Monitoring device, monitoring system, monitoring method, and monitoring program
The monitoring device addresses the challenge of detecting and verifying work abnormalities by acquiring and analyzing image data to identify deviations from normal work procedures, enhancing production line efficiency.
Patent Information
- Application Number
- JP2025037296
- Authority / Receiving Office
- JP · JP
- Patent Type
- Patents
- Current Assignee / Owner
- Filing Date
- 2025-03-10
- Publication Date
- 2026-02-10
- Estimated Expiration
- 2041-02-25
AI Technical Summary
Existing technologies fail to accurately detect work abnormalities and verify the content of work performed on a production line, as they either rely on cycle time signals, worker recognition, or image comparison at different times, lacking the ability to confirm correct procedural adherence.
A monitoring device that acquires image data of work performed in a predetermined order, detects abnormalities in work time, and adds information indicating the detection to the image data, allowing for verification of work content.
Enables the detection of work deviations from normal procedures and verifies the actual work performed, improving efficiency by identifying and recording abnormalities in production line operations.
Smart Images

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Abstract
Description
[Technical Field]
[0001] The present invention relates to a technique for monitoring a production line, and more particularly to a technique for monitoring the working status. [Background technology]
[0002] On a production line, work procedures are established to maintain quality and ensure safety, and workers follow the procedures. When a quality abnormality occurs, the work procedures may be checked to ensure they are correct. However, finding the timing of the abnormality from work records requires a huge amount of work. Furthermore, verifying the work being performed when the abnormality occurred based on the worker's memory may not accurately identify the cause of the abnormality. Therefore, it is desirable to have a technology that can detect an abnormality and check the work status when an abnormality occurs. For example, Patent Document 1 discloses such an abnormality detection technology.
[0003] Patent Document 1 relates to a production management device that detects abnormalities in the production status. The production management device in Patent Document 1 acquires the cycle time using a signal output when a product is fed from production equipment. The production management device in Patent Document 1 detects an abnormality when the cycle time is below a lower threshold.
[0004] Patent Document 2 discloses a process monitoring device that uses a camera to capture images of multiple processes. When a switch is operated by an operator who recognizes an abnormality, the process monitoring device of Patent Document 2 stores image data of the work area corresponding to the operated switch.
[0005] Patent Document 3 discloses a recording device for image data from a surveillance camera. The recording device in Patent Document 3 compares two sets of image data from different times, and when it determines that the two sets are different, it adds a chapter to the image data and records it. [Prior art documents] [Patent documents]
[0006] [Patent Document 1] Japanese Patent Application Publication No. 2019-061628 [Patent Document 2] Japanese Patent Application Publication No. 2018-128729 [Patent Document 3] Japanese Patent Application Laid-Open No. 2007-081662 Summary of the Invention [Problem to be solved by the invention]
[0007] However, the technology of Patent Document 1 is insufficient in the following respects. The production management device of Patent Document 1 detects cycle time abnormalities using signals output from production equipment, but when an abnormality occurs, it is not possible to verify how the work was performed. Furthermore, the technology of Patent Document 2 does not record video unless the worker recognizes the abnormality, so it is not possible to verify abnormalities that the worker does not recognize. Furthermore, the technology of Patent Document 3 compares images taken at different times, so it is not possible to verify whether the work was performed correctly in the specified order.
[0008] In order to solve the above-mentioned problems, an object of the present invention is to provide a monitoring device or the like that can detect work that differs from normal work and verify the content of the work. [Means for solving the problem]
[0009] In order to solve the above problems, the monitoring device of the present invention includes an image acquisition unit, an abnormality detection unit, and an output unit. The image acquisition unit acquires image data of work performed in a predetermined order. The abnormality detection unit monitors abnormalities in the work time, which is the time required for the work, and, if an abnormality is detected, adds information indicating the detection of the abnormality to the image data acquired when the abnormality was detected. The output unit outputs the image data with the added information.
[0010] The monitoring method of the present invention acquires image data of work performed in a predetermined order. The monitoring method of the present invention monitors abnormalities in work time, which is the time required for the work, and, if an abnormality in work time is detected, adds information indicating the detection of the abnormality to the image data acquired when the abnormality is detected. The monitoring method of the present invention outputs the image data with the added information.
[0011] The monitoring program of the present invention causes a computer to execute a process of acquiring image data of work performed in a predetermined order. The monitoring program of the present invention monitors abnormalities in work time, which is the time required for the work, and, if an abnormality is detected, causes the computer to execute a process of adding information indicating the detection of the abnormality to the image data acquired when the abnormality is detected. The monitoring program of the present invention causes the computer to execute a process of outputting the image data with the added information. [Effects of the Invention]
[0012] According to the present invention, it is possible to detect work that differs from normal work and verify the content of the work. [Brief explanation of the drawings]
[0013] [Figure 1] 1 is a diagram illustrating an outline of the configuration of a first exemplary embodiment of the present invention. [Figure 2] 1 is a diagram illustrating an example of a configuration of a monitoring device according to a first embodiment of the present invention. [Figure 3] FIG. 2 is a diagram illustrating an example of a work procedure according to the first embodiment of the present invention. [Figure 4] FIG. 3 is a diagram illustrating an example of an operation flow of the monitoring device according to the first exemplary embodiment of the present invention. [Figure 5] FIG. 2 is a graph showing an example of operation time in the first embodiment of the present invention. [Figure 6] FIG. 4 is a diagram illustrating another example of the configuration of the first exemplary embodiment of the present invention. [Figure 7] FIG. 10 is a diagram illustrating an outline of the configuration of a second exemplary embodiment of the present invention. [Figure 8]FIG. 10 is a diagram illustrating an example of the configuration of a monitoring device according to a second exemplary embodiment of the present invention. [Figure 9] FIG. 10 is a diagram illustrating an example of an operation flow of a monitoring device according to a second exemplary embodiment of the present invention. [Figure 10] FIG. 10 is a diagram illustrating an example of the configuration of a monitoring device according to a third exemplary embodiment of the present invention. [Figure 11] FIG. 10 is a diagram illustrating an example of an operation flow of a monitoring device according to a third exemplary embodiment of the present invention. [Figure 12] FIG. 10 is a diagram illustrating an example of another configuration of an embodiment of the present invention. DETAILED DESCRIPTION OF THE INVENTION
[0014] (First embodiment) A first embodiment of the present invention will be described in detail with reference to the drawings. FIG. 1 is a diagram showing an outline of the configuration of a monitoring system of this embodiment. The monitoring system of this embodiment includes a monitoring device 10, a photographing device 20, and an input device 30. FIG. 1 shows an example in which a work object is placed on a workbench, and the photographing device 20 is installed in a position where it can photograph the work performed by a worker on the work object. The monitoring device 10 is connected to the photographing device 20 via a network. The monitoring device 10 is also connected to the input device 30 via a network.
[0015] The monitoring system of this embodiment is a system for monitoring work performed on a production line. The monitoring system of this embodiment is used to monitor a production line in which work is repeatedly performed according to a predetermined order. Work that follows a predetermined order refers to work performed in a product assembly process, for example, in which a set order of work is set and the work is performed according to the set order, such as placing work objects on a workbench, removing components, attaching the components to the product, and removing the work objects after the work is completed. The work may be other than product assembly work, such as product packaging and product transportation between processes. Furthermore, as long as the work is performed in a set order, the work may also be performed without short intervals between repetitions, such as workers putting on work clothes and protective gear, washing the workers' bodies and removing dust, and equipment maintenance.
[0016] The following describes the configuration of the monitoring device 10. Fig. 2 is a diagram showing an example of the configuration of the monitoring device 10. The monitoring device 10 includes an image acquisition unit 11, an operation data acquisition unit 12, an abnormality detection unit 13, a storage unit 14, and an output unit 15.
[0017] The image acquisition unit 11 acquires image data of images of work performed in a predetermined order on the production line. The image acquisition unit 11 acquires image data of images of work on the production line captured by the photographing device 20. The image acquisition unit 11 stores the acquired image data in the storage unit 14.
[0018] FIG. 3 is a diagram showing an example of a work instruction manual indicating the order of work to be performed on a production line. FIG. 3 shows an example in which the order of work to be performed in process X of the production line is set. In the example of FIG. 3, a worker in process X takes tool A from the tool storage area and component B from the component shelf, then attaches component B to the product and returns tool A to the tool storage area. After storing tool A in the tool storage area, the worker performs tasks from number 5 onwards in order. The worker in process X repeats the work in the order indicated in the work procedure manual, changing the product to be worked on. The image acquisition unit 11 acquires, from the imaging device 20, image data of images captured of the work performed repeatedly by the worker in the predetermined order as shown in the work instruction manual in FIG. 3.
[0019] The work data acquisition unit 12 acquires data on the worker's identification information, the work object's identification information, and the start and end times of the work as work history data. For example, the work data acquisition unit 12 acquires the worker's identification information from the input device 30, which the worker inputs into the input device 30 when the worker starts work. The work data acquisition unit 12 may also acquire the worker's identification information from a production management system (not shown). Alternatively, the worker's identification information may be input directly to the monitoring device 10.
[0020] The work data acquisition unit 12 acquires, from the input device 30, the identification information of the work object, which is read, for example, at the start and end of the work. The identification information of the work object is read, for example, from a barcode containing identification information attached to the work object. A barcode reading device is installed, for example, on a workbench. The barcode containing identification information is read, for example, by the worker operating the barcode reading device. The work data acquisition unit 12 also acquires the times at which the identification information is read as the start and end times of the work. The work data acquisition unit 12 associates the data of the worker's identification information, the identification information of the work object, and the start and end times of the work and stores them in the memory unit 14. The start and end times of the work may be input into the input device 30 by the worker's operation.
[0021] The anomaly detection unit 13 calculates the time required for a task as the task time from the data on the start and end times of the task. The task time per task performed repeatedly according to a set order is also called the cycle time. The anomaly detection unit 13 identifies an abnormality in the task time when the task time is outside the standard range of normal task times. The task time for tasks performed according to a predetermined procedure will not deviate significantly from the average value if performed in the correct order. Therefore, the anomaly detection unit 13 compares the task time with the standard and identifies task time outside the standard range as an abnormality, thereby making it possible to detect tasks that may be a cause of defects in the product being worked on.
[0022] For example, the abnormality detection unit 13 determines that an abnormality has occurred in the work time when the work time is equal to or greater than a preset threshold. Furthermore, the abnormality detection unit 13 determines that an abnormality has occurred in the work time when the work time is less than a preset threshold. The threshold that sets the boundary between the normal range and an abnormality may be either an upper limit or a lower limit. The threshold used to determine whether or not there is an abnormality in the work time is set using the time required for the work when it is performed normally. The standard indicating the range of normal work time is set for each type of work. Furthermore, the standard indicating the range of normal work time may be set for each worker, or may be set according to the worker's level of proficiency in the work.
[0023] When the abnormality detection unit 13 identifies that an abnormality has occurred during work time, the abnormality detection unit 13 adds information indicating that an abnormality has been detected to the image data. When an abnormality is detected, the abnormality detection unit 13 adds information indicating that an abnormality has been detected (hereinafter also referred to as abnormality detection information) to the image data stored in the storage unit 14.
[0024] The storage unit 14 stores image data and work history data. The storage unit 14 is configured, for example, by a hard disk drive. The storage unit 14 may also be configured by other storage devices such as a non-volatile semiconductor storage device. The storage unit 14 may also be configured by a combination of multiple types of storage devices.
[0025] The output unit 15 outputs the image data to which the abnormality detection information is added to a display device (not shown). The output unit 15 may also output the image data to which the information indicating that an abnormality has been detected is added to a terminal device or a server connected via a network.
[0026] The processes in image acquisition unit 11, work data acquisition unit 12, abnormality detection unit 13, and output unit 15 are performed by, for example, executing a computer program in a CPU (Central Processing Unit). The processes in image acquisition unit 11, work data acquisition unit 12, abnormality detection unit 13, and output unit 15 may be performed by a semiconductor device such as an FPGA (Field Programmable Gate Array) or an ASIC (Application Specific Integrated Circuit).
[0027] The imaging device 20 captures images of work being performed on a production line. The imaging device 20 is installed so that it can capture images of the work state, such as the worker's hands. The imaging device 20 generates image data of the captured image and sends the generated image data to the monitoring device 10. The imaging device 20 is configured using, for example, a camera that captures images in the visible light range. The imaging device 20 may also use a camera that captures images in a range other than the visible light range, such as a far-infrared camera.
[0028] The input device 30 accepts input of data on the worker's identification information, the work object's identification information, and the start and end times of the work as work history data. The input device 30 sends the accepted work history data to the monitoring device 10. The input device 30 acquires the worker's identification information, for example, by reading the identification information on an ID card held by the worker. The input device 30 acquires information on the work object, for example, by reading the lot number information attached to the product being worked on. The input device 30 identifies the start and end times of the work, for example, based on the times when the start and end of the work are input by the worker's operation. The input device 30 may also acquire information on the start and end times of the work by reading the work object's identification information at the start and end of the work by the worker's operation. The input device 30 may also identify the start and end times of the work by acquiring information on the placement of the work object on the work table and the removal of the work object from the work table via a sensor.
[0029] The operation of the monitoring system of this embodiment will be described below with reference to Fig. 4, which is a diagram showing an example of the operation flow of the monitoring device 10.
[0030] The image capturing device 20 captures images of workers working on the production line. The image capturing device 20 sends image data of the captured images to the monitoring device 10. The input device 30 also acquires identification information of the worker, identification information of the work target, and information on the start and end times of the work, and sends this information to the monitoring device 10 as work history data.
[0031] 4, the image acquisition unit 11 acquires image data of an image of a task from the photographing device 20 (step S11). Upon acquiring the image data, the image acquisition unit 11 stores the acquired image data in the storage unit .
[0032] Furthermore, the work data acquisition unit 12 acquires data on the worker's identification information, the work object's identification information, and the start and end times of the work as work history data (step S12). Once the work history data has been acquired, the anomaly detection unit 13 calculates the work time from the work start time and the work end time (step S13). After calculating the work time, the anomaly detection unit 13 compares the calculated work time with a standard for normal work time.
[0033] If the calculated work time is within the standard range (Yes in step S14), and if the production line being monitored continues to operate (Yes in step S17), the monitoring device 10 continues the operation of monitoring whether or not there is an abnormality in the work time from step S11.
[0034] If the calculated work time is outside the reference range (No in step S14), the abnormality detection unit 13 adds information indicating that an abnormality has occurred in the work time to the image data (step S15). The abnormality detection unit 13 adds the abnormality detection information to the image data acquired when the abnormality in the work time is detected, and stores the image data in the storage unit 14. The abnormality detection information may also include identification information of the worker who was working when the abnormality was detected and identification information of the work target.
[0035] Once the abnormality detection information has been added to the image data, the output unit 15 outputs the image data of the portion to which the abnormality detection information has been added (step S16). The output unit 15 outputs the image data of the portion to which the abnormality detection information has been added to, for example, a terminal device (not shown) carried by a production line manager. The output unit 15 outputs, for example, image data of a length from the portion to which the abnormality detection information has been added, going back by the work time, i.e., from the image corresponding to the work start time, to the image of the portion to which the abnormality detection information has been added, i.e., the image corresponding to the work end time, to the terminal device.
[0036] When the terminal device requests image data of a location where an abnormality has occurred, the output unit 15 may output the image data of the portion to which the abnormality detection information has been added to the terminal device. Also, the output unit 15 may output the image data of the portion requested by an operation performed by checking the image data to which the abnormality detection information has been added to the terminal device.
[0037] When the image data of the portion to which the abnormality detection information is added is output, if the production line being monitored is still operating (Yes in step S17), the monitoring device 10 continues the operation of monitoring for the presence or absence of abnormalities from step S11.
[0038] In step S17, when the operation of the production line is stopped (No in step S17), the monitoring device 10 ends the operation of monitoring the production line.
[0039] FIG. 5 is a diagram schematically illustrating an example of a graph generated using records of work time. The horizontal axis of FIG. 5 indicates, for example, the end time of a work, and the vertical axis indicates the work time of the work completed at each time. A threshold value Th in FIG. 5 is set as a criterion for determining an abnormality in work time, and when the work time is equal to or greater than Th, the abnormality detection unit 13 determines that an abnormality in work time has occurred. In the example of FIG. 5, the lower limit of the normal range is not indicated, but the criterion for indicating the normal range may be set using threshold values indicating lower and upper limits.
[0040] The output unit 15 may output display data displaying a graph such as that shown in Fig. 5 to the terminal device. In a configuration in which a graph such as that shown in Fig. 5 is displayed, for example, when a black circle at the position of an abnormality is selected by an operation of the user of the terminal device, that is, when any of the data for the work time is selected, the output unit 15 may output corresponding image data to the terminal device. With such a configuration, the user of the monitoring system can easily determine the image data to be checked by referring to the work time.
[0041] The output unit 15 may output statistical data on work time to a terminal device. For example, the output unit 15 may calculate the number of abnormal work time events per predetermined period and the average number of abnormal work time events per predetermined period and output them to the terminal device. When outputting the statistical data on work time, the output unit 15 may also output statistical data on abnormal work time events for each individual, group, and process to the terminal device. By outputting such statistical data, a production line manager can refer to the trend of abnormal work time events and manage processes more efficiently by referring to image data.
[0042] When calculating statistical data on work time, if the variation in work time is equal to or greater than a preset standard, the output unit 15 may output information indicating that the variation in work time is large to the terminal device. If the variation in work time is large, it is possible that the work performed by the workers is not stable. Therefore, by outputting information indicating that the variation in work time is large, the manager of the production line can verify the content of the work and improve the efficiency of the work.
[0043] In the above example, the monitoring device 10 monitors the work time of the work photographed by one of the photographing devices 20 and stores the image data, but the monitoring device 10 may also monitor the work time of each of the work photographed by multiple photographing devices 20.
[0044] FIG. 6 shows an example in which work is photographed using five camera devices 20. In the example of FIG. 6, the work in each work section is photographed by a camera device 20 installed in each work section. An input device 30 is also installed for each work section. In the example of FIG. 6, the work data acquisition unit 12 of the monitoring device 10 acquires work history data for each work section. The abnormality detection unit 13 monitors whether or not there is an abnormality in the work time, and if an abnormality is detected, adds abnormality detection information to the image data of the image of the work section in which the abnormality was detected. In the example of FIG. 6, a camera device 20 is installed in each work section, but a configuration in which one camera device 20 photographs multiple work sections may also be used. In such a configuration, the monitoring device 10 may add information about the work section in which the abnormality was detected to the image data in addition to the abnormality detection information. The number of camera devices 20 may be other than five.
[0045] As described above, when the monitoring system of this embodiment detects an abnormality in the work time per repetition of a task that is repeated according to a preset procedure, it adds anomaly detection information, which is information indicating the detection of the abnormality, to a captured image of the task and saves the image. The work time per repetition, also known as cycle time, does not fluctuate significantly if the task is performed correctly according to the work procedure. If the work time fluctuates, it is possible that the task was not performed according to the correct procedure and that an abnormality has occurred in the product. The monitoring system of this embodiment adds anomaly detection information to image data of the work time and saves it. By referencing the information during verification, for example, it is possible to check images of areas where an abnormality may have occurred in the product and confirm the actual work procedure. As a result, the monitoring system of this embodiment can detect tasks that deviate from normal work and verify the content of the work.
[0046] (Second embodiment) A second embodiment of the present invention will be described in detail with reference to the drawings. Fig. 7 is a diagram showing an outline of the configuration of a monitoring system of this embodiment. The monitoring system of this embodiment includes a monitoring device 40, an image capturing device 20, and an input device 30. The monitoring device 40 is connected to the image capturing device 20 via a network. The monitoring device 40 is also connected to the input device 30 via a network.
[0047] The monitoring system of the first embodiment calculates the work time from input data of the start and end times of the work and detects abnormalities in the work time. In contrast to such a configuration, the monitoring system of this embodiment calculates the work time by detecting the movement of the worker from image data of the work, thereby identifying the start and end times of the work.
[0048] The configurations and functions of the photographing device 20 and the input device 30 of this embodiment are similar to those of the photographing device 20 and the input device 30 of the first embodiment, respectively.
[0049] The configuration of the monitoring device 40 will be described. Fig. 8 is a diagram showing an example of the configuration of the monitoring device 40. The monitoring device 40 includes an image acquisition unit 11, an image analysis unit 41, a data acquisition unit 42, an abnormality detection unit 13, a storage unit 14, and an output unit 15. The configurations and functions of the image acquisition unit 11, the storage unit 14, and the output unit 15 of this embodiment are similar to those of the parts of the same names in the first embodiment.
[0050] The image analysis unit 41 detects the movement of the worker from the image data. For example, the image analysis unit 41 detects the color of the hand, the movement of the gloves worn by the worker, or the movement of the worker's equipment using a well-known image recognition technology. For example, the image analysis unit 41 generates time-series data in which "1" indicates that the movement of the worker is detected and "0" indicates that the movement is not detected.
[0051] The image analysis unit 41 identifies the start time and end time of the work. The image analysis unit 41 identifies the time when a movement is detected after a period of time during which no movement is detected continues for a predetermined time or longer as the start time of the work. Furthermore, after identifying the start time of the work, when a period of time during which no movement is detected continues for a predetermined time or longer, the image analysis unit 41 identifies the time when the last movement was detected as the end time of the work.
[0052] The data acquisition unit 42 acquires the identification information of the worker and the identification information of the work target as work history data. For example, the data acquisition unit 42 acquires the identification information of the worker from the input device 30, which the worker inputs into the input device 30 when the worker starts work. The data acquisition unit 42 may also acquire the identification information of the worker from a production management system (not shown). Alternatively, the identification information of the worker may be input directly to the monitoring device 40.
[0053] The data acquisition unit 42 acquires the identification information of the work object from the input device 30, which is read, for example, at the start and end of the work. The identification information of the work object is read in the same manner as in the first embodiment. The data acquisition unit 42 associates the identification information of the worker and the identification information of the work object with the acquisition date and time of the information and stores them in the storage unit 14. Furthermore, the worker and the work object may be identified by image recognition in the image analysis unit 41.
[0054] The anomaly detection unit 13 calculates the work time from the start time and end time of the work identified by the image analysis unit 41. When the work time is outside the standard range of normal work time, the anomaly detection unit 13 identifies that an abnormality has occurred in the work time. The anomaly detection unit 13 identifies the presence or absence of an abnormality in the same manner as in the first embodiment. When the anomaly detection unit 13 detects an abnormality in the work time, it adds anomaly detection information, which is information indicating that an abnormality has been detected, to the image data. When an abnormality is detected, the anomaly detection unit 13 adds the anomaly detection information to the position of the image stored in the memory unit 14.
[0055] The image analysis unit 41 is implemented by, for example, executing a computer program in a CPU. Each process in the image analysis unit 41 may be implemented by a semiconductor device such as an FPGA or an ASIC.
[0056] The operation of the monitoring system of this embodiment will be described below with reference to Fig. 9. Fig. 9 is a diagram showing an example of the operation flow of the monitoring device 40.
[0057] The photographing device 20 photographs the work of workers on the production line. The photographing device 20 sends image data of the photographed image to the monitoring device 40. The input device 30 also acquires identification information of the worker and identification information of the work target, and sends this to the monitoring device 40 as work history data.
[0058] 9, the image acquisition unit 11 of the monitoring device 40 acquires image data of work on the production line from the imaging device 20 (step S21). Upon acquiring the image data, the image acquisition unit 11 stores the acquired image data in the storage unit 14. Furthermore, the data acquisition unit 42 acquires the identification information of the worker and the identification information of the work target as work history data.
[0059] When the image data is acquired, the image analysis unit 41 identifies the start time and end time of the work from the image data (step S22). Once the start time and end time of the work have been identified, the abnormality detection unit 13 calculates the work time from the start time and end time of the work (step S23). After calculating the work time, the abnormality detection unit 13 compares the calculated work time with a standard for normal work time.
[0060] If the calculated work time is within the standard range (Yes in step S24), and if the production line being monitored continues to operate (Yes in step S27), the monitoring device 40 continues the operation of monitoring for abnormalities from step S21.
[0061] If the calculated work time is outside the reference range (No in step S24), the abnormality detection unit 13 adds abnormality detection information to the image data (step S25). The abnormality detection unit 13 adds the abnormality detection information to the image data acquired when an abnormality in the work time is detected, and stores the image data in the storage unit 14. The abnormality detection information may also include identification information of the worker who was performing the work when the abnormality was detected and identification information of the work target.
[0062] When the abnormality detection information is added to the image data, the output unit 15 outputs the image data of the portion to which the abnormality detection information is added (step S26). When the image data of the portion to which the abnormality detection information is added is output, if the operation of the production line to be monitored is continuing (Yes in step S27), the monitoring device 40 continues the operation of monitoring for the presence or absence of abnormalities from step S21.
[0063] In step S27, when the operation of the production line is stopped (No in step S27), the monitoring device 40 ends the operation of monitoring the production line.
[0064] The monitoring system of this embodiment identifies the start and end times of work, which is repeated according to a preset procedure, by analyzing image data captured of the work. Therefore, the monitoring system of this embodiment can accurately calculate work time because the worker does not need to input information about the start and end times of the work. Therefore, the monitoring system of this embodiment can more accurately detect abnormalities in work time. By improving the accuracy of detecting abnormalities in work time, the monitoring system of this embodiment can more efficiently check image data that may contain abnormalities.
[0065] (Third embodiment) The third embodiment of the present invention will be described in detail with reference to the drawings. Fig. 10 is a diagram showing an outline of the configuration of a monitoring device 100 of this embodiment.
[0066] The monitoring device 100 of this embodiment includes an image acquisition unit 101, an abnormality detection unit 102, and an output unit 103. The image acquisition unit 101 acquires image data of work performed in a predetermined order. The abnormality detection unit 102 monitors abnormalities in the work time, which is the time required for the work, and, if an abnormality is detected, adds information indicating that the abnormality has been detected to the image data acquired when the abnormality was detected. The information indicating that an abnormality has been detected is also referred to as abnormality detection information. The output unit 103 outputs the image data to which the information indicating that an abnormality has been detected has been added.
[0067] The image acquisition unit 11 in the first and second embodiments is an example of the image acquisition unit 101. The image acquisition unit 101 is also an aspect of image acquisition means. The abnormality detection unit 13 in the first and second embodiments is an example of the abnormality detection unit 102. The abnormality detection unit 102 is also an aspect of abnormality detection means. The output unit 15 in the first and second embodiments is an example of the output unit 103. The output unit 103 is also an aspect of output means.
[0068] The operation of the monitoring device 100 will be described. FIG. 11 is a diagram showing an example of the operation flow of the monitoring device 100. The image acquisition unit 101 acquires image data of work performed in a predetermined order (step S101). Once the image data has been acquired, the abnormality detection unit 102 monitors for abnormalities in the work time, which is the time required for the work (step S102). If an abnormality is detected, the abnormality detection unit 102 adds information indicating that an abnormality has been detected to the image data acquired when the abnormality was detected (step S103). Once the information indicating that an abnormality has been detected has been added, the output unit 103 outputs the image data to which the information indicating that an abnormality has been detected has been added (step S104).
[0069] The monitoring device 100 of this embodiment monitors abnormalities in the work time of tasks that are repeatedly performed in a predetermined order, and when an abnormality is detected, adds information indicating the detection of the abnormality to the image data. When tasks are performed in a predetermined order, abnormalities in the work time occur when tasks that differ from normal are performed. Therefore, by detecting abnormalities in the work time, it is possible to detect that work that differs from normal work has been performed. Therefore, by using the monitoring device 100 of this embodiment, it is possible to detect work that differs from normal work and verify the content of the work.
[0070] Each process in the monitoring device 10 of the first embodiment, the monitoring device 40 of the second embodiment, and the monitoring device 100 of the third embodiment can be performed by executing a computer program on a computer. Fig. 12 shows an example of the configuration of a computer 200 that executes a computer program that performs each process in the monitoring device 10 of the first embodiment, the monitoring device 40 of the second embodiment, and the monitoring device 100 of the third embodiment. The computer 200 includes a CPU 201, a memory 202, a storage device 203, an input / output I / F (Interface) 204, and a communication I / F 205.
[0071] The CPU 201 reads out and executes computer programs that perform each process from the storage device 203. The CPU 201 may be configured as a combination of a CPU and a GPU (Graphics Processing Unit). The memory 202 is configured with a DRAM (Dynamic Random Access Memory) or the like, and temporarily stores the computer programs executed by the CPU 201 and data being processed. The storage device 203 stores the computer programs executed by the CPU 201. The storage device 203 is configured with, for example, a non-volatile semiconductor storage device. Other storage devices such as a hard disk drive may also be used for the storage device 203. The input / output I / F 204 is an interface that receives input from an operator and outputs display data, etc. The communication I / F 205 is an interface that sends and receives data to and from each device that makes up the monitoring system.
[0072] The computer program used to execute each process can also be stored on a recording medium and distributed. Examples of recording media that can be used include magnetic tapes for recording data and magnetic disks such as hard disks. Optical disks such as CD-ROMs (Compact Disc Read Only Memory) can also be used as recording media. Non-volatile semiconductor storage devices can also be used as recording media. [Explanation of symbols]
[0073] 10 Monitoring equipment 11 Image acquisition unit 12 Work data acquisition section 13 Abnormality detection unit 14 Storage section 15 Output section 20 Imaging equipment 30 Input Devices 40 Monitoring equipment 41 Image analysis unit 42 Data Acquisition Section 100 Monitoring equipment 101 Image acquisition unit 102 Abnormality detection unit 103 Output section 200 computers 201 CPU 202 memory 203 Storage device 204 Input / Output Interface 205 Communication I / F
Claims
1. image acquisition means for acquiring image data of work that is repeatedly performed by a worker in a predetermined order; an image analysis means for identifying a start time and an end time of the work from the image data; an anomaly detection means for monitoring a work time, which is the time required for each repetition of the work that is repeatedly performed by the worker in a predetermined order, based on the start time and the end time, and for detecting an abnormality in the variation in the work time by the worker when the variation in the work time that the worker repeatedly performs in the predetermined order is equal to or exceeds a standard, and for adding information indicating the detection of the abnormality to image data acquired when the abnormality is detected in the work time; an output means for outputting image data to which the information has been added; A monitoring device comprising:
2. The monitoring device according to claim 1, wherein the image analysis means determines the start time and the end time based on the time when the movement is detected when a period of time during which no movement is detected continues for a predetermined period of time or longer.
3. 3. The monitoring device according to claim 1, wherein the output means outputs image data for a period of time corresponding to the operation period during which the abnormality was detected.
4. 4. The monitoring device according to claim 1, wherein the output means outputs display data that displays the work time as a graph, and outputs the image data that corresponds to selected data.
5. a plurality of photographing devices that photograph images of work that is repeatedly performed in a predetermined order and output image data of the photographed images; The monitoring device according to any one of claims 1 to 4. Equipped with The image acquisition means acquires the image data from each of the photographing devices, and the abnormality detection means monitors abnormalities in the work time of the image data for each of the photographing devices, and when an abnormality is detected, adds information indicating that an abnormality has been detected to the image data acquired at the time the abnormality was detected.
6. The system captures image data of the workers repeatedly performing tasks in a set order, Identifying the start time and end time of the work from the image data; Based on the start time and the end time, a work time, which is the time required for each repetition of the work performed repeatedly in a predetermined order by the worker, is monitored; if the variation in the work time performed repeatedly in a predetermined order by the worker is equal to or exceeds a standard, an abnormality in the variation in the work time by the worker is detected; and if an abnormality in the work time is detected, information indicating the detection of the abnormality is added to image data acquired when the abnormality is detected; A monitoring method that outputs image data to which the information is added.
7. The monitoring method according to claim 6, wherein when a period of time during which no motion is detected continues for a predetermined period of time or longer, the start time and the end time are determined based on the time at which motion is detected.
8. A process of acquiring image data of work that is repeatedly performed by a worker in a predetermined order; A process of identifying a start time and an end time of the work from the image data; a process of monitoring a work time, which is the time required for each repetition of the work that is repeatedly performed by the worker in a predetermined order, based on the start time and the end time, detecting an abnormality in the variation in the work time by the worker when the variation in the work time that the worker repeatedly performs in the predetermined order is equal to or exceeds a standard, and when an abnormality in the work time is detected, adding information indicating the detection of the abnormality to image data acquired when the abnormality is detected; a process of outputting the image data to which the information has been added; A monitoring program that causes a computer to run the following.
9. The monitoring program of claim 8, which causes a computer to execute a process for identifying the start time and the end time based on the time when the movement is detected when a period of time during which no movement is detected continues for a predetermined period of time or longer.
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