event network, whose resolution has been adjusted by the adjustment unit, into information representing the relationship between the occurrence order of multiple events, i.e., a design structure matrix. The output section outputs information related to the design structure matrix. The resolution refers to the number of nodes that make up the event network. The higher the resolution, the more nodes there are; the lower the resolution, the fewer nodes there are. The adjustment unit, while reducing the resolution, aggregates the nodes of events that are associated within a specified degree of association among the plurality of nodes into a single node.

2. The working status monitoring system as described in claim 1, wherein, The output section outputs the design structure matrix generated based on the plurality of events detected by the event detection unit and the design structure matrix of a pre-set benchmark, respectively, as information related to the design structure matrix.

3. The working status monitoring system as described in claim 1, wherein, The output unit outputs the changes in the design structure matrix as the work is repeated, as information related to the design structure matrix.

4. The working status monitoring system as described in claim 1, wherein, The output unit displays information related to the design structure matrix on a monitor.

5. The working status monitoring system as described in claim 1, wherein, The adjustment unit determines whether a first event shown by a first node (which is an arbitrary node) and a second event shown by a second node (which is another arbitrary node) are associated within the specified degree of association, based on at least one of the following: the object related to the occurrence of the first event and the second event, the time of occurrence of the first event and the second event, and the location of occurrence of the first event and the second event.

6. The working status monitoring system as described in claim 1, wherein, The event detection unit uses at least one of a ranging sensor and a camera to detect the plurality of events occurring in the working area.

7. A method for monitoring work status, wherein, The computer detects multiple events occurring in the work area. Generate an event network consisting of multiple nodes representing the detected events and multiple edges representing the order in which the nodes occur. Adjust the resolution of the generated event network to the resolution specified by the user. The event network, with its resolution adjusted, is then transformed into information representing the relationship between the occurrence order of multiple events, i.e., a design structure matrix. Output information related to the design structure matrix. The resolution refers to the number of nodes that make up the event network. The higher the resolution, the more nodes there are; the lower the resolution, the fewer nodes there are. When the resolution is reduced, nodes of events that are associated within a specified degree of association among the plurality of nodes are aggregated into a single node.

8. A computer-readable storage medium, wherein, The system stores a working condition monitoring program that causes the computer to perform the following processes: Processing of multiple events occurring in the work area; The process of generating an event network consisting of multiple nodes representing the detected multiple events and multiple edges representing the order of occurrence of the multiple nodes; The process of adjusting the resolution of the generated event network to a resolution specified by the user; The process of converting the resolution-adjusted event network into information representing the relationship between the occurrence order of multiple events is called design structure matrix processing. Processing that outputs information related to the design structure matrix. The resolution refers to the number of nodes that make up the event network. The higher the resolution, the more nodes there are; the lower the resolution, the fewer nodes there are. When the resolution is reduced, nodes of events that are associated within a specified degree of association among the plurality of nodes are aggregated into a single node.

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