Analysis device, analysis system, analysis method, program, and storage medium

Abstract

To provide an analysis device, an analysis system, an analysis method, a program, and a storage medium capable of automatically analyzing work.SOLUTION: An analysis device according to an embodiment performs analysis on a plurality of works in a manufacturing process. The analysis device receives images from an imaging device that captures the images as each of the plurality of works is performed. The analysis device receives a detection signal detected by a tool from the tool used in at least one of the plurality of works. The analysis device refers to end determination data for determining the end of each of the plurality of works. The analysis device determines end of each of the plurality of works based on the images, the detection signal, and the end determination data.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] FIELD Embodiments of the present invention relate to an analysis device, an analysis system, an analysis method, a program, and a storage medium. [Background technology]

[0002] There is a need to develop technology that can automatically perform work analysis. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Re-tabled publication 2017 / 033561 Summary of the Invention [Problem to be solved by the invention]

[0004] The problem to be solved by the present invention is to provide an analysis device, an analysis system, an analysis method, a program, and a storage medium that are capable of automatically analyzing work. [Means for solving the problem]

[0005] An analysis device according to an embodiment performs analysis of a plurality of tasks in a manufacturing process. The analysis device receives images from an imaging device that captures images of each of the plurality of tasks when the task is performed. The analysis device receives a detection signal detected by a tool used in at least one of the plurality of tasks. The analysis device references completion determination data for determining completion of each of the plurality of tasks. The analysis device determines completion of each of the plurality of tasks based on the images, the detection signal, and the completion determination data. [Brief explanation of the drawings]

[0006] [Figure 1] FIG. 1 is a schematic diagram illustrating an analysis system according to an embodiment. [Figure 2] 10 is a table illustrating example work data. [Figure 3] 10 is a table illustrating example work data. [Figure 4] 10 is a table illustrating example work data. [Figure 5] 4 is a flowchart showing a process performed by the analysis device according to the embodiment. [Figure 6] 10 is a flowchart showing another process performed by the analysis device according to the embodiment. [Figure 7] FIG. 4 is a schematic diagram showing an example of output from the analysis device according to the embodiment. [Figure 8] FIG. 4 is a schematic diagram showing an example of output from the analysis device according to the embodiment. [Figure 9] FIG. 4 is a schematic diagram showing an example of output from the analysis device according to the embodiment. [Figure 10] FIG. 4 is a schematic diagram showing an example of output from the analysis device according to the embodiment. [Figure 11] FIG. 4 is a schematic diagram showing an example of output from the analysis device according to the embodiment. [Figure 12] FIG. 4 is a schematic diagram showing an example of output from the analysis device according to the embodiment. [Figure 13] 10 is a flowchart illustrating a process performed by the analysis device according to the embodiment when a simulation is executed. [Figure 14] FIG. 2 is a schematic diagram showing a hardware configuration. DETAILED DESCRIPTION OF THE INVENTION

[0007] Hereinafter, embodiments of the present invention will be described with reference to the drawings. In the present specification and the drawings, elements similar to those already described are designated by the same reference numerals, and detailed descriptions thereof will be omitted where appropriate.

[0008] FIG. 1 is a schematic diagram showing an analysis system according to an embodiment. As shown in FIG. 1, the analysis system 1 includes an analysis device 10, an imaging device 20, a tool 30, an input device 40, an output device 50, and a storage device 60.

[0009] The analysis device 10 performs analysis on multiple tasks in a manufacturing process. The imaging device 20 acquires images. The imaging device 20 may acquire video, and images may be extracted from the video. The imaging device 20 captures images of the work site. The imaging device 20 may be attached to a worker. Multiple imaging devices 20 may be provided. For example, an imaging device 20 is provided at each of multiple sites where tasks may be performed.

[0010] The tool 30 is used for work and detects signals during the work. For example, the tool 30 is a digital torque wrench or a digital caliper. The tool 30 includes at least one selected from a torque sensor, an acceleration sensor, and an angular velocity sensor. A plurality of tools 30 may be prepared, and a different tool 30 may be used for each work. The imaging device 20 and the tool 30 transmit the acquired data to the analysis device 10.

[0011] The input device 40 is used by a user to input data to the analysis device 10. The input device 40 includes one or more devices selected from a mouse, a keyboard, a microphone (voice input), and a touchpad. The output device 50 outputs information to a user. The output device 50 includes one or more devices selected from a display, a projector, a speaker, and a printer. For example, a worker wears smart glasses including the imaging device 20, the input device 40 (microphone), and the output device 50 (display). The output device 50 may display input devices such as a virtual keyboard or buttons. The imaging device 20 may capture images of a user operating a virtual input device, and the analysis device 10 may accept input from the user based on the captured images. That is, the analysis device 10 may be capable of executing hand gesture input using motion detection. The storage device 60 appropriately stores work data, data obtained by processing by the analysis device 10, data obtained from the imaging device 20 and the tool 30, and the like.

[0012] 2 to 4 are tables showing examples of work data. As shown in FIGS. 2 to 4, the task data 100 includes worker data 110, individual task data 120, history data 130, manufacturing specification data 140, and a checklist 150.

[0013] As shown in FIG. 2, worker data 110 includes data related to workers. The worker data 110 includes a worker ID 111, authentication means 112, and worker information 113. The worker ID 111 is a character string for identifying the worker. The authentication means 112 indicates a means for authenticating the worker. Examples of authentication means include biometric authentication using an image, fingerprint, voice, etc., and physical authentication using a security card or barcode carried by the worker. The worker information 113 includes the name and affiliation of the worker.

[0014] The individual task data 120 includes data relating to the start, the progress, and the completion of each of a plurality of tasks. In Fig. 2, data relating to the first task of the plurality of tasks is illustrated.

[0015] The individual task data 120 includes data related to the start of a task, such as a data ID 121a, a starting product state 121b, a detection means 121c, and start determination data 121d. The data ID 121a is a character string for identifying a data set related to the start of a task. The starting product state 121b is data indicating the state of the product when the task starts. The detection means 121c indicates a data detection means for determining the start of a task. The start determination data 121d is data for determining the start of a task.

[0016] The individual task data 120 further includes a data ID 122a, an instruction means 122b, and instruction data 122c as data related to task instructions. The data ID 122a is a character string for identifying a data set related to task instructions. The instruction means 122b indicates a means for outputting task instructions to the worker. The output means may be a display on a screen, a voice, or the like. The instruction data 122c is data indicating specific instructions to the worker.

[0017] The individual task data 120 further includes data related to the completion of the task, such as a data ID 123a, a finished product status 123b, a detection means 123c, and completion determination data 123d. The data ID 123a is a character string for identifying a data set related to the completion of the task. The finished product status 123b is data indicating the status of the product when the task is completed. The detection means 123c indicates a data detection means for determining the completion of the task. The completion determination data 123d is data for determining the completion of the task.

[0018] The individual task data 120 also includes data on the start, the duration, and the end of each task, similar to the data illustrated in FIG. 2, for the second and subsequent tasks.

[0019] The detection means 121c and 123c may be detection using an image obtained from the imaging device 20, detection using a signal transmitted from a digital tool, etc. For one task, the detection means for the end of the task may be different from the detection means for the start of the task.

[0020] As an example, the detection means 121c or 123c is configured to extract a worker's skeleton from an image. The imaging device 20 captures an image of the work site. The analysis device 10 inputs the image obtained by the imaging device 20 into a model for extracting the skeleton of a human body. The model includes, for example, a neural network. The analysis device 10 refers to the output result from the model, and determines that work has started if the skeleton is extracted. Alternatively, the analysis device 10 may determine that work has started if it is determined that the worker has touched a specific object based on the skeleton.

[0021] As another example, matching between a captured image and a template image is set as the detection means 121c or 123c. The imaging device 20 is included in smart glasses worn by the worker. The imaging device 20 captures the scene seen by the worker. The analysis device 10 compares the image obtained by the imaging device 20 with a template image prepared in advance. If a portion of the obtained image matches the template image, the analysis device 10 determines that work has started. The template image can be an image of the product at the start of work, an image of the work site, or the like.

[0022] As another example, marker detection is set as the detection means 121c or 123c. A marker may be used to determine the start of work. The marker may be, for example, an Augmented Reality (AR) marker. An object at the work site is registered in advance as an AR marker. A Quick Response (QR) code (registered trademark) may also be used as a marker. In this case, a QR code (registered trademark) is attached to an object at the work site in advance.

[0023] As yet another example, the detection means 121c or 123c is set to detect a signal from the tool 30. When the analysis device 10 receives a signal indicating work from the tool 30, it determines that work has started.

[0024] 3, the history data 130 indicates the history of the start, the duration, and the end of each of a plurality of tasks. In FIG. 3, the history of the first task among the plurality of tasks is illustrated.

[0025] The history data 130 includes a data ID 131a, a date and time 131b, and a worker 131c as history data at the start of work. The data ID 131a is a character string for identifying a data set related to the history at the start of work. The date and time 131b is data indicating the date and time when the work started. The worker 131c is data indicating the worker at the start of work.

[0026] The history data 130 further includes a data ID 132a, a date and time 132b, and a worker 132c as work history data. The data ID 132a is a character string for identifying a data set related to the work history. The date and time 132b is data indicating the date and time when the output instruction was executed. The content of the output instruction is based on the instruction data 122c. The worker 132c is data indicating the worker who executed the instruction.

[0027] The history data 130 further includes, as history data at the time of work completion, a data ID 133a, a date and time 133b, an operator 133c, status data 133d, a determination result 133e, detection data 133f, and log data 133g. The data ID 133a is a character string for identifying a data set related to the history at the time of work completion. The date and time 133b is data indicating the date and time when the work was completed. The operator 133c is data indicating the operator at the time of work completion. The status data 133d is data indicating the state of the product at the time of work completion. For example, an image of the product at the time of work completion is used. The determination result 133e indicates the determination result, such as whether the work has been completed or whether the data obtained by the detection means 123c is normal. The detection data 133f is data obtained by the detection means 123c at the time of work completion. The log data 133g indicates the history of data obtained by the tool 30 during work.

[0028] The history data 130 also includes data indicating the history of the start, the duration, and the end of each task, similar to the data exemplified in FIG. 3, for the second and subsequent tasks.

[0029] The manufacturing specification data 140 is data indicating elements related to manufacturing. The manufacturing specification data 140 includes a standard work man-hour 141. The standard work man-hour 141 indicates the standard man-hour for each work.

[0030] 4, the checklist 150 includes a name 151 of each task, a start time 152 of each task, an end time 153 of each task, man-hours 154 of each task, and a check 155. The start time 152 and the end time 153 are input based on the start and end determination results by the analysis device 10. The period from the start time 152 to the end time 153 corresponds to the man-hours 154. The check 155 is input when it is determined that the task has been completed.

[0031] The operation data 100 is created for each product. For example, even for the same type of product, if at least some of the operation content or operation sequence differs between the respective manufacturing processes, operation data is created for each product.

[0032] FIG. 5 is a flowchart showing the processing performed by the analysis device according to the embodiment. The analysis device 10 identifies the worker according to the authentication means 112 (process S1). For example, the analysis device 10 receives an image of the worker's face from the imaging device 20. The analysis device 10 performs facial recognition from the image to identify the worker. The analysis device 10 may receive fingerprint data of the worker from a fingerprint sensor and identify the worker based on the fingerprint data. The analysis device 10 may receive voice data of the worker from a microphone and identify the worker based on the voice data. The analysis device 10 may receive the results of reading the worker's security card from a card reader and identify the worker based on the reading results. The analysis device 10 may receive the results of reading a barcode or the like assigned to each worker and identify the worker based on the reading results.

[0033] The analysis device 10 references the work data related to the work to be performed (process S2). For example, the user uses the input device 40 to select the manufacturing process to be performed. The analysis device 10 accepts the selection result and references the selected work data. The worker and the work to be performed may be linked in advance. In this case, the analysis device 10 references the work data linked to the worker identified in process S1. The manufacturing process to be performed may be automatically selected based on the progress of other work, etc.

[0034] The analysis device 10 continuously receives data from the imaging device 20 and the tool 30. The analysis device 10 compares the data of the detection means identified by the detection means 121c with the start determination data 121d, and determines the start of work (process S3).

[0035] When it is determined that the work should be started, the analysis device 10 outputs work instructions based on the instruction data 122c to the output device 50 (process S4). For example, the analysis device 10 displays the work instructions on a display. The analysis device 10 may output the work instructions from a speaker. When smart glasses including a display are used, the work instructions may be displayed superimposed on real space using AR technology or Mixed Reality (MR) technology.

[0036] The analysis device 10 compares the detection means data identified by the detection means 123c with the completion determination data 123d and determines whether the work has been completed (process S5). As an example, the analysis device 10 determines that the work has been completed when the signal detected from the tool 30 indicates the completion of the work instruction. As another example, the analysis device 10 compares the image acquired by the imaging device 20 with a template image prepared in advance. If a portion of the acquired image matches the template image, the analysis device 10 determines that the work has been completed. The template image may be an image of the product at the end of the work, an image of the work site, or the like.

[0037] For example, the output of work instructions continues until it is determined that the work has been completed. When it is determined that the work has been completed, the analysis device 10 updates the work data (process S6). For example, the analysis device 10 adds data about the completed work to the history data 130. The analysis device 10 checks the work that has been determined to be completed, and updates the checklist 150.

[0038] The analysis device 10 determines whether all tasks have been completed for the selected manufacturing process (process S7). If not, processes S3 to S6 are repeated for the next task. When all tasks have been completed, the analysis device 10 ends the process.

[0039] The advantages of the embodiment will be described. Product design may be performed for a small number of products. For example, equipment such as plants, factories, and large ships are designed for each product. Here, such products are called indented products. For indented products, the content of the work and the order of each work differ for each product. The time required for the manufacturing process also differs for each product.

[0040] Checking work is an effective way to improve product quality. Conventionally, technology has been used to automatically check work. However, for indented products, automatic work checks are not easy due to the factors mentioned above. For this reason, the manufacturing process of indented products is often checked by a separate worker or supervisor. On the other hand, in order to reduce the manufacturing costs of indented products, it is desirable to reduce the number of people who check work.

[0041] To address this issue, the inventors of the present application have discovered a method that focuses on the state at the end of a task. That is, the state of the product, task, or worker at the end of a task will be constant if the task is performed correctly, regardless of the order in which the tasks are performed.

[0042] Based on this idea, in an embodiment, the analysis device 10 receives images of each task being performed from the imaging device 20. The analysis device 10 receives a detection signal from the tool 30. The analysis device 10 refers to end determination data for determining the end of each of the multiple tasks. Then, the analysis device 10 determines the end of each of the multiple tasks based on the images, the detection signal, and the end determination data.

[0043] For example, when work is not yet complete, the appearance of the product shown in the image varies depending on the work procedure. On the other hand, when work is complete, the appearance of the product shown in the image remains constant regardless of the work procedure. By registering the appearance of the product when work is complete as completion determination data in advance and using this completion determination data, it is possible to accurately determine when work is complete.

[0044] Similarly, the signals transmitted from the tool 30 during work vary depending on the work procedure. The order in which the tool 30 is used also differs depending on the work procedure. On the other hand, the type and number of signals detected until the work is completed are constant regardless of the work procedure. By using the completion determination data related to the detection signals when the work is completed, the completion of the work can be determined more accurately.

[0045] By determining the completion of a task, for example, a task history can be generated based on the determination result of the task completion by the analysis device 10. By comparing the determination result with a pre-prepared task procedure manual, it is possible to automatically check whether there are any omissions in the task. According to the embodiment, tasks can be automatically analyzed even when the manufacturing process differs for each product, such as an indented product.

[0046] In addition, indented products are generally large in size, making it difficult to check the entire product during the manufacturing process. The production area for the product is also large, allowing for flexibility in work locations. Workers may also work inside the product. For this reason, determination based solely on images from the imaging device 20 may result in the possibility that work may be performed outside the imaging range, making it impossible to accurately determine the completion of work. To address this issue, in the embodiment, a detection signal from the tool 30 is used to determine the completion of work. The detection signal from the tool 30 can be received regardless of the location where the work is performed. By using the detection signal in addition to the image to determine the completion of work, the completion of work can be determined more accurately.

[0047] Generally, tasks are performed consecutively in a predetermined order. Therefore, the timing at which the end of a task is determined can be considered the timing at which the next task begins. However, for more accurate task analysis, it is preferable to also determine the start of each task. As described above, the analysis device 10 may refer to start determination data for determining the start of each of the multiple tasks. The analysis device 10 determines the start of each of the multiple tasks based on the image from the imaging device 20, the detection signal from the tool 30, and the end determination data.

[0048] Preferably, the analysis device 10 causes the output device 50 to output work instructions related to one of the multiple tasks while that task is being performed, as shown in the flowchart of FIG. 5, thereby allowing the worker to easily understand the task to be performed.

[0049] Preferably, the analysis device 10 calculates the man-hours for each task based on the determination results of the start and end of each task, as shown in Fig. 4. The analysis device 10 records the man-hours in the task data 100. The analysis device 10 may compare the calculated man-hours with the standard task man-hours in the task data 100. If the calculated man-hours exceed the standard task man-hours, the analysis device 10 may cause the output device 50 to output information indicating this.

[0050] The analysis device 10 may calculate the cost of multiple tasks based on the calculated man-hours. The storage device 60 stores a cost model (e.g., a function) that indicates the relationship between man-hours and costs. The cost model is prepared in advance by the user. When the analysis device 10 calculates the man-hours for each task, it inputs the sum of the man-hours into the cost model. The analysis device 10 obtains an output value of the cost model as the cost. The analysis device 10 may record the cost in the task data or output the cost to the output device 50.

[0051] Preferably, the work data includes a checklist for confirming completion of each work, as shown in Fig. 4. The analysis device 10 inputs data into the checklist based on the start and end determination results. By checking the checklist, the user can easily understand whether each work has been completed.

[0052] The analysis device 10 may determine whether the work has been performed in accordance with the output work instructions. By determining whether the work instructions have been performed, it is possible to prevent work from being omitted and improve product quality.

[0053] FIG. 6 is a flowchart showing another process performed by the analysis device according to the embodiment. Compared with the flowchart shown in FIG. 5, the flowchart shown in FIG. 6 includes steps S4a to S4f instead of step S4.

[0054] One task includes one or more steps. The analysis device 10 outputs task instructions for one step (process S4a). After outputting the task instructions, the analysis device 10 determines whether the performed task conforms to the task instructions based on an image or a detection signal (process S4b). If the performed task does not conform to the task instructions, the analysis device 10 outputs a notification from the output device 50 (process S4c). For example, the notification indicates that the task is incorrect. The notification may be output as a sound or on a display. If the performed task conforms to the task instructions, the analysis device 10 determines whether all steps included in the task have been completed (process S4d).

[0055] When all steps are completed, the analysis device 10 determines whether the content of the work performed conforms to the overall work instructions (process S4e). If the performed work does not conform to the overall work instructions, the analysis device 10 outputs a notification from the output device 50 (process S4f). For example, the work instructions for each step may include the parts to be held, the direction in which the parts should be attached, the orientation of the screws, and the strength of the screws to be tightened. The overall work instructions may include the number of screws fastened, the state of the assembled unit (shape, position), and so on.

[0056] If the performed work conforms to the overall work instructions, the analysis device 10 determines whether the work has been completed (process S5). The conformance of the performed work to the overall work instructions may be set as a condition for determining whether the work has been completed.

[0057] As described above, for indented products, work procedures and the like may vary for each product. The production area is large, and work locations are highly flexible. Therefore, determining the completion of each small step in a single operation requires many detectors or high-performance detectors, which increases manufacturing costs. To address this issue, in an embodiment, one or more steps included in a single operation are defined, and work instructions are set for each step. This makes it possible to determine the completion of that step by providing a detection means corresponding to the work instructions. This allows for improved product and work quality while suppressing increases in manufacturing costs.

[0058] 7 to 11 are schematic diagrams showing examples of outputs from the analysis device according to the embodiment. As an example, a worker is performing an assembly operation for a part (unit) of a manufactured product. The worker wears smart glasses including an imaging device 20, an input device 40, and an output device 50. Fig. 7 is a schematic diagram showing the view seen by the worker through the smart glasses.

[0059] In the example shown in FIG. 7, parts 201 and 202 are placed on a workbench 200. For example, template images of parts 201 and 202 are prepared. The analysis device 10 determines the start of assembly work of parts 201 and 202 by matching an image from the imaging device 20 with the template image. Alternatively, another imaging device 20 captures an image of the vicinity of the workbench 200. The analysis device 10 determines the start of work when the skeletal structure of a worker is recognized near the workbench 200. The analysis device 10 may determine the start of work when it is determined that the worker has touched part 201 or 202 based on the worker's skeletal structure.

[0060] When it is determined that the work has started, the analysis device 10 displays a part image 203, a symbol 204, and a completed image 205. The part image 203 indicates the part 202. The symbol 204 indicates that the part 202 is to be attached to the part 201 from above. The completed image 205 indicates the state in which the part 202 has been attached to the part 201. For example, the analysis device 10 refers to computer-aided design (CAD) drawings of the part 202 and the assembled unit, and displays these CAD drawings as the part image 203 and the completed image 205.

[0061] When part 202 is attached to part 201, part 210 is obtained as shown in Fig. 8. For example, a template image of part 210 is prepared. Analysis device 10 determines that the step of placing part 202 on part 201 is complete by matching the image from imaging device 20 with the template image. Analysis device 10 then displays work instructions for the next step.

[0062] In the example shown in Fig. 8, a screw image 212 and a symbol 213 are displayed on a part 210. The symbol 213 indicates that a screw is to be fastened to the part 202. A digital torque wrench, which functions as a tool 30, is used for fastening. Based on the detection signal from the tool 30, the analysis device 10 determines whether fastening of the screw has started, whether the fastening direction of the screw is appropriate, whether fastening of the screw has been completed, and the like.

[0063] The analysis device 10 may display all work instructions for multiple steps during work. In the example shown in Fig. 9, work instructions 220 are displayed, including work instructions 221 to 224 for four steps in assembling a unit and a message 225. Symbols 226 and 227 indicate completed steps and steps in progress. Message 225 provides specific instructions regarding the step in progress.

[0064] The analysis device 10 may display a checklist 230 during work, as shown in FIG. 10 . The checklist 230 includes a step name 231, a history 232, man-hours 233, and a difference 234. The history 232 indicates whether each step has been completed. A check mark is placed on a completed step. The man-hours 233 include an actual man-hour 233a and a standard man-hour 233b for each step. The actual man-hour 233a indicates the time actually required for that step. The standard man-hour 233b indicates the standard time required for that step. The difference 234 is the difference between the actual man-hour 233a and the standard man-hour 233b. Furthermore, the analysis device 10 may display an image 240 obtained from another imaging device 20, as shown in FIG. 10 . The image 240 shows a skeleton 241 of the worker.

[0065] 11 , one or more selected from the completed image 205, work instructions 220, checklist 230, and image may be displayed on the output device 50 of the smart glasses, superimposed on real space using AR or MR technology. Using MR technology, one or more selected from the completed image 205, work instructions 220, checklist 230, and image may be selectable. For example, the selected data may be reduced or enlarged.

[0066] The analysis device 10 may determine that work has been suspended. For example, from the time when it is determined that work has started to the time when it is determined that work has ended, if a human skeleton is not detected from an image of the work site for a period longer than a predetermined time, the analysis device 10 determines that work has been suspended. After determining that work has been suspended, if a human skeleton is again detected from an image of the work site, the analysis device 10 determines that work has been resumed. From the time when it is determined that work has started to the time when it is determined that work has ended, the analysis device 10 may determine that work has been suspended if a detection signal indicating that the tool 30 is being held by the worker is not transmitted from the tool 30 for a period longer than a predetermined time. After determining that work has been suspended, if a detection signal indicating that the tool 30 is being held is transmitted from the tool 30, the analysis device 10 determines that work has been resumed.

[0067] FIG. 12 is a schematic diagram showing an example of output from the analysis device according to the embodiment. 12, the analysis device 10 may display a Gantt chart 260. The Gantt chart 260 includes a task name 261, a start time 262, an end time 263, a task duration 264, and a chart 265. The chart 265 displays the task time periods and interruption time periods in a distinguishable manner.

[0068] A simulation of the manufacturing process may be performed using the analytical device 10, the work data 100, and data on the product to be manufactured.

[0069] FIG. 13 is a flowchart showing a process performed by the analysis device according to the embodiment when a simulation is executed. The user selects the manufacturing process to be simulated. The analysis device 10 accepts the selection (process S11). The user selects the worker who will perform the simulation and the cost model for cost calculation. The analysis device 10 accepts these selections (process S12). After the selection, the simulation starts.

[0070] In the simulation, a user wears smart glasses including an imaging device 20 and an output device 50 (display). An analysis device 10 acquires data (e.g., three-dimensional CAD data) on products, units, parts, etc. related to the manufacturing process. In the simulation of each task, the analysis device 10 displays an object based on the data on the display of the smart glasses. The object is the product, unit, or part when the task is actually performed. The imaging device 20 captures an image of the worker's view during the simulation. Mixed reality (MR) technology is used for display. When a worker wearing the smart glasses performs a task on the displayed virtual object, the task is reflected in the object.

[0071] When the simulation starts, the analysis device 10 determines the start and end of the work based on start determination data and end determination data in the preset work data (process S13). The start and end determination is performed in the same manner as processes S3 to S6 in the flowchart shown in FIG. 5 or 6. The analysis device 10 calculates the man-hours of the work from the start and end determination results (process S14). The analysis device 10 calculates the cost using the selected cost model (process S15). The analysis device 10 determines whether all the work to be performed by the selected worker has been completed (process S16).

[0072] If all tasks are not completed, the analysis apparatus 10 executes process S13 again for the next task. If all tasks are completed, the analysis apparatus 10 determines whether there is any task that should be performed by another worker in the selected manufacturing process (process S17). If there is any task that should be performed by another worker, process S12 is executed again. If there is no task that should be performed by another worker, the analysis apparatus 10 updates the task data based on the calculated man-hours and costs (process S18). For example, the analysis apparatus 10 updates the standard work man-hours based on the calculated man-hours. The analysis apparatus 10 may further create a distribution of man-hours or costs for multiple tasks.

[0073] The simulation may be performed before the actual manufacturing process, or after the manufacturing process is completed. By performing a simulation before the manufacturing process, workers can experience the work in advance. This can improve the quality of the work in the actual manufacturing process. It also allows for more accurate estimation of labor hours and costs in advance. By performing a simulation after the manufacturing process, workers can practice work that was slower than the standard labor hours. Simulations may be performed both before and after the manufacturing process. Depending on the results of the simulation after the manufacturing process, data such as the standard labor hours set based on the simulation before the manufacturing process may be modified.

[0074] FIG. 14 is a schematic diagram showing a hardware configuration. The analytical device 10 includes, for example, a computer 90 having the configuration shown in Fig. 14. The computer 90 includes a CPU 91, a ROM 92, a RAM 93, a storage device 94, an input interface 95, an output interface 96, and a communication interface 97. The functions of the analytical device 10 may be realized by the cooperation of two or more computers.

[0075] The ROM 92 stores a program that controls the operation of the computer 90. The ROM 92 stores a program necessary for causing the computer 90 to perform each of the above-described processes. The RAM 93 functions as a storage area in which the programs stored in the ROM 92 are expanded.

[0076] The CPU 91 includes a processing circuit. The CPU 91 uses a RAM 93 as a work memory and executes a program stored in at least one of a ROM 92 and a storage device 94. During program execution, the CPU 91 controls each component via a system bus 98 and executes various processes.

[0077] The storage device 94 stores data necessary for executing the program and data obtained by executing the program.

[0078] The input interface (I / F) 95 connects the computer 90 and the input device 95a. The input I / F 95 is, for example, a serial bus interface such as USB. The CPU 91 can read various data from the input device 95a via the input I / F 95.

[0079] The output interface (I / F) 96 connects the computer 90 and the output device 96a. The output I / F 96 is, for example, a video output interface such as a Digital Visual Interface (DVI) or a High-Definition Multimedia Interface (HDMI (registered trademark)). The CPU 91 can transmit data to the output device 96a via the output I / F 96 and cause the output device 96a to display an image.

[0080] The communication interface (I / F) 97 connects the computer 90 to a server 97a external to the computer 90. The communication I / F 97 is, for example, a network card such as a LAN card. The CPU 91 can read various data from the server 97a via the communication I / F 97.

[0081] The storage device 94 includes one or more selected from a hard disk drive (HDD) and a solid state drive (SSD). The input device 95a includes one or more selected from a mouse, a keyboard, a microphone (voice input), and a touchpad. The output device 96a includes one or more selected from a display and a projector. A device having the functions of both the input device 95a and the output device 96a, such as a touch panel, may also be used.

[0082] The various data processing operations described above may be recorded as a computer-executable program on a magnetic disk (such as a flexible disk or hard disk), an optical disk (such as a CD-ROM, CD-R, CD-RW, DVD-ROM, DVD±R, or DVD±RW), a semiconductor memory, or other non-transitory computer-readable storage medium.

[0083] For example, information recorded on a recording medium can be read by a computer (or an embedded system). The recording medium may have any recording format (storage format). For example, a computer reads a program from the recording medium and causes a CPU to execute instructions written in the program based on the program. The computer may acquire (or read) the program via a network.

[0084] The analysis device, analysis system, and analysis method described above can automatically analyze tasks. The same effect can be achieved by using a program that causes a computer to execute the analysis method.

[0085] Although several embodiments of the present invention have been described above, these embodiments are presented by way of example only and are not intended to limit the scope of the invention. These novel embodiments can be embodied in various other forms, and various omissions, substitutions, modifications, etc. can be made without departing from the spirit of the invention. These embodiments and their modifications are included within the scope and spirit of the invention, as well as within the scope of the invention and its equivalents as set forth in the claims. Furthermore, the above-described embodiments can be implemented in combination with each other. [Explanation of symbols]

[0086] 1: analysis system, 10: analysis device, 20: imaging device, 30: tool, 40: input device, 50: output device, 60: storage device, 90: computer, 91: CPU, 92: ROM, 93: RAM, 94: storage device, 95: input interface, 95a: input device, 96: output interface, 96a: output device, 97: communication interface, 97a: server, 98: system bus, 100: work data, 110: worker data, 120: individual work data, 130: history data, 140: manufacturing specification data, 150: checklist, 200: work table, 201, 202: parts, 203: part image, 205: completed image, 210: parts, 212: image, 220: work instructions, 225: messages, 230: Check sheet, 240: Image, 241: Skeleton, 260: Gantt chart

Claims

1. An analysis device that performs analysis on a plurality of operations in a manufacturing process, receiving images from an imaging device that captures images when each of the plurality of tasks is performed; receiving a detection signal detected by a tool used in at least one of the plurality of operations from the tool; referencing completion determination data for determining completion of each of the plurality of tasks; An analysis device that determines the completion of each of the plurality of tasks based on the image, the detection signal, and the completion determination data.

2. Further referencing start determination data for determining the start of each of the plurality of tasks; The analysis device according to claim 1 , wherein the start of each of the plurality of tasks is determined based on the image, the detection signal, and the end determination data.

3. The analysis device according to claim 2 , further comprising an output device that outputs a work instruction relating to one of the plurality of works while the one of the plurality of works is being performed.

4. The analysis device according to claim 2 or 3, wherein the number of man-hours for each of the plurality of tasks is calculated based on a determination result of a start and an end of each of the plurality of tasks.

5. referencing a cost model that indicates the relationship between the man-hours and costs for each of the plurality of tasks; The analysis device according to claim 4 , wherein costs of the plurality of operations are calculated based on the cost model and the calculated plurality of man-hours.

6. The analysis device according to any one of claims 1 to 5, wherein the tool includes at least one selected from a torque sensor, an acceleration sensor, and an angular velocity sensor.

7. Refer to a checklist to confirm the completion of each of the plurality of tasks, 7. The analyzer according to claim 1, wherein a check mark is entered on the check sheet in accordance with a determination of completion of each of the plurality of tasks.

8. referencing instruction data indicating work instructions for one or more of the plurality of works; An analysis device according to any one of claims 1 to 7, which determines whether the performed work conforms to the work instructions for one or more of the plurality of work tasks based on the image, the detection signal, and the instruction data.

9. An analytical device according to any one of claims 1 to 8; the imaging device; The tool; An analysis system equipped with

10. An analysis method for causing a computer to perform an analysis on a plurality of operations in a manufacturing process, comprising: The computer, receiving images from an imaging device that captures images when each of the plurality of tasks is performed; receiving, from a tool used in at least one of the plurality of operations, a detection signal detected by the tool; Referencing completion determination data for determining completion of each of the plurality of tasks; determining the completion of each of the plurality of tasks based on the image, the detection signal, and the completion determination data; Analysis method.

11. A program that causes a computer to perform an analysis of a plurality of operations in a manufacturing process, The computer, receiving images from an imaging device that captures images when each of the plurality of tasks is performed; receiving, from a tool used in at least one of the plurality of operations, a detection signal detected by the tool; Referencing completion determination data for determining completion of each of the plurality of tasks; determining the completion of each of the plurality of tasks based on the image, the detection signal, and the completion determination data; program.

12. A storage medium storing the program according to claim 11.

Images