JP2017068432A - Step organization supporting device, step organization supporting method - Google Patents

Abstract

PROBLEM TO BE SOLVED: To accurately achieve derivation of an efficient step organization while reducing manpower load relating to the organization.SOLUTION: A step organization supporting device that supports the organization of steps including one or plural work operations comprises: a detection information obtaining unit for obtaining, for a worker performing work to be measured, information on the worker's body conditions at each point of time, in a state where the worker is modelled in a simplified way by detection points corresponding to a plurality of his/her body sites and by lines connecting the detection points; an evaluation value calculating unit for calculating an evaluation value for the worker's work on the basis of the information obtained in the detection information obtaining unit; and an output controlling unit that performs an organization simulation for obtaining a plurality of step organizations, in which organization contents are made to differ, regarding a step of one group to be organized, selects one or plural step organizations from among the plurality of step organizations on the basis of an evaluation value for each of the step organizations obtained by the organization simulation, and performs controls for presenting information on the selected step organizations.SELECTED DRAWING: Figure 6

Description

  The present invention relates to a process organization support apparatus and a process organization support method, and relates to a technique for assisting a group of processes in a production line such as a manufacturing factory for the organization of a process by a person such as a line designer.

JP 2001-101422 A Japanese Patent Laying-Open No. 2015-125578

Japanese Patent Application Laid-Open No. 2004-228561 discloses a technique that associates the state of a human body and work object being worked with the burden on the human body, monitors the state of the human body and work object, and provides data effective for work improvement.
Patent Document 2 discloses a technique for evaluating a posture of a working posture or the like based on an objective evaluation and a subjective evaluation.

Many parts are assembled by workers in the automobile manufacturing process. By continuing this work for a long time, the work burden increases, and there are many cases where work efficiency decreases with time.
This work burden is usually taken up as an operator's sensory voice. In addition, the impression and fatigue of the process differ depending on the weakness of the operator. In particular, workers are different from each other in their specific tasks and tasks that they are not good at.
However, such a sense of burden and orientation / unsuitability are only subjectively felt by the operator, and it has been difficult to objectively judge them.

  In a production line that includes a large number of processes and a large number of operations, the workload and status of each worker in each process is not objective for managing personnel assignments in each process. And quantitative evaluation is required.

  Further, in order to improve the manufacturing efficiency, it is desirable to organize a group of processes in consideration of the work load (work load) and the orientation / non- orientation of the worker. However, it is difficult to objectively and quantitatively determine what process organization is actually effective. In addition, it is conceivable to actually execute the work for a plurality of process formations that can be assumed and derive an optimal process formation based on the feedback from the worker. It is not realistic in terms of cost and time.

  Therefore, an object of the present invention is to realize efficient process composition derivation while accurately and reducing the burden on personnel involved in composition.

The process organization support device according to the present invention is a process organization support device that assists in the organization of a process including one or a plurality of operations, and corresponds to a plurality of body parts for an operator who performs the operation to be measured. Based on the information obtained by the detection information acquisition unit, the detection information acquisition unit for acquiring information on the physical state of the worker at each time point, in a state modeled by a line connecting the detection point and the detection point, An evaluation value calculation unit for calculating an evaluation value for the work of the worker, and a knitting simulation for obtaining a plurality of process knittings with different knitting contents for a group of processes to be knitted, and the process knitting obtained by the knitting simulation An output control unit that performs control for selecting one or a plurality of process organizations from the plurality of process organizations and presenting information of the selected process organizations based on the evaluation value for each Obtain.
That is, the worker's body state is detected by a simple model, and the operator's movement can be grasped by the detection point and the position or change (movement vector) of the detection point or line for each body part, for example, a joint. Then, based on the information about the detection points or lines, that is, individual data such as each part of the body (arms, hips, feet), etc., an evaluation value for the work of the worker is calculated, and a plurality of process knitting with different knitting contents Based on the evaluation value obtained for each, one or a plurality of process organizations are selected from the plurality of process organizations, and control for presenting information on the selected process organizations is performed. At this time, since the evaluation value is calculated based on the actual measurement data on the worker's physical condition, an objective and quantitative value can be obtained. Moreover, since the evaluation value is obtained for each of the plurality of process formations by the knitting simulation, the burden of causing the worker to actually perform the work on the plurality of process formations that can be assumed is unnecessary.

In the above-described process organization support device, the process composition support device includes an operation determination unit that determines an attitude or operation of an operator based on a change in the detection point or line in the information obtained by the detection information acquisition unit, and the evaluation value calculation unit It is conceivable to obtain a work burden value calculated based on the posture or motion of the worker determined by the motion determination unit as the evaluation value.
Thereby, in the knitting simulation, a work burden value for each process knitting having different knitting contents is obtained, and one or a plurality of process knittings are selected based on the work burden value.

In the process organization support apparatus, the evaluation value calculation unit compares the information about the detection point or line in the information obtained by the detection information acquisition unit with reference information set for the work to be measured. It is conceivable to calculate an adaptive value for the work of the worker and obtain the adaptive value as the evaluation value.
Thereby, in the knitting simulation, an adaptive value for each process knitting having different knitting contents is obtained, and one or a plurality of process knittings are selected based on the adaptive value.

In the above-described process organization support device, the evaluation value calculation unit calculates the evaluation value for each of the workers when each of the plurality of workers executes the group of processes, and the output control unit includes: As the knitting simulation, a simulation of rearranging work between the group of processes executed by the plurality of workers is performed, and one or more process knitting is performed based on the evaluation value for each process knitting obtained by the knitting simulation. Can be considered.
This makes it possible to derive an efficient process organization including the organization of personnel as workers.

The above-described process organization support apparatus includes a required time acquisition unit that acquires the work required time of the worker, and the output control unit includes the evaluation value and the required operation time for each process organization obtained by the composition simulation. Based on the above, it is conceivable to select one or a plurality of process arrangements.
Thereby, it is possible to derive the process organization in consideration of the length of time required for the work.

In the above-described process organization support device, the detection information acquisition unit may acquire a three-dimensional position of the plurality of detection points from an analysis result of image data obtained by imaging an operator.
If the worker is imaged and the captured image is analyzed, the three-dimensional position of the detection point of the worker can be specified.

The process organization support method according to the present invention is a process organization support method for assisting organization of a process including one or a plurality of operations, and corresponds to a plurality of body parts with respect to an operator who performs the operation to be measured. Based on the detection information acquisition procedure for acquiring information on the physical state of the worker at each time point and the information obtained by the detection information acquisition procedure in a state modeled by a line connecting the detection points and the detection points, An evaluation value calculation procedure for calculating an evaluation value for the work of the worker, and a knitting simulation for obtaining a plurality of process knittings with different knitting contents for a group of processes to be knitted, and the process knitting obtained by the knitting simulation Output control for performing control for selecting one or a plurality of process organizations from the plurality of process organizations and presenting information of the selected process organizations based on the evaluation value for each And forward, the one in which the information processing device executes.
Thereby, the process scheduling support apparatus according to the present invention described above can be realized using the information processing apparatus.

  According to the present invention, efficient process composition derivation can be realized accurately and while reducing the burden on personnel involved in composition.

It is a block diagram of a process organization support system of an embodiment of the present invention. It is explanatory drawing of the simple model of the worker's physical condition of embodiment. It is explanatory drawing of the attitude | position and motion detection by the simple model of embodiment. It is explanatory drawing of the three-dimensional positional information and process of each detection point detected in embodiment. It is explanatory drawing of the calculated value about each process calculated | required by embodiment. It is a flowchart of the process of the calculating part of embodiment. It is explanatory drawing of the work burden evaluation information of embodiment. It is explanatory drawing of the work burden evaluation information of embodiment. It is the figure which showed the example of the work burden value obtained for every worker who performed a group of processes, respectively. It is the figure which showed the example of the work required time calculated for every worker who respectively performed a group of processes. It is the figure which showed the information presentation example of the optimal process organization of embodiment. It is the flowchart which showed the process which should be performed when selecting an optimal process organization using an adaptive value as an evaluation value. It is a flowchart of an example of adaptability determination processing. It is the figure which showed the example of the adaptive value for every operator and process which were calculated by the process of FIG. It is explanatory drawing about the example of leveling of a work burden.

<System configuration>
Hereinafter, an embodiment of a process organization support apparatus according to the present invention will be described. In addition, the calculating part 1 shown in FIG. 1 becomes embodiment of the process organization assistance apparatus which concerns on this invention. FIG. 1 shows an example of a process organization support system including a calculation unit 1.

  As shown in FIG. 1, the process organization support system includes a calculation unit 1, a database unit 2, a storage unit 3, a display unit 4, a communication unit 5, a printing unit 6, an imaging unit 10, a drive unit 11, a sensor 20, and a reception unit 21. The detection value generation unit 22 is included.

The imaging unit 10 is a video camera installed on a production line, and images a worker who performs a process operation. Although the figure shows an example having two imaging units 10, it is usually assumed that a larger number of the imaging units 10 are arranged so that an operator can be imaged in each process of the production line.
The one or a plurality of imaging units 10 supply the calculation unit 1 with captured image data of each frame captured as a moving image.
Note that the imaging unit 10 performs stereo imaging, and the captured image signal obtained by stereo imaging can also obtain information in the depth direction by using the principle of triangulation in image analysis.
The drive unit 11 is a device that displaces the imaging direction of the imaging unit 10 and includes, for example, a pan / tilt mechanism and its drive motor.

The sensor 20 is assumed to be, for example, a sensor that the worker wears at various places on the body, a sensor that is installed at the work position and detects the movement of the worker, and the like. Specifically, an angular velocity sensor, an acceleration sensor, an infrared sensor, a position sensor, and the like.
The detection signal of each sensor 20 is supplied to the reception unit 21 by wire or wirelessly, and the detection signal received by the reception unit is decoded into a detection value by the detection value generation unit 22 and supplied to the calculation unit 1.

  In the system shown in FIG. 1, the imaged image signal of the worker by the imaging unit 10 and the detection value by the sensor 20 are information for detecting the posture and motion of the worker. For this reason, at least one of the imaging unit 10 and the sensor 20 may be used. Of course, both may be used to supplement or correct each other's information.

The computing unit 1 is constituted by a computer device, for example. In other words, the calculation unit 1 includes a CPU (Central Processing Unit), a ROM (Read Only Memory), a RAM (Random Access Memory), an interface unit, and the like, and the CPU executes various processes according to programs stored in the ROM. To do. The RAM appropriately stores data necessary for the CPU to execute various processes.
Note that the information processing apparatus as the computing unit 1 may be realized by a single computer apparatus, or may be realized in cooperation with a plurality of computer apparatuses.
The calculation unit 1 includes an image analysis unit 1a, a camera control unit 1b, a detection information acquisition unit 1c, an operation determination unit 1d, an evaluation value calculation unit 1e, and an output control unit 1f as processing functions for this system. Each of these units is a block diagram of processing functions executed by software.

The image analysis unit 1a performs a process of analyzing each frame data as captured image data supplied from the imaging unit 20.
In the case of this example, the worker is mainly detected as a simplified model that is simplified based on information about detection points such as joints and lines connecting the detection points.
FIG. 2 shows an example of a simple model. Detection points P are set for various parts of the human body. In the figure, detection points P0 to P20 are shown as an example. For example, a detection point P is a place that is displaced mainly according to the posture, such as a waist, a head, a neck, and joint portions of limbs.
Each detection point P is connected to another specific detection point P by a line.
For example, the detection point P1 is connected to the detection points P2, P3, and P6 by lines.
The detection point P2 is connected to the detection point P1 only by a line.
The detection point P3 is connected to the detection points P1 and P4 by a line.
As described above, each of the detection points P1 to P20 defines a detection point that is connected by a line, thereby forming a simple model that represents the human body by the point and the line.

  FIG. 3 shows an example in which the posture of the worker is represented by a simple model. 3A is an XY plane, FIG. 3B is a ZY plane, and FIG. 3C is an XZ plane, showing the position of each detection point, and showing a line between the detection points. That is, by detecting the three-dimensional coordinate position for each of the detection points P0 to P20, the posture of the worker at that time can be detected.

In order to detect the posture of the worker using such a simple model, the image analysis unit 1a in FIG. 1 detects the positions (x, y, and z three-dimensional coordinate values of the detection points P0 to P20 from the worker's image. ) Is detected.
In order to accurately detect the worker's body from the captured image data, it is preferable to register the colors of the work clothes (uniforms) and hats in advance so that they can be clearly distinguished from the colors of the factory equipment and products. It is.
Alternatively, it may be possible to determine each detection point P in the human body constituent part by pattern matching.
Further, when the operator attaches the sensor 20 to the wrist, ankle or the like so that the position information thereof can be detected, the three-dimensional position information of the detection point P extracted from the captured image data is used as the position information by the sensor 20. It is possible to correct it.

The camera control unit 1b controls the driving unit 11 to displace the imaging direction of the imaging unit 10. For example, a worker who is working on a process moves the position for the work. The camera control unit 1b performs control so that the follow-up operation of the imaging unit 10 is performed so that the worker does not frame out of the captured image data due to such movement of the worker.
Specifically, the drive unit 11 is driven in accordance with the movement of the worker position recognized by the image analysis unit 1a (change in worker position in each frame).

  At each time point, the detection information acquisition unit 1c is a simple model of detection points P corresponding to a plurality of body parts of the worker who performs the measurement target work and lines connecting the detection points P. Get physical condition information. That is, the detection result of the image analysis unit 1a or the detection value by the sensor 20 is acquired and managed as worker information. Specifically, three-dimensional position information of each detection point P0 to P20 is acquired at each measurement timing and stored as a detection result.

FIG. 4A shows an example of worker information acquired and stored by the detection information acquisition unit 1c.
For example, the image analysis unit 1a detects each of the detection points P0 to P (n) (n = 20 in the example of FIG. 2) at a sample timing t (t0, t1, t2,...) That is a predetermined frame interval of the captured image data. Suppose that three-dimensional position information is detected. The detection information acquisition unit 1c acquires the three-dimensional coordinate values of the detection points P0 to P (n) for each sample timing t and stores them. The information as shown in FIG. 4A is acquired for each process, for each worker, and stored and managed.
Here, one process includes one or a plurality of operations. The three-dimensional position information of the worker for each sample timing t may be stored in a subdivided unit of work instead of being stored for each process as shown in FIG. 4A.

For example, in the production line, there are processes A, B, C,..., And one worker is in charge of one process. For example, it is assumed that the process A includes operations a1 to a5. As a specific example, for example, one process is a process of attaching a tire to a vehicle body, and each operation is an individual operation such as setting, mounting, and confirmation of a tire.
Assuming that the process A has five operations a1 to a5 as shown in FIG. 4B, the worker WM1 in charge repeats the process A (operations a1 to a5) for the vehicle body on the line. Become.
The three-dimensional position information of the detection points P0 to P20 as shown in FIG. 4A is acquired and stored at each sample timing t, so that the three-dimensional position information of the detection points P0 to P20 in the repeated process is time-series. It will be collected above.
In FIG. 4B, one time of the process A is completed at the sample timings t0 to t99 and t100 to t199, but this is only an example for explanation. For example, even when the same worker performs the same process, it is not always completed in the same time every time. Which sample timing t the information as each operation a1 to a5 in the process A is can be determined by the posture determined by each three-dimensional coordinate value, a change in posture, a change in motion, or the like.

  The motion determination unit 1d determines the posture or motion of the worker based on a change in the detection point P or line in the body state obtained by the detection information acquisition unit 1c. The change of the detection point P or line is represented by the change of the three-dimensional coordinate value of the detection points P0 to P (n) acquired as shown in FIG. 4A. In FIG. 4A, the information on the detection points P is stored. However, since the information on the lines connects the detection points P, the information on the lines can be grasped from the detection points P. Then, the motion determination unit 1d determines the posture and motion of the worker based on the time series change of the information in FIG. 4A.

The evaluation value calculation unit 1e calculates an evaluation value for the worker's work (work to be measured) based on the worker's physical condition information obtained by the detection information acquisition unit 1c. Specifically, the evaluation value calculation unit 1e in this example calculates a work burden value based on the posture or movement of the worker determined by the movement determination unit 1d as the evaluation value.
The burden value can be calculated in advance for human postures and movements ergonomically. For example, the burden values for the burden of the posture in which both hands are raised, the burden of the squatting posture, the posture of bending down, the lateral movement operation, the motion of twisting the body, and the like can be calculated in advance. Although the burden varies depending on the duration of each posture and operation, a burden value corresponding to the duration can be set in advance. For example, the posture of raising both hands is not so burdened for a moment, but it is considerably burdensome when it is continuously raised.
These postures and movements, and the burden values according to the time are calculated in advance according to ergonomics, systematized, and registered in the database unit 2.
Then, the evaluation value calculation unit 1e calculates a work load value for each work in the process or the process based on a series of actions and postures of the worker in the process and each work determined by the motion determination unit 1d and the duration thereof. calculate. For example, a burden value for the motion or posture determined from the detection point P or the amount of movement of the line, its duration, etc. is obtained, and these are added or weighted and added to obtain a series of motions (postures) in the work or process. The work burden value is calculated. Specifically, for each of the determined posture during work, the angle of a joint such as an arm, and the amount of movement, a corresponding burden value is assigned from the registration information in the database unit 2 described above. The work burden value of the process is calculated.
Further, for example, it is possible to calculate the work burden value through to the end of the work, and to obtain the peak of fatigue and the influence degree (fatigue prediction) when the work is extended.

For example, the evaluation value calculation unit 1e stores calculation values related to processes and operations as shown in FIG.
Various calculated values are assumed. For example, the calculated value MA1 for the process A may be the total burden value of the workload in the process A, MA2 may be the burden value for the shoulder of the worker, MA3 (not shown) may be the burden value for the legs, and the like.
Also, the calculated values for each work (for example, the calculated values Ma1-1, Ma2-2,... For the work a1) may be the total burden value, the burden value of each part, and the like.
The calculation example of the burden value (work load) about a process or a work is shown.

Here, Dis is a movement load in each joint 1 frame, Kdis is a weight of each joint movement amount with respect to the fatigue degree, Pos is a posture load, and Kpos is a weight of each joint angle with respect to the fatigue degree.
Dis is obtained by (Expression 2).

Here, X1, Y1, and Z1 are the coordinates of each joint, and X0, Y0, and Z0 are the coordinates of one frame before each joint.
Pos is obtained by, for example, (Equation 3).

Where U is the weight of the body above each joint, Ku is the weight of the body weight above each joint with respect to the work load, F is the total external force set for each process, and Kf is the external force above each joint with respect to the work load. Weight, θ is a calculated angle of each joint, and P is a constant indicating the posture of a human being.
The above calculation example of the burden value (work load) is only an example.

The output control unit 1f performs control for presenting work load evaluation information in the process to be measured based on the calculation result of the evaluation value calculation unit 1e. That is, work load evaluation information is generated, and the work load evaluation information is stored in the storage unit 3, displayed on the display unit 4, transmitted to an external device through the communication unit 5, or printed out by the printing unit 6. Perform control processing.
In particular, the output control unit 1f in the present embodiment performs a knitting simulation for obtaining a plurality of process knittings with different knitting contents for a group of processes to be knitted, and the work load for each process knitting obtained by the knitting simulation. Based on the value (evaluation value), one or a plurality of process organizations are selected from among a plurality of process organizations, and control for presenting information on the selected process organizations is performed. This will be described later.

The database unit 2 stores, for example, a burden value for each posture and motion as described above, and the calculation unit 1 can be referred to sequentially for calculation of a work burden value.
The storage unit 3 stores detection information as shown in FIG. 4A and information of calculated values as shown in FIG. In addition, a program for the calculation unit 1 to execute the above functions is stored.
The display unit 4 is a display device connected to the calculation unit 1 and displays various user interface images and images indicating work load evaluation information.
The communication unit 5 performs communication with an external device by wire or wireless, or performs communication via a communication path such as a LAN (Local Area Network). The computing unit 1 can provide, for example, work load evaluation information to another information processing apparatus or the like through the communication unit 5.
The printing unit 6 is a printer or the like connected to the calculation unit 1 and performs a printing operation in accordance with an instruction from the calculation unit 1.

<Processing procedure>
The processing procedure of the calculation unit 1 will be described with reference to FIG. The calculation unit 1 executes the following processing using the functions (1a to 1f) shown in FIG.
FIG. 6A shows a process of measuring a workload for one process executed by one worker. When performing the knitting simulation of this example, which will be described later, the calculation unit 1 performs the process of FIG. 6A for each process in a group of processes to be knitted (a group of processes constituting the production line). Specifically, assuming the composition simulation of this example, each of a plurality of workers is caused to execute a group of processes to be organized. In this case, the process shown in FIG. This is executed for each process in the group of processes executed by the person. For example, in a case where two workers, A and B, each execute a group of processes, the process shown in FIG. 6A is performed for each group of processes performed by the worker A, and the worker B executes The process shown in FIG. 6A is performed for each group of processes. In addition, when making a some worker perform a process in this way, the several computer apparatus provided for every worker may each perform the process shown to FIG. 6A in parallel.

  In FIG. 6A, the calculation unit 1 reads basic information in step S101. For example, the process number, information on the work in the process, information on the worker, various parameter settings in the measurement, and the like are read according to the operation or automatic setting by the operator.

In step S102, the calculation unit 1 starts imaging and / or sensing. That is, the capturing of captured image data from the imaging unit 10 is started. Also, the capturing of the detection value of the sensor 20 is started.
In step S103, the calculation unit 1 performs worker recognition. That is, the operator is recognized by image analysis of the captured image data that has been started. For example, a person wearing work clothes of a specific color is recognized as a worker, and the body position of the worker is grasped.
In step S104, the calculation unit 1 starts worker tracking. That is, the tracking control for controlling the drive unit 11 is started so that the worker recognized on the image does not go out of the frame.

In step S105, the calculation unit 1 stands by for the start of measurement. That is, the worker waits for a trigger to start measurement as soon as the actual process operation starts. The trigger may be an operator instruction, a specific time, or a synchronization signal from the production line management system.
In response to the measurement start trigger, operation unit 1 proceeds to step S106.

In step S106, the calculation unit 1 acquires measurement data. That is, the function of the detection information acquisition unit 1c acquires the analysis result of the image analysis unit 1a and the information from the sensor 20, and stores and manages the information as, for example, information of one sample timing t (x) in FIG. 4A.
In step S107, the calculation unit 1 performs posture data modeling. That is, by the function of the motion determination unit 1d, the posture and motion of the worker are determined from the simple model of the worker expressed by the three-dimensional coordinate value of each detection point P acquired in step S106.
In step S <b> 108, the calculation unit 1 performs a work burden numerical value. That is, the calculation unit 1 calculates various work loads by the function of the evaluation value calculation unit 1e and stores the calculated values.
The processes in steps S106 to S108 are repeated until it is determined in step S109 that the measurement is finished.
During this time, the calculated values in step S108 may be stored as data as shown in FIG. 5 at each time point, or the data as shown in FIG. 5 is updated as an integrated value of the calculated values at each sample timing t. You may do it.

After the measurement is completed, the calculation unit 1 generates burden evaluation information in step S110, and displays the burden evaluation information on the display unit 4 in step S111.
Thereby, burden evaluation information related to the burden on the worker is generated and displayed for a certain process executed by a certain worker.

<Presentation of workload evaluation information>
Here, for example, when the measurement process of FIG. 6A (the process up to S109) is performed for each process of the production line in the span of one day, it becomes possible to generate the burden evaluation information related to the burden on the worker of the day.
Here, a specific example of work load evaluation information will be described.

FIG. 7A is an example in which the work burden calculated for each process is quantified. For example, the work burden values at each sample timing t are integrated for each process, and the value of the burden given to the worker by working for one day is obtained and presented so that the processes can be compared.
For one process, the worker's physical condition at each sample timing t can be acquired in step S106 as shown in FIG. 4A, for example, and the burden value is calculated for each unit period in steps S107 and S108. If these burden values are integrated and held until the end of measurement, the calculated values (for example, MA1, MA2,...) Held in each step as shown in FIG. Value. For example, it becomes the burden value of the process in the day work. Therefore, by collecting the integrated values obtained in this way for each process and using it as burden evaluation information, it is possible to display as shown in FIG. 7A.

FIG. 7B is an example in which the work load calculated for each work in a certain process is quantified. For example, for each work in one process, the work burden values at each sample timing t are integrated, the value of the burden given to the worker in one day's work is obtained, and presented so that the work can be compared.
The degree of burden of each work can be seen in one process.
For each work in the process, if an operation pattern or the like by each work is registered in advance, it is possible to determine which work is being performed during the period of each sample timing t by image analysis. Therefore, the calculation of the burden value in step S108 can be executed separately for each work unit, and if the calculated values for each work are integrated, the stored calculated value is the process from the start to the end of the measurement. It becomes the burden value of. For example, the calculated values Ma1-1, Ma2-1... Ma5-1) in FIG. 5 are the burden values of the operations a1 to a5 in the process A from the start to the end of measurement. For example, it becomes a burden value of each work in a day work. Therefore, by collecting the integrated values obtained in this way for each process and using it as load evaluation information, a display as shown in FIG. 7B can be performed.

FIG. 7C is an example in which the momentum load and the posture load are obtained and presented for each part of the body regarding a certain process or work. From such information, it is possible to know where the load is applied to the worker in the process or operation.
The burden value itself relating to each part of the body can be processed to be acquired from, for example, the database unit 2 by determining posture and movement, for example. For example, when a certain posture is determined in step S107, the burden value of the right hand, the burden value of the left hand, the burden value of the waist, the burden value of the right foot, the burden value of the left foot, and the like are acquired from the database unit 2. In step S108, the burden value of each unit may be integrated during the period from the start to the end of measurement. Then, the burden value of each part of the body is obtained at the end of measurement. By collecting such integrated values as the load evaluation information, a display as shown in FIG. 7C can be performed.

FIG. 8A is an example in which a burden value is displayed for each detection point P0 to P20 regarding a certain process or operation. As in the case of FIG. 7C, the burden value is accumulated for each of the detection points P0 to P20 set corresponding to the posture and movement, for example, the burden value of each of the detection points P0 to P20 in the day work. Can be calculated. By collecting such integrated values as the burden evaluation information, a display as shown in FIG. 8A can be performed.
With such information, an administrator, a line engineer, or the like can know in more detail where the load is applied to the worker in the process or operation.

FIG. 8B is an example of presenting information that can be compared for each worker regarding a certain process (or work). By associating the detection information as shown in FIG. 4A with the worker code, for example, for one process, the burden value and the required time can be obtained for each worker. The required time can be measured by the posture / motion determined at each sample timing t. For example, since the start / end of each work and the start / end timing of the process can be determined from the posture and the operation, the time required for the process and the time required for the work can be calculated by the number of sample timings during that time.
Therefore, burden evaluation information that can compare the burden values for each worker for the same process or work is generated and displayed as shown in the figure. As a result, the manager can determine the characteristics of each process and work using the burden value for each worker as an index, for example, characteristics such as proficiency and orientation / non-suitability.

  FIGS. 7 and 8 are examples of the burden evaluation information. Various other information presentations can be considered. In any case, since the burden value is calculated by determining the posture and motion of each worker in the process and work, various burden evaluation information can be generated and displayed based on the information. it can. For example, it is possible to present a burden value for each time zone, and to present a predicted burden value when the work is extended.

<Selection of knitting simulation and optimum process knitting>
Next, the process for selecting the knitting simulation and the optimum process knitting shown in FIG. 6B will be described.
As described above, when performing the knitting simulation of this example, each of a plurality of workers is caused to execute a group of processes to be knitted, and each of the steps in the group of processes performed by the workers of each individual is illustrated. By executing the process shown in 6A, the work burden value for each process in the group of processes is obtained for each worker.

FIG. 9 shows an example of the work burden value obtained for each worker who has executed each group of processes in this way. In the figure, for each worker and process obtained when n (natural number of 2 or more) workers (workers WM1 to WMn) execute a group of processes (process A to process N) to be organized. The work burden value is illustrated. Here, for simplification of explanation, it is assumed that each of the processes A to N is composed of operations 1 to x. The work burden value in the work unit in each of these processes is obtained for each worker. In the example of FIG. 9, as shown as “total” in the figure, a total work load value (total value of work load values of each work in the process) for each process is calculated for each worker. It is supposed to be.
The calculation unit 1 stores information on the work burden value for each worker and each process obtained as illustrated in FIG. 9 in, for example, the storage unit 3.

Further, in this example, the calculation unit 1 calculates the time required for the work of each individual worker when each of the plurality of workers performs a group of processes to be organized, and stores it in the storage unit 3. .
FIG. 10 shows an example of the required work time calculated for each worker who has executed each group of processes. In this example, the time required for each work is calculated as the work required time. In this example, the total work required time for each process is calculated as the work required time. As shown in FIG. 10, the calculation unit 1 stores information on the required work time calculated for each worker and each process in the storage unit 3.

Based on the above assumptions, the process shown in FIG. 6B will be described.
In step S201, the calculation unit 1 executes a process organization simulation process. Specifically, in this example, the work is rearranged between a group of processes executed by a plurality of workers as the workers WM1 to WMn to obtain a plurality of process compositions having different composition contents. For example, as a recombination method, based on a group of processes executed by the worker MW1, the work of the process B is recombined with the work of the process B by the worker WM2, and the work of the process D is performed by the worker WM3. Etc. As can be understood from this point, depending on the composition simulation of this example, recombination of personnel may occur as the work is recombined.
At this time, the work is rearranged according to a predetermined work order condition. In a series of processes in a production line, for example, it is appropriate that a certain work and a certain work are performed in order by the same person, that a certain work may be incorporated into the next process, or the characteristics of each work are is there. These are conditioned in advance and stored in the database unit 2. The calculation unit 1 confirms such work order conditions for each work, and performs work reassignment simulation within a range satisfying the work order conditions.

  By performing such a process organization simulation, a work burden value and a work required time for each process organization can be obtained for a plurality of process organizations having different composition contents.

  In subsequent step S202, the calculation unit 1 executes an optimum process composition selection process. That is, the calculation unit 1 selects a knitting process that is optimum from among the plurality of process knittings based on the work burden value and the work required time for each of the plurality of process knittings obtained by the simulation process in step S201. select. Specifically, the calculation unit 1 calculates, for example, the total value of the work burden value and the total value of the work required time for each process organization obtained by the simulation, and calculates the total value of these work load values and the work required time. The optimum process organization is selected based on the total value of. For example, a process organization that minimizes a value obtained by multiplying a total value of work burden values by a coefficient corresponding to the total value of work required time (hereinafter referred to as “total evaluation value”) is selected as the optimum process organization. . In this case, if there are multiple process organizations that minimize the overall evaluation value, among them, for example, the process organization that has the smallest total work burden value or total work time required is optimal. What is necessary is just to select as process organization. If the total value of work burden values and the total value of required work time are the same among a plurality of process schedules that minimize the overall evaluation value, for example, the plurality of process schedules are selected as the optimum process schedule.

Note that the above-described method for selecting the optimum process organization is merely an example, and various other methods are conceivable. For example, on the basis of selecting the process organization that minimizes the total value of the work burden values as the optimum process organization, when there are a plurality of corresponding process organizations, the total value of the work required time among these process organizations is It is also possible to adopt a method of selecting the smallest process organization as the optimum process organization.
In selecting the optimum process organization, it is not essential to use the work required time as a selection criterion.
In any case, the optimum process composition selection process in this case may be performed so that at least a process composition with a small work load is selected preferentially.

  In response to the execution of the selection process in step S202, the calculation unit 1 causes the display unit 4 to display information on the optimum process composition in step S203, and ends the process illustrated in FIG. 6B.

FIG. 11 shows an information display example of the optimum process organization.
As shown in the figure, as the information of the optimum process organization, at least a process order for a group of processes, a work order in each process, and information on an operator who performs each work are displayed. In other words, at least information for specifying the process organization is displayed. In this example, in addition to these pieces of information, worker assignment information in work units, work load values and work time information in work units, work load values in process units ("process load values in the figure" )) And work required time ("process required time" in the figure), as well as the total work burden value ("total load value" in the figure) and the total work required time ("total" in the figure) for a group of processes. Time required)) information is also displayed.

  6B, information on the optimum process organization may be stored in the storage unit 3, printed out by the printing unit 6, or transmitted to an external device by the communication unit 5 in step S202. Good.

<Another example of selection of knitting simulation and optimum process knitting>
Here, the case where the work burden value is used as an evaluation value as an index when selecting the optimum process composition is taken as an example, but an adaptive value for the work is calculated for each worker, and the optimal value is used as an index. It is also possible to select a process organization.

In this case, the evaluation value calculation unit 1e shown in FIG. 1 compares the information about the detection points or lines obtained by the detection information acquisition unit 1c with the reference information set for the work to be measured, and An adaptive value for the work is calculated.
For example, in each operation of one process, for example, an ideal posture or motion is used as a reference, and the position of each detection point P (P0 to P20) or time-series change in the reference posture or motion is digitized in advance. And stored in the database unit 2. For example, it is also possible to take an image of the process work of a skilled worker, acquire the position and change of each detection point P1 to P20 at each time point as in FIG. 4A, and store it as reference information. Alternatively, an ergonomic analysis is used to set a posture or action that places the least burden on the person in the corresponding work, and the position and change of each point corresponding to each of the detection points P0 to P20 in that case are used as reference information. You may remember.
In any case, by comparing such reference information with the detection information as shown in FIG. 4A, an adaptive value indicating whether or not the worker who is the detection target is suitable for the work is obtained. The adaptation value in this example is information obtained by quantifying whether or not the target worker is suitable for the target work. For example, the numerical value from “0” to “100” represents the adaptability.

  For the calculation of the adaptive value, for example, a difference from the reference information for each of the detection points P0 to P20 at each time point is obtained, and an operation is performed so that the larger the difference is, the value that is not suitable for the work. . It is also conceivable to compare the movement trajectory and movement time of each detection point P0 to P20 in time series with the reference information, analyze the smoothness of the operation, the operation efficiency, etc., and digitize it. In any case, an operation is performed to obtain a value such that the closer to the reference information, the more adaptable (for example, adaptive value = 100), and the more the difference from the reference information, the less adaptable (for example, adaptive value = 0). .

  FIG. 12 shows a process to be executed when selecting an optimal process composition using an adaptive value as an evaluation value. In addition, about the process which becomes the content similar to the process already demonstrated so far, the same step number is attached | subjected and description is abbreviate | omitted. Also in the process shown in FIG. 12, as in the process shown in FIG. 6B, each of a plurality of workers is caused to execute a group of processes to be organized, and each of the processes in the group of processes executed by each of the workers is performed. It should be executed after the process shown in FIG. 6A is executed for the process.

  In this case, the calculation unit 1 executes the adaptability determination process in step S301, and then executes the process composition simulation process in step S201, the optimum process composition selection process in step S202, and the display process in step S203.

FIG. 13 shows an example of adaptability determination processing in step S301.
The calculation unit 1 performs the process of FIG. 13 for each worker who has executed a group of processes to be organized.
First, in step S401, the calculation unit 1 selects a target worker. In this example, a plurality of workers WM1 to WMn are made to perform a group of processes, respectively. First, for example, the worker WM1 is selected.
In subsequent step S402, the calculation unit 1 selects a work to be processed. In step S402, individual operations in the group of processes executed by the worker selected in step S401 are sequentially selected.

  In step S403, the calculation unit 1 extracts individual data of each part of the worker's body in the work selected as the processing target. For example, when the work a1 is selected, if the information of the sample timings t0 to t15, t100 to t115,... Is a sample for the work a1, as shown in FIG. The three-dimensional coordinate values of P0 to P (n) are extracted.

In step S404, the calculation unit 1 compares the extracted individual data with the corresponding data of the reference information set for the work a1.
For this reason, the calculation unit 1 acquires reference information regarding the work a1 of the process A from the database unit 2. For example, the three-dimensional coordinate values at each time point of the detection points P0 to P (n) serving as a reference as the work a1 are registered in the database unit 2. A difference value is obtained by comparing such reference information with individual data of each part of the body of the subject worker.
In step S405, the calculation unit 1 performs calculation using the difference value, and calculates an adaptive value indicating the adaptability of the worker to the work (for example, work a1).
That the difference value is small means that the difference in posture and movement of the worker is small compared to the reference information, and there is little useless movement during work. Conversely, a large difference value means that there are many useless movements.
For example, the adaptive value is obtained by performing a predetermined calculation such as integration of the difference values of each sample timing, selection / weighting of information of the main detection points P, displacement time of each detection point P, and the like. This adaptive value is set to a value indicating whether the posture or motion of the target worker is similar to or different from the reference posture or motion.
Further, according to the information as shown in FIG. 4A, it is possible to determine the time required for one operation and one operation. Therefore, it is also effective to obtain the adaptive value using a coefficient corresponding to the required time.

  In step S406, the calculation unit 1 determines whether or not there is an unprocessed work among the work performed by the target worker, and if there is an unprocessed work, the process returns to step S402. As a result, the processes in steps S403 to S405 are performed for all the work performed by the target worker, and an adaptive value for each work of the worker is obtained.

  After obtaining the adaptive value for each work, the calculation unit 1 proceeds from step S406 to S407, determines whether there is an unprocessed worker, and returns to step S401 if there is an unprocessed worker. As a result, the processes in steps S402 to S405 are performed for each of the workers WM1 to WMn, and an adaptive value for each work is obtained for each of the workers WM1 to WMn.

  FIG. 14 shows an example of the adaptive value for each worker and process calculated in the process of FIG. In this case, the calculation unit 1 causes the storage unit 3 to store information on adaptive values for each worker / process obtained as shown in FIG.

In FIG. 12, when the process composition simulation in step S201 is performed, an adaptive value for each process composition is obtained for a plurality of process compositions having different composition contents.
In the optimum process composition selection process of step S202 in this case, the calculation unit 1 is the process that is optimized from among the plurality of process compositions based on the adaptive value for each of the plurality of process compositions obtained by the simulation of step S201. Select an organization. For example, the total value of the adaptation values is calculated for each process organization obtained by the simulation process, and the process organization that maximizes the total value is selected as the optimum process organization (as described above, the more adaptive the adaptation is (Assuming that the value will increase).
In this case, the optimum process composition selection process may be performed so that at least a process composition that is highly adaptable to work is preferentially selected.
In this case as well, the time required for the work can be taken into consideration when selecting the optimum process organization.

  In this case, as the information displayed in the display process in step S203, for example, the work unit, the process unit, and the total “burden value” in the information shown in FIG. 11 are replaced with “adaptive values” in the corresponding units. Information can be used.

  Note that the selection of the optimum process organization can be performed based on both the adaptive value and the work burden value. As an example, for example, a total value of adaptation values and a total value of work burden values are calculated for each of a plurality of process organizations obtained by the process organization simulation in step S201, and the sum of adaptation values is calculated for each of these plurality of process organizations. A method of calculating a comprehensive evaluation value obtained by multiplying the value by a coefficient corresponding to the total value of the work burden values and selecting a process composition that maximizes the comprehensive evaluation value as the optimum process composition can be given.

<Another example of selection of knitting simulation and optimum process knitting>
In the above, as the selection of the process organization based on the work burden value, it is mentioned that the process organization is selected using the small work burden value as an index. An example is proposed. Specifically, the optimum process knitting is selected on the basis of leveling (equalizing) the work load for each process for a group of processes to be knitted.

An example of leveling will be described with reference to FIG.
FIG. 15A is an example of burden evaluation information that is a premise of leveling. First, the leveling of this example is based on the premise of obtaining a work burden value for each work constituting a group of processes to be organized. FIG. 15A shows an example in which a work load value is obtained for each work constituting the group of processes when the group of processes to be organized includes the processes A to E. Note that “overall” in the figure also means a work burden value for each process.
The work burden value of each work in such a group of processes may be obtained by causing a single worker to execute the group of processes, or the work constituting the group of processes may be a predetermined value such as for each process. It may be obtained by dividing the operation unit into a plurality of work units and sharing them with each other for execution (for example, in the case of FIG. 15A, one process corresponding to each of five workers in the case of sharing each process) To execute).
The work burden value for each process in the group of processes as shown in FIG. 15A is obtained, for example, by executing the process shown in FIG. 6A for each process in the group of processes.

  In the example shown in FIG. 15A, the burden values of the process A and the process E surrounded by a thick frame in the drawing are almost equal to “251” and “257”, respectively. Other processes B and C have a relatively large burden, and process D has a relatively small burden.

FIG. 15B shows an example of leveling the work load for a group of processes by the knitting shown in FIG. 15A.
For leveling, set an equal range of work burden. For example, an average value of burden values of each process is obtained, and a range of ± α centered on the average value is set as an equal range. Speaking in accordance with the numerical example of FIG. 15, the average value of the work burden values for the processes A to E is “260”. For example, when α = 10, “250” to “270” are set to an equal range. This is a range setting in which each process becomes an almost equal load for the operator if the burden value of each process is within an equal range.
In leveling, the goal is to have work burden values for the most processes, preferably all processes, within an equal range. FIG. 15B shows an example in which the process b to the process E are all within the equal range “250” to “270” by incorporating the work b1 in the process organization of FIG. 15A into the process A and the work c4 into the process D. It is shown. Thereby, all the burden of process A-process E is made substantially equal.

In this case, the calculation unit 1 executes the following processing based on the work load values obtained for the group of processes as shown in FIG. 15A in order to derive the above-described leveled optimum process organization. To do.
In this case, the calculation unit 1 performs the process composition simulation process in step S201, the optimum process composition selection process in step S202, and the display process in step S203, as in the case shown in FIG. 6B. In this case, in the process composition simulation process of step S201, the work is rearranged for a group of processes within a range satisfying the above-described work order condition, and a plurality of process compositions having different composition contents are obtained.
In the optimum process composition selection process of step S202, the number of processes in which the work burden value is within the above-described equal range is calculated for each of the plurality of process compositions obtained by the simulation process of step S201. The process organization with the largest number is selected as the optimum process organization. In this case, when there are a plurality of corresponding process organizations, the plurality of process organizations may be selected as the optimum process organization.

  With the above-described processing, it is possible to derive a process organization in which the work load is leveled while eliminating the need for the worker to actually perform work on a plurality of possible process organizations. The organization can be presented to personnel such as production line managers or line design engineers.

<Summary>
As described above, the process organization support device (calculation unit 1) as an embodiment is a process organization support device that assists in the organization of a process including one or a plurality of operations, and for an operator who performs a work to be measured. A detection information acquisition unit (1c) that acquires information on the physical state of the worker at each time point in a state that is simply modeled by detection points corresponding to a plurality of body parts and lines connecting the detection points; and detection information Based on the information obtained by the acquisition unit, an evaluation value calculation unit (1e) that calculates an evaluation value for an operator's work, and a knitting simulation that obtains a plurality of process knittings with different knitting contents for a group of processes to be knitted Based on the evaluation value for each process composition obtained by the composition simulation, selecting one or a plurality of process compositions from the plurality of process compositions and presenting information on the selected process composition. Output control unit for performing and a (same 1f).

That is, the worker's body state is detected by a simple model, and the operator's movement can be grasped by the detection point and the position or change (movement vector) of the detection point or line for each body part, for example, a joint. Then, based on the information on the detection points or lines, that is, on individual data such as each part of the body (arms, waist, legs), an evaluation value for the work of the operator is calculated, and the composition contents are different based on the evaluation value. Control is performed in which one or a plurality of process organizations are selected from the selected plurality of process organizations and information on the selected process organizations is presented. At this time, since the evaluation value is calculated based on the actual measurement data on the worker's physical condition, an objective and quantitative value can be obtained. In addition, since the evaluation value for each of the plurality of process formations is obtained by the formation simulation, the burden of causing the worker to actually perform the work for the plurality of process formations that can be assumed is unnecessary.
Therefore, according to the process organization support device as the above-described embodiment, efficient process organization derivation can be realized while accurately and reducing the burden on personnel relating to organization.

  As described above, simplified data using detection points and lines corresponding to a plurality of body parts is used as information on the worker's physical state, thereby facilitating processing and a relatively small-scale computing system. Can be realized.

In addition, the process organization support apparatus as the embodiment includes an operation determination unit (1d) that determines the posture or motion of the worker based on a change in the detection point or line in the information obtained by the detection information acquisition unit, and the evaluation value The calculation unit obtains, as an evaluation value, a work burden value calculated based on the posture or motion of the worker determined by the motion determination unit.
Thereby, in the knitting simulation, a work burden value for each process knitting having different knitting contents is obtained, and one or a plurality of process knittings are selected based on the work burden value.
Therefore, it is possible to derive a process organization that is efficient in terms of work load.

In the process organization support device as an embodiment, the evaluation value calculation unit compares the information about the detection point or line in the information obtained by the detection information acquisition unit with the reference information set for the work to be measured. An adaptive value for the work of the worker is calculated, and the adaptive value is obtained as an evaluation value.
Thereby, in the knitting simulation, an adaptive value for each process knitting having different knitting contents is obtained, and one or a plurality of process knittings are selected based on the adaptive value.
Accordingly, it is possible to derive a process organization that is efficient in terms of adaptability to the worker's work, such as the poorness of the worker and the orientation / unsuitability.

Further, in the process organization support apparatus as the embodiment, the evaluation value calculation unit calculates an evaluation value for each worker when a plurality of workers are each executed a group of processes, and the output control unit As a simulation, a simulation is performed in which work is rearranged between a group of processes executed by a plurality of workers, and one or a plurality of process organization is selected based on an evaluation value for each process organization obtained by the organization simulation. .
This makes it possible to derive an efficient process organization including the organization of personnel as workers.

Furthermore, the process organization support apparatus as an embodiment includes a required time acquisition unit that acquires the work required time of the worker, and the output control unit includes an evaluation value and an operation required time for each process organization obtained by the knitting simulation. Based on the above, one or a plurality of process arrangements are selected.
Thereby, the process organization can be derived in consideration of the length of time required for the work.

Moreover, in the process organization assistance apparatus as an embodiment, the detection information acquisition unit acquires the three-dimensional positions of a plurality of detection points from the analysis result of image data obtained by imaging the worker.
That is, an operator is imaged with a camera, and converted into simplified data into a plurality of points mainly imitating joints of humans to be imaged and lines connecting them. The calculation unit 1 is a system that identifies human movement from the detection result of such a point or line movement vector.
If the worker is imaged and the captured image is analyzed as described above, the three-dimensional position of the worker's detection point can be specified.
Further, in this case, the operator can eliminate the need to wear a sensor or the like on the body, and can prevent a sense of incongruity or deterioration of workability due to the wearing of the sensor.

  In the embodiment, the burden evaluation information is displayed after the measurement is completed. However, for example, the burden value of each process or operation may be displayed in real time during the measurement. Then, it is possible to find a worker with a heavy load during the work, or to perform a personnel rearrangement accordingly. Furthermore, it is possible to cope with a case where the burden value of work increases according to mixed flow production or quality conditions. For example, there are cases where the production load changes during the day, the quality changes depending on the situation and environment of the day, and some modifications are made. is there.

  DESCRIPTION OF SYMBOLS 1 ... Operation part, 1a ... Image analysis part, 1b ... Camera control part, 1c ... Detection information acquisition part, 1d ... Motion determination part, 1e ... Evaluation value calculation part, 1f ... Output control part, 1g ... Adaptive value calculation part, 2 ... Database unit, 3 ... Storage unit, 4 ... Display unit, 5 ... Communication unit, 6 ... Printing unit, 10 ... Imaging unit, 20 ... Sensor

Claims (7)

A process organization support apparatus for assisting in organization of a process including one or a plurality of operations,
With respect to the worker who performs the work to be measured, information on the physical state of the worker at each time point is obtained in a simple model with detection points corresponding to a plurality of body parts and lines connecting the detection points. A detection information acquisition unit;
An evaluation value calculation unit that calculates an evaluation value for the work of the worker based on information obtained by the detection information acquisition unit;
A knitting simulation is performed to obtain a plurality of process knittings with different knitting contents for a group of processes to be knitted, and one of the plurality of process knittings is determined based on the evaluation value for each process knitting obtained by the knitting simulation. Or an output control unit that performs control for selecting a plurality of process organizations and presenting information on the selected process organizations. An operation determination unit that determines the posture or operation of an operator based on a change in the detection point or line in the information obtained by the detection information acquisition unit;
The evaluation value calculation unit
The process scheduling support device according to claim 1, wherein a work burden value calculated based on the posture or motion of the worker determined by the motion determination unit is obtained as the evaluation value. The evaluation value calculation unit
The information about the detection point or line in the information obtained by the detection information acquisition unit is compared with reference information set for the work to be measured to calculate an adaptive value for the work of the worker, and the adaptive value is The process organization support device according to claim 1, which is obtained as the evaluation value. The evaluation value calculation unit
Calculating the evaluation value for each of the workers when the plurality of workers are each performing the group of steps;
The output control unit
As the knitting simulation, a simulation of rearranging work between the group of processes executed by the plurality of workers is performed, and one or more process knitting is performed based on the evaluation value for each process knitting obtained by the knitting simulation. The process organization support device according to claim 1. A required time acquisition unit for acquiring the work required time of the worker;
The output control unit
The process organization support device according to claim 1, wherein one or a plurality of process organizations are selected based on the evaluation value and the work required time for each process organization obtained by the organization simulation. The process organization support device according to claim 1, wherein the detection information acquisition unit acquires a three-dimensional position of the plurality of detection points from an analysis result of image data obtained by imaging an operator. A process organization support method for assisting in organization of a process including one or a plurality of operations,
With respect to the worker who performs the work to be measured, information on the physical state of the worker at each time point is obtained in a simple model with detection points corresponding to a plurality of body parts and lines connecting the detection points. Detection information acquisition procedure;
An evaluation value calculation procedure for calculating an evaluation value for the work of the worker based on the information obtained in the detection information acquisition procedure;
A knitting simulation is performed to obtain a plurality of process knittings with different knitting contents for a group of processes to be knitted, and one of the plurality of process knittings is determined based on the evaluation value for each process knitting obtained by the knitting simulation. Or an output control procedure for performing control to select a plurality of process organization and present information of the selected process organization;
A process organization support method in which the information processing apparatus executes.

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