JP7684191B2 - Work plan update system and work plan update method - Google Patents

Description

The present invention relates to a work plan update system and a work plan update method.

In non-standard remote work that utilizes robots in unknown environments, workers operate the robots manually or automatically (semi-automatically). Work in unknown environments generally places a high mental burden on workers.

Patent document 1 describes an invention for a personnel management system that creates a personnel allocation plan that is expected to maximize work performance through teamwork. The invention described in patent document 1 assigns tasks to all personnel based on the difficulty of the tasks and the proficiency of the personnel, and provides a personnel allocation plan that is expected to maximize work performance through teamwork.

JP 2014-211766 A

In non-routine remote work using robots in unknown environments, the mental stress on the worker varies depending on the difficulty of the work, the time of day the work is being done, and the worker's own vital signs. In the event of an environmental change, such as a worker's poor health or a robot malfunction, if the work plan is updated by routinely reassigning the work to another worker or robot, this can lead to reduced work efficiency, incompatible tasks, and human error.
Therefore, an object of the present invention is to update a work plan robustly against environmental changes.

In order to solve the above-mentioned problems, the work plan updating system of the present invention comprises a data interface unit that acquires data related to each task included in a work plan from workers and robots at pre-specified time intervals; a task status processing unit that analyzes the vital signs of the worker or the movements of the robot from the data; and a task resource processing unit that, when a status abnormality is detected from the data acquired by the data interface unit or from data obtained by the work status processing unit analyzing the data, updates the allocation of workers and robots, who are resources required for subsequent tasks of the work plan , to the task, and the task resource processing unit compares the manual and automatic work efficiencies of other tasks similar to each of the tasks in the work plan after the status abnormality is detected from the data and stored in a database , and if the manual work efficiency of the other tasks is higher, designates a task classification for manual performance of each of the tasks, and if the automatic work efficiency of the other tasks is higher, updates the work plan by designating a task classification for automatic performance of each of the tasks.

The work plan updating method of the present invention executes the steps of: a data interface unit provided in a work plan updating system acquiring data related to each task included in a work plan from workers and robots at pre-specified time intervals; a task status processing unit provided in the work plan updating system analyzing the vital signs of the worker or the motion of the robot from the data; and a task resource processing unit provided in the work plan updating system , when detecting a status abnormality from the data acquired by the data interface unit or from data obtained by analyzing the data by the work status processing unit, updating the allocation of workers and robots, who are resources required for subsequent tasks of the work plan , to the corresponding tasks. The work resource processing unit compares the manual and automatic work efficiencies of other tasks similar to each of the tasks of the work plan after detecting a status abnormality from the data and stored in a database, and if the manual work efficiency of the other tasks is higher, designates a task classification for manual execution of each of the tasks, and if the automatic work efficiency of the other tasks is higher, updates the work plan by designating a task classification for automatic execution of each of the tasks .
Other means will be described in the description of the embodiment of the invention.

The present invention makes it possible to update work plans robustly in response to environmental changes.

1 is a configuration diagram of a work plan updating system according to a first embodiment. FIG. 2 is a configuration diagram of a work status processing device. 11 is a graph showing an example of data output from a working state measuring unit. 11 is a graph showing an example of data output from a robot state measuring unit. 13 is a graph showing an example of analysis data output. FIG. 2 is a configuration diagram of a work management database. FIG. 11 is a diagram illustrating an example of data in a work management database. FIG. 2 is a configuration diagram of a work resource processing device. FIG. 2 is a configuration diagram of a work instruction operating device. 13 is a flowchart showing a work plan update process. 13 is a flowchart showing a work plan update process. 13 is a flowchart showing a work resource allocation calculation process. FIG. 13 is a diagram illustrating an example of a step function in a working state. FIG. 13 is a diagram illustrating an example of a step function for a task attribute. 13 is a chart showing an example of updating a task resource allocation. 13 is a chart showing an example of updating a task resource allocation. 13 is a chart showing an example of updating a task resource allocation. FIG. 11 is a configuration diagram of a work plan updating system according to a second embodiment. 13 is a flowchart showing a work plan update process. 13 is a flowchart showing a work plan update process. 13 is a chart showing an example of updating a task resource allocation. 13 is a flowchart showing a work plan update process. 13 is a flowchart showing a work plan update process. 11 is a graph showing an example of data output from a working state measuring unit. 11 is a graph showing an example of data output from a robot state measuring unit. FIG. 2 is a configuration diagram of a work management database. FIG. 13 is a configuration diagram of a work plan updating system according to a third embodiment.

Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings.
FIG. 1 is a configuration diagram of a work plan updating system 1 according to the first embodiment.
The work plan updating system 1 includes a data interface unit 11, a work status processing device 12, a work management database 13, a work resource processing device 14, and a work instruction operating device 15. This work plan updating system 1 updates a work plan using workers 2a to 2c and a work robot system.

Here, workers 2a to 2c are robot operators, assistant workers, work supervisors, etc. Workers 2a to 2c have individual differences in ability, and there is variation in work processing ability. Even when the same worker performs the same work, there is variation in ability depending on their physical condition at the time. A work team is a team of multiple people who perform the same work together. It is advisable to organize a work team taking into account the differences in the initial abilities of individuals.

The data interface unit 11 is an interface for exchanging data between the workers 2a-2c and the work robot and the work plan updating system 1. The data interface unit 11 is configured, for example, to include a group of multiple types of sensors and a wireless router that transmits instructions to the worker's terminal and the robot. The data interface unit 11 issues work instructions to the workers 2a-2c and acquires vital sign data from the workers 2a-2c at pre-specified time intervals.

The working robot system consists of the robots 3a-3c, their control devices, operation log recording devices, operation devices, monitoring devices, and associated equipment. If the robots 3a-3c are the same, there is almost no variation in performance, and if they are performing the same work in the same environment, there is no variation in deterioration over time. The data interface unit 11 issues control instructions to the robots 3a-3c, and acquires operation log data from the robots 3a-3c at pre-specified time intervals.
That is, the data interface unit 11 acquires work-related data from the workers 2a to 2c and the robots 3a to 3c at pre-specified time intervals.

The work-related information 4 refers to information such as the layout of the work environment, temperature, humidity, hydrogen concentration, oxygen concentration, radiation dose, as well as the date, time, etc. The work-related information 4 is on-site data that measures the status of the workers 2a to 2c and the work robot system. The data interface unit 11 acquires this on-site data at pre-specified time intervals.

The work attribute information 5 is a history indicated by work results such as the work name, work purpose, work difficulty, work organization, worker proficiency, worker history, work process, work time period, work equipment specifications, work equipment history, work completion time, and work time for each work. The data interface unit 11 updates this history at pre-specified time intervals.

The work status processing device 12 analyzes the work status and work attributes using on-site data that measures the status of the workers 2a-2c and the robots 3a-3c, and stores this analysis data and on-site data in the work management database 13. The work status processing device 12 further outputs the analysis data to the work resource processing device 14. In other words, the work status processing device 12 functions as a work status processing unit that analyzes the data acquired by the data interface unit 11.

The work resource processing device 14 calculates the allocation of work resources based on the analysis data and history data. When it detects a state in which the data acquired by the work status processing device 12 exceeds a pre-specified threshold, the work resource processing device 14 calculates the allocation of resources required for this work. The work resource processing device 14 then stores the work resource calculation results in the work management database 13 and outputs them to the work instruction operation device 15.
In other words, the work resource processing device 14 functions as a work resource processing unit that calculates the allocation of resources required for work.

The work instruction operation device 15 outputs operation instruction data to the workers 2a to 2c and control data to the robots 3a to 3c based on the work resource calculation results.

The worker status refers to the vital data and movement data of workers 2a to 2c. Vital data includes heart rate, brain waves, sweat rate, body temperature, blood pressure, etc. Movement data includes acceleration, position, movement path/history, line of sight, number of steps, etc.

The robot status refers to the work operation log data and regular inspection data of the robots 3a to 3c. The work operation log data includes time trends of each joint operation (flow rate, pressure, camera footage, etc.), cumulative work time/system operation time, cumulative radiation dose, etc. The regular inspection data includes time trends of each joint operation (flow rate, pressure, camera footage, etc.) during specified operations, etc.

The work conditions include the date, time period, whether it is a weekday, Saturday, Sunday or holiday, working hours per day, total number of working days and cumulative number of working days, temperature and humidity in the work environment, structure layout, work environment images and point clouds, etc.
The work attributes include the work purpose, the work difficulty (risk level), the work urgency, the work team structure, the worker proficiency, and the work system.
The work results include whether the work was successful, the work time (including the degree of delay), the amount of radiation exposure and accumulated dose, whether a risk event occurred, and whether the plan was updated.

FIG. 2 is a configuration diagram of the work status processing device 12. As shown in FIG.
The work status processing device 12 includes a worker status measuring unit 121 , a robot status measuring unit 122 , a work status analysis and evaluation unit 123 , and a work attribute analysis and evaluation unit 124 .

The work status processing device 12 acquires data from equipment element tests, equipment combination tests, mock-up tests, training, actual equipment construction, etc.

The worker status measurement unit 121 measures the status of the workers 2a to 2c and outputs vital data and movement data. Here, vital data refers to the worker's heart rate, brain waves, amount of sweat, body temperature, blood pressure, physical condition, etc. Movement data refers to acceleration, position, movement path/history, line of sight, number of steps, etc.

3 is a graph showing an example of output data from the worker condition measuring unit 121. The vertical axis of the graph indicates the measured value, and the horizontal axis indicates time.
The solid line in the graph indicates acceleration, the dashed line in the graph indicates heart rate, and the dashed line in the graph indicates sweat rate.

Returning to Figure 2 for further explanation, the robot status measurement unit 122 measures the robots 3a to 3c and outputs work log data and regular inspection data. Work operation log data includes time trends of each joint operation (current, voltage, liquid flow rate and pressure, camera footage, etc.), cumulative work time/system operation time, cumulative radiation dose, etc. Regular inspection data includes time trends of each joint operation (current, voltage, liquid flow rate and pressure, camera footage, etc.) during specified operations.

4 is a graph showing an example of output data from the robot state measurement unit 122. The vertical axis of the graph indicates the measurement value, and the horizontal axis indicates time.
The solid line in the graph indicates the motion of joint 1. The dashed line in the graph indicates the motion of joint 2. The dashed and dotted line in the graph indicates the cumulative dose.

Figure 5 is a graph showing an example of analysis data output by the work status analysis evaluation unit 123. The vertical axis of the graph shows the value of the analysis data, and the horizontal axis shows time.

Returning to FIG. 2 for further explanation, the work status analysis evaluation unit 123 evaluates vital analysis data from the worker status, and evaluates robot operation analysis data from the robot status. Examples of vital analysis data include fatigue level, concentration level, happiness level, relaxation level, alertness level, and agitation level.

The robot motion analysis data refers to the frequency of robot motion calibration, the amount of unit calibration (correction), the robot motion instruction-motion result difference amount (space, time), and the like.
The variation due to each individual's physical condition is defined as the deviation from the standard value of the long-term data of each individual, and the variation of the robot's motion analysis data is defined as the deviation from the standard value of the long-term data of each robot.

FIG. 6 is a diagram showing the configuration of the work management database 13.
The work management database 13 includes a worker status record management unit 131, a robot status record management unit 132, a work status record management unit 133, a work attribute record management unit 134, and a work result record management unit 135. The work management database 13 stores the on-site data and analysis data shown in Figures 3 to 5, as well as associated data such as the processing conditions thereof.

The worker condition record management unit 131 stores the vital data and motion data of the workers 2 a to 2 c measured by the worker condition measurement unit 121 .
The robot state record management unit 132 stores the work log data and regular inspection data of the robots 3 a to 3 c measured by the robot state measurement unit 122 .

The work status record management unit 133 records and manages the status data of the work evaluated by the work status analysis evaluation unit 123 .
The work attribute record management unit 134 records and manages the attribute status of a work.
The work result record management unit 135 records and manages the results of the work.

FIG. 7 is a diagram showing an example of data in the work management database 13. As shown in FIG.
The work management database 13 includes a date column, a time column, a worker status column, a robot status column, a work attribute column, a work status column, and a work incidental information column. The worker status column includes a heart rate column, an acceleration column, etc. The robot status column includes a joint angle column.

FIG. 8 is a diagram showing the configuration of the work resource processing device 14. As shown in FIG.
The work resource processing device 14 includes a work resource allocation calculation unit 141 and a work resource allocation update unit 142. The work resource processing device 14 calculates the work resources based on the analysis data and the history data.

The work resource allocation calculation unit 141 calculates the allocation of the work resource based on the calculation result of the work resource. The work resource allocation update unit 142 updates the allocation of the work resource based on the allocation of the work resource calculated by the work resource allocation calculation unit 141.

FIG. 9 is a configuration diagram of the work instruction operating device 15. As shown in FIG.
The work instruction operation device 15 includes an operator procedure instruction unit 151 and a robot control operation unit 152 .

The worker procedure instruction unit 151 instructs the workers 2a to 2c on the work procedure. The robot control operation unit 152 outputs control instructions to the robots 3a to 3c to operate them.

10A and 10B are flowcharts showing the work plan update process according to the first embodiment.
First, the workers 2a to 2c operate the robots 3a to 3c to carry out work (step S10).

The work status processing device 12 measures the work status and analyzes and evaluates it (step S11). Specifically, the worker status measurement unit 121 of the work status processing device 12 measures the status of the worker, and the robot status measurement unit 122 measures the status of the robot. Then, the work status analysis and evaluation unit 123 analyzes and evaluates the work status, and the work attribute analysis and evaluation unit 124 analyzes and evaluates the work attributes.

Next, the work status processing device 12 records and manages the work status in the work management database 13 (step S12). The work status recorded in the work management database 13 is exemplified in the graphs of Figures 3 and 4.

Then, the work resource processing device 14 judges whether or not a plan update is necessary (step S13). Here, the work resource processing device 14 judges that a plan update is necessary when the data measured by the work status processing device 12 or the data obtained by analyzing the measured data exceeds a pre-specified threshold value.
If the plan update is necessary (Yes), the work resource processing device 14 proceeds to step S20 in FIG. 10B, and if the plan update is not necessary (No), the work resource processing device 14 proceeds to the process of step S14.

In step S14, the work status processing device 12 determines whether the work is complete. Here, the completion of the work is determined, for example, by whether the work supervisor has input that the work is complete. If the work is not complete (No), the work status processing device 12 returns to the processing of step S10, and if the work is complete (Yes), the processing of FIG. 10A ends.

In step S20, the work resource processing device 14 sets an objective function and constraint conditions. Next, the work resource processing device 14 searches for and extracts similar past tasks from the work management database 13 (step S21). Here, the work resource processing device 14 ranks similar past tasks using statistical methods such as machine learning algorithms and mathematical models, and extracts similar tasks with high ranking values and their work efficiency.

Then, the work resource processing device 14 calculates the allocation of work resources (step S22). Here, the allocation of work resources means the arrangement of resources required for work. Details of the processing of step S22 will be described later with reference to FIG. 11. In step S22, the work resource processing device 14 extracts, as resources, robots whose work efficiency in each work item exceeds a predetermined value. Note that the work resource processing device 14 may also extract, as resources, robots whose work efficiency in each work item exceeds a predetermined value in a plurality of works whose work continuity exceeds a predetermined value.
Next, the work resource processing device 14 determines whether or not the calculation of the corresponding work resource is completed (step S23).

In step S23, if the work resource calculation is not complete (No), the work resource processing device 14 returns to step S20, and if the work resource calculation is complete (Yes), the work resource processing device 14 proceeds to step S24.

In step S24, the work supervisor determines and inputs an update to this work based on the work resources calculated by the work resource processing device 14. In response to this determination, the work instruction operating device 15 updates the worker operation procedure and the robot control (step S25). As a result, the worker and the robot resume the work (step S26), and the process returns to step S10 in FIG. 10A.

FIG. 11 is a flowchart showing the task resource allocation calculation process shown in step S22 of FIG. 10B.
This task resource allocation calculation process is a method for searching and extracting similar tasks from the past, ranking similar tasks from the past using statistical methods such as machine learning algorithms and mathematical models, and extracting similar tasks with high ranking values and their task efficiency. This task resource allocation calculation process corresponds to the process of step S22 shown in FIG. 10B.

The work resource allocation calculation unit 141 calculates the work time for manual operation of a certain task, or extracts the calculation result (step S30). Extracting the calculation result here means, for example, extracting past calculation results stored in a database. The work resource allocation calculation unit 141 then calculates the work time for automatic (semi-automatic) operation of this task, or extracts the calculation result (step S31). The work resource allocation calculation unit 141 performs a comparative calculation between the calculation result for manual operation and the calculation result for automatic (semi-automatic) operation (step S32), and when a task classification is specified (step S33), the processing of FIG. 11 ends.

In other words, the work resource allocation calculation unit 141 compares the work efficiency of other tasks similar to a certain task between manual and automatic, and specifies the task classification of whether each task should be performed manually or automatically. Furthermore, when calculating the work efficiency of a certain task between manual and automatic, the work resource allocation calculation unit 141 weights the input values of the task state and task attributes with a coefficient. More specifically, this is explained using equations (1) to (3) below.

Note that the semi-automatic operation mentioned above refers to cases where some of the functions in the robot operation are automated.

In step S33, which specifies the task classification of each task based on the comparison result, the task resource allocation calculation unit 141 extracts the task with the highest task efficiency (e.g., robot operation means) for each task item and updates the task procedure. For example, the movement operation is set to automatic and the task arm operation is set to manual.

The following formula (1) is a basic formula for calculating the work efficiency ε _xn . The work efficiency ε _xn is calculated by dividing the work time t _xn in the selected operation mode by the work time t _mn in the manual mode. Here, since the work state at the time of work planning is the manual mode, the work efficiency ε _xn of the selected operation mode relative to the manual mode is calculated.

Equation (2) is obtained by weighting equation (1) with a coefficient α.

Equation (3) is a formula for calculating the coefficient α of equation (2). The coefficient α is calculated as the product of the task state function f(a) and the task attribute function f(b). When calculating the task efficiency when a certain task is performed manually and automatically, the task resource allocation calculation unit 141 weights the task efficiency with the task state coefficient and the task attribute coefficient.

Figure 12 shows an example of a step function in a working state. Here, coefficients for three steps are shown as an example. The vertical axis of the graph shows the value of the function f(a), and the horizontal axis shows the working state.

The first state is, for example, a state of low radiation dose relative to the reference, or a state in which the latest highly accurate layout has been acquired. In this case, the value of the function f(a) is 2.0.

The second state is, for example, the work state at the time of work planning. At this time, the value of the function f(a) is 1.0.
The third state is, for example, a state in which there are many layout differences or a state in which the radiation dose is high. In this case, the value of the function f(a) is 0.3.

Figure 13 shows an example of a step function for task attributes. Here, three step coefficients are shown as an example. The vertical axis of the graph shows the value of the function f(b), and the horizontal axis shows the task attributes.

The first attribute is, for example, an attribute of a low difficulty task, a highly skilled worker, or a highly maneuverable robot relative to the standard. In this case, the value of the function f(b) is 2.0.
The second attribute is, for example, the task state at the time of task planning or the task attribute at the time of similar tasks. In this case, the value of the function f(b) is 1.0.
The third state is, for example, an attribute of a highly difficult task, a low skilled worker, a low operability robot, or an attribute of a time period where human error occurs frequently, relative to the standard. In this case, the value of the function f(b) is 0.3.

In this embodiment, each function that calculates the change in work efficiency in response to a change in work state and the change in work efficiency in response to a change in work attribute is realized as a step function, and the work efficiency when the work state and work attribute are changed is calculated by applying a bias according to the difference between the work state and work attribute using the work efficiency in manual mode in the work state at the time of work planning as a standard. This makes it easy to calculate the work efficiency that has changed due to changes in the work state and work attributes. Each bias is an example, and optimization based on past similar work and work simulation results, and conversion using a continuous function such as a normal distribution rather than a step function conversion are also possible. In addition, the work state at the time of work planning is not limited to manual mode.

Furthermore, in the coefficient optimization method, the work resource allocation calculation unit 141 can rank past similar tasks using statistical methods such as machine learning algorithms and mathematical models, and calculate coefficients related to changes in work efficiency in response to changes in work status and changes in work efficiency in response to changes in task attributes in correlation with the ranking values. In order to select continuous tasks for high-operability robots from among the task attributes, the work resource allocation calculation unit 141 sets a high coefficient for high-operability robot selection.

In a method for extracting a robot operation method with high work efficiency for each work item and updating the work procedure, the work resource allocation calculation unit 141 calculates the improvement of the work efficiency of multiple tasks for multiple tasks with high work continuity. Then, by extracting a robot operation procedure with high work efficiency, it is possible to preferentially extract robot operations with improved work efficiency by engaging in multiple consecutive tasks.

Figure 14 is a chart showing an example of updating work resource allocation. The dashed line in the center of the chart indicates the current time. At this time, a cross icon is displayed because an abnormal condition or symptom of an abnormal condition has been detected for worker A. Note that in each chart, the robot is abbreviated to "robo."

In past Task 1-1 and Task 1-2, Worker A operated Robot A, and Worker B operated Robot B. Worker A's proficiency is "low," and Robot A's operability is "normal." Worker B's proficiency is "high," and Robot B's operability is "normal."

In Task 2-1, Worker A is operating Robot B, and Worker C is operating Robot C. Worker A's proficiency is "low", and the operability of Robot B is "normal". Worker C's proficiency is "medium", and the operability of Robot C is "normal".

According to the plan, Worker A was scheduled to operate Robot A in Task 3-1 and Task 3-2, as shown by the dashed bar. Then, after Worker C operated Robot C in Task 3-1, Worker B was scheduled to operate Robot C in Task 3-2, as shown by the dashed bar.

However, while Worker A was performing Task 3-1, an abnormality or symptom of an abnormality in Worker A's condition was detected. As a result, the work plan update system 1 updates the work resource allocation. The chart of the updated work resource allocation is shown with hatched bars.

Specifically, as shown by the hatched bars, the work plan updating system 1 updates the assignment so that worker B operates robot A instead of worker A in tasks 3-1 and 3-2. Then, as shown by the hatched bars, the work plan updating system 1 changes the assignment so that worker B operates robot C instead of worker C in task 3-2. Here, the work plan updating system 1 continues to assign worker C to task 3-2 due to the continuity of the tasks and robot operation.

In this way, when the work plan update system 1 detects an abnormality in the condition of worker A or a sign of such an abnormality, it changes the allocation of workers from worker A to worker B by increasing the work efficiency of worker B, who has a track record of performing similar tasks in the past with robot B.

15 is a chart showing another example of updating task resource allocation. The dashed line in the center of the chart indicates the current time. The task resource allocation up to the current time and the future task resource allocation plan are the same as those in FIG. 14.
However, while worker A is performing task 3-1, an abnormal condition or a sign of an abnormal condition is detected in worker A. In response to this, the work plan updating system 1 updates the task resource allocation.

The work plan updating system 1 switches the manual operation of robot B by worker A to automatic operation in tasks 3-1 and 3-2, and worker A updates the work content to the safety monitoring work during automatic operation. In the chart in Figure 15, the automatic operation of the robot is indicated by a dark hatched bar, and the safety monitoring work by worker A during automatic operation is indicated by a light hatched bar.

In this way, when the work plan update system 1 detects an abnormality in the condition of worker A or a sign of such an abnormality, it changes the position of robot B to automatic operation.

Figure 16 is a chart showing an example of updating work resource allocation. The dashed line in the center of the chart indicates the current time. The work resource allocation up to the current time and the future work resource allocation plan are the same as in Figure 14.

However, while Worker A was performing Task 3-1, an abnormality or symptom of an abnormality in the status of Robot B was detected. As a result, the work plan update system 1 updates the work resource allocation. At this time, Robot B was performing recovery work.

Specifically, in task 3-1, worker A works using robot A instead of robot B. Then, if it is expected that the efficiency of the work performed by robot A, which is the substitute robot, for task 3 will decrease, the work plan update system 1 changes the time schedule to postpone the work, and then returns robot B, which has recovered in task 3-2, to the work.

Second Embodiment
FIG. 17 is a configuration diagram of a work plan updating system 1A according to the second embodiment.
The work plan updating system 1A of the second embodiment is configured to further include a work process management device 16 in addition to the same configuration as the work plan updating system 1 shown in Fig. 1. It is clearly indicated that the work plan updating system 1A handles a plurality of works.

In the step of designating the work classification of each task based on the comparison results of the work resource allocation update unit 142, the work process management device 16 calculates the overall work efficiency including the variation in work efficiency of each task due to the work resource status. Then, the work process management device 16 outputs the work plan update result that satisfies the pre-specified overall work efficiency threshold value.

18A and 18B are flowcharts showing a work plan update process according to the second embodiment.
First, the workers 2a to 2c operate the robots 3a to 3c to carry out work (step S40).

The work status processing device 12 measures the work status and analyzes and evaluates it (step S41). Specifically, the worker status measurement unit 121 of the work status processing device 12 measures the status of the worker, and the robot status measurement unit 122 measures the status of the robot. Then, the work status analysis and evaluation unit 123 analyzes and evaluates the work status, and the work attribute analysis and evaluation unit 124 analyzes and evaluates the work attributes.
Next, the work status processing device 12 records and manages the work status in the work management database 13 (step S42). Then, the work resource processing device 14 judges whether or not a plan update is necessary (step S43). Here, the work resource processing device 14 judges that a plan update is necessary when the data measured by the work status processing device 12 or the data obtained by analyzing this exceed a pre-specified threshold value.

If the work resource processing device 14 determines that a plan update is necessary (Yes), it proceeds to step S50 in FIG. 18B. If the work resource processing device 14 determines that a plan update is not necessary (No), it proceeds to processing in step S44.

In step S44, the work status processing device 12 determines whether the work is complete. Here, the completion of the work is determined, for example, by whether the work supervisor has input that the work is complete. If the work is not complete (No), the work status processing device 12 returns to the processing of step S40, and if the work is complete (Yes), the processing of FIG. 18A ends.

In step S50, the work resource processing device 14 sets an objective function and constraint conditions. The work resource processing device 14 searches for and extracts similar past tasks from the work management database 13 (step S51). Here, the work resource processing device 14 ranks similar past tasks using statistical methods such as machine learning algorithms and mathematical models, and extracts similar tasks with high ranking values and their task efficiencies.
Then, the work resource processing device 14 calculates the allocation of work resources (step S52). Here, the allocation of work resources means the allocation of resources required for work. In step S52, the work resource processing device 14 extracts, as resources, robots whose work efficiency in each work item exceeds a predetermined value. Note that the work resource processing device 14 may also extract, as resources, robots whose work efficiency in each work item exceeds a predetermined value in a plurality of works whose work continuity exceeds a predetermined value. In step S52, the work resource processing device 14 calculates the overall efficiency including the variation in work efficiency due to the resources required for this work, and calculates the allocation of resources required for this work so as to satisfy a pre-specified threshold value.

Next, the work resource processing device 14 determines whether the calculation of the corresponding work resource has been completed (step S53).

In step S53, if the work resource calculation is not complete (No), the work resource processing device 14 returns to step S50, and if the work resource calculation is complete (Yes), the work resource processing device 14 proceeds to step S54.

In step S54, the work supervisor decides to update this work based on the work resources calculated by the work resource processing device 14. In response to this decision, the work process management device 16 updates the overall work process (step S55). Then, the work instruction operation device 15 updates the worker operation procedure and the robot control (step S56). As a result, the worker and robot resume the work (step S57), and the process returns to step S40 in FIG. 18A.

19 is a chart showing an example of updating task resource allocation. The dashed line in the center of the chart indicates the current time. In this chart, the robot is abbreviated to "robo."
In the past task A-1, worker A operated robot A. The proficiency level of worker A is "low," and the operability of robot A is "normal."

In the next task, A-2, Worker A continues to operate Robot A. In the parallel task, B-1, Worker C operates Robot C. Worker C's proficiency level is "high," and the operability of Robot C is "difficult."

Then, in task A-3, worker A continues to operate robot A, and worker B begins to operate robot B. In parallel task B2, worker C continues to operate robot C, and worker D begins to operate robot D.

However, at the current time while tasks A-3 and B-2 are being performed, an abnormality or a sign of an abnormality in the condition of worker B is detected. As a result, the work plan update system 1 updates the work resource allocation. Note that tasks A-3 and A-4 are set to a high level of difficulty and can only be performed manually.

The work plan update system 1 changes the shift of worker C and has him perform tasks A-3 and A-4 by operating robot B. Worker C has the skills to perform highly difficult tasks such as tasks A-3 and A4.

Then, switch robot B to automatic operation to perform task A-5, and have worker A monitor the safety of robot B.

As a result, there will be no resources to carry out task B-2 and subsequent tasks, so task B-2 is suspended until task A-4 is completed. Then, resources are allocated to task B-2 in parallel with the execution of task A-5. Specifically, for task B-2, worker C and robot C are assigned as originally planned, and worker D and robot D are assigned. Thereafter, worker D and robot D are assigned to tasks B-3 and B-4.

20A and 20B are flowcharts showing periodic work plan update processing according to the second embodiment.
First, the workers 2a to 2c operate the robots 3a to 3c to carry out work (step S60).

The work status processing device 12 periodically measures the work status and analyzes and evaluates it (step S61). Specifically, the worker status measurement unit 121 of the work status processing device 12 periodically measures the status of the worker, and the robot status measurement unit 122 periodically measures the status of the robot. Then, the work status analysis and evaluation unit 123 periodically analyzes and evaluates the work status, and the work attribute analysis and evaluation unit 124 periodically analyzes and evaluates the work attributes.
Then, the work status processing device 12 periodically records and manages the work status in the work management database 13 (step S62). Then, the work resource processing device 14 judges whether or not a plan update is necessary (step S63). Here, the work resource processing device 14 judges that a plan update is necessary when the data measured by the work status processing device 12 or the data obtained by analyzing this exceed a pre-specified threshold value. Specific examples of when a plan update is necessary will be described later with reference to Figs. 21 and 22.
If the plan update is necessary (Yes), the work resource processing device 14 proceeds to step S70 in FIG. 20B, and if the plan update is not necessary (No), the work resource processing device 14 proceeds to the process of step S64.

In step S64, the work status processing device 12 determines whether the work is complete. Here, the completion of the work is determined, for example, by whether the work supervisor has input that the work is complete. If the work is not complete (No), the work status processing device 12 returns to the processing of step S60, and if the work is complete (Yes), the processing of FIG. 20A ends.

The work resource processing device 14 sets an objective function and constraint conditions (step S70), and searches for and extracts similar past work from the work management database 13 (step S71). The work resource processing device 14 then calculates the allocation of work resources (step S72). In step S72, the work resource processing device 14 extracts, as resources, robots whose work efficiency in each work item exceeds a predetermined value. The work resource processing device 14 may also extract, as resources, robots whose work efficiency in each work item exceeds a predetermined value in multiple works whose work continuity exceeds a predetermined value. In step S72, the work resource processing device 14 calculates the overall efficiency, including the variation in work efficiency due to the resources required for this work, and calculates the allocation of resources required for this work so as to satisfy a pre-specified threshold value.

Next, the work resource processing device 14 determines whether the calculation of the corresponding work resource has been completed (step S73).

In step S73, if the work resource calculation is not complete (No), the work resource processing device 14 returns to step S70, and if the work resource calculation is complete (Yes), the work resource processing device 14 proceeds to step S74.

In step S74, the work supervisor determines and inputs an update to this work based on the work resources calculated by the work resource processing device 14. In response to this determination, the work process management device 16 updates the overall work process (step S75). Then, the work instruction operation device 15 updates the worker operation procedure and the robot control (step S76). As a result, the worker and robot resume the work (step S77), and the process returns to step S60 in FIG. 20A.

Figure 21 is a graph showing an example of data output from the work status measurement unit. The vertical axis of the graph shows the value of the analysis data, and the horizontal axis shows time.

The upper dashed line is the vital threshold, which is used to determine the need to update the plan based on vital analysis data such as fatigue level and concentration level. The lower dashed line is the robot movement threshold, which is used to determine the need to update the plan based on robot movement analysis data such as robot movement calibration frequency and unit calibration amount.

In cases where the measured value exceeds any of the thresholds, the work plan update system 1 updates the plan. The work plan update system 1 also updates the plan in cases where the measured value exceeds any of the thresholds and also exceeds the threshold of the derivative or second derivative of the deterioration curve.

FIG. 22 is a graph showing an example of data output from the robot state measuring unit 122.
The robot state measurement unit 122 assigns a variance value σ due to variation to the measured value. Here, the arrows added to the lines of each graph are obtained by multiplying the variance value σ due to variation by a predetermined coefficient.

The work plan updating system 1 updates the plan when the range to which the variance value obtained by multiplying the measured value by a predetermined coefficient is assigned exceeds any threshold value. The work plan updating system 1 further updates the plan when the range to which the variance value obtained by multiplying the measured value by a predetermined coefficient is assigned exceeds any threshold value and also exceeds the threshold value of the derivative value or the second derivative value of the deterioration curve. The coefficient by which the variance value is multiplied is set by the worker depending on the importance and risk of the work.

Third Embodiment
FIG. 23 is a configuration diagram of a work plan updating system 1B according to the third embodiment.
The work plan updating system 1B of the third embodiment has a work management database 13B that is different from the work management database 13 of the work plan updating system 1 shown in Fig. 1. The work instruction operating device 15 accumulates the work resource update results, worker operation instruction data, and work robot control data in the work management database 13B.

FIG. 24 is a configuration diagram of the work management database 13B.
The work management database 13B has the same configuration as the work management database 13 shown in FIG. 6, and further includes a work resource allocation record management section 136, a worker procedure record management section 137, and a robot control record management section 138.

The work resource allocation record management unit 136 records the work resource update results by the work instruction operation device 15. The worker procedure record management unit 137 records worker operation instruction data by the work instruction operation device 15. The robot control record management unit 138 records work robot control data by the work instruction operation device 15.
By managing this information, it is possible to accumulate more knowledge about past work plan updates, present more suitable past similar work, and allocate appropriate work resources to the work.

(Modification)
The present invention is not limited to the above-described embodiment, and includes various modified examples. For example, the above-described embodiment has been described in detail to clearly explain the present invention, and is not necessarily limited to those having all of the configurations described. It is possible to replace a part of the configuration of one embodiment with the configuration of another embodiment, and it is also possible to add the configuration of another embodiment to the configuration of one embodiment. In addition, it is also possible to add, delete, or replace a part of the configuration of each embodiment with another configuration.

The above configurations, functions, processing units, processing means, etc. may be realized in part or in whole by hardware such as an integrated circuit. The above configurations, functions, etc. may be realized by software by a processor interpreting and executing a program that realizes each function. Information such as the programs, tables, and files that realize each function can be stored in a recording device such as a memory, a hard disk, or an SSD (Solid State Drive), or on a recording medium such as a flash memory card or a DVD (Digital Versatile Disk).

In each embodiment, the control lines and information lines are those that are considered necessary for explanation, and not all control lines and information lines in the product are necessarily shown. In reality, it can be considered that almost all components are interconnected.

1, 1A, 1B Work plan update system 11 Data interface unit 12 Work status processing device (work status processing unit)
121 Worker status measurement unit 122 Robot status measurement unit 123 Work status analysis and evaluation unit 124 Work attribute analysis and evaluation unit 13, 13B Work management database 131 Worker status record management unit 132 Robot status record management unit 133 Work status record management unit 134 Work attribute record management unit 135 Work result record management unit 136 Work resource allocation record management unit 137 Worker procedure record management unit 138 Robot control record management unit 14 Work resource processing device (work resource processing unit)
141 Work resource allocation calculation unit 142 Work resource allocation update unit 15 Work instruction operation device (work instruction operation unit)
151 Worker procedure instruction unit 152 Robot control operation unit 16 Work process management device (work process management unit)
2a to 2c Workers 3a to 3c Robot 4 Work incidental information 5 Work attribute information

Claims (12)

a data interface unit that acquires data relating to each task included in a task plan from a worker and a robot at a pre-specified time interval;
a work status processing unit that analyzes the vital signs of the worker or the motion of the robot from the data;
a work resource processing unit which, when detecting a status abnormality from the data acquired by said data interface unit or from data obtained by analyzing said data by said work status processing unit, updates the allocation of workers and robots, which are resources required for subsequent work in said work plan , to said work ;
Equipped with
the work resource processing unit compares the work efficiency of other tasks similar to each of the tasks in the work plan after detecting a status abnormality from the data and stored in a database between manual and automatic operations, and if the manual work efficiency of the other tasks is high, specifies a work classification for manually performing each of the tasks, and if the automatic work efficiency of the other tasks is high, updates the work plan by specifying a work classification for automatically performing each of the tasks.
A work plan updating system comprising: the work resource processing unit calculates the work efficiency of the work performed manually and automatically by dividing the work time in the selected operation mode by the work time in the manual operation mode;
2. The work plan updating system according to claim 1 . The work resource processing unit further calculates a work efficiency of the work performed manually and automatically by dividing a work time in the selected operation mode by a work time in the manual operation, and multiplies the work efficiency by a work state coefficient that decreases as the dose of the work state increases.
3. The work plan updating system according to claim 2 . The work resource processing unit further calculates a work efficiency for the manual and automatic work of the work by dividing a work time in the selected operation mode by a work time in the manual work mode, and multiplies the work efficiency by a work state coefficient that increases as the accuracy of the layout information of the work state increases.
3. The work plan updating system according to claim 2 . The task resource processing unit further calculates task efficiency for the manual and automated tasks by dividing the task time in the selected operation mode by the manual task time, and multiplies the task efficiency by a task attribute coefficient that decreases as the difficulty of the task increases.
3. The work plan updating system according to claim 2 . The work resource processing unit further calculates a work efficiency for the manual and automated work of the work by dividing the work time in the selected operation mode by the manual work time, and multiplies the work efficiency by a work attribute coefficient that increases as the proficiency of the worker engaged in the work increases.
3. The work plan updating system according to claim 2 . the task resource processing unit further calculates task efficiency in manual and automated modes of the task by dividing the task time in the selected operation mode by the task time in manual mode, and multiplies the task efficiency by a task attribute coefficient that increases as the operability of the robot used in the task increases;
3. The work plan updating system according to claim 2 . the task resource processing unit, when calculating the task efficiency when the task is performed manually and when the task is performed automatically, ranks past tasks similar to the task in question using a machine learning algorithm or a statistical method using a mathematical model, extracts similar tasks with high ranking values and their task efficiency, and updates the allocation of workers and/or robots, which are resources required for each task in the work plan, to each task.
3. The work plan updating system according to claim 2 . the work resource processing unit calculates a deviation of work efficiency data relating to a long-term work by the resources required for the work from a standard value , calculates an overall efficiency of the work plan including the deviation, and updates the allocation of the resources required for the work so that the overall efficiency satisfies a pre-specified threshold value;
9. The work plan updating system according to claim 8 . the task resource processing unit, when calculating allocation of resources required for the task, ranks past similar tasks similar to the task using a statistical method, extracts the task efficiency of the task from the highly ranked similar tasks, extracts a robot whose task efficiency for each task item exceeds a predetermined value as the resource , and allocates the robot as a resource for the task;
2. The work plan updating system according to claim 1 . When calculating the allocation of resources required for the tasks, the task resource processing unit calculates the task efficiency by improving the task efficiency of a plurality of tasks whose task efficiency exceeds a predetermined value when performed continuously , and extracts, as the resource, a robot whose task efficiency for each task item exceeds the predetermined value.
11. The work plan updating system according to claim 10 . A data interface unit provided in the work plan updating system acquires data related to each work included in the work plan from the worker and the robot at a pre-specified time interval;
A step in which a work status processing unit provided in the work plan updating system analyzes the vital signs of the worker or the motion of the robot from the data;
a step in which a work resource processing unit provided in the work plan updating system , when detecting a status abnormality from the data acquired by the data interface unit or from data obtained by analyzing the data acquired by the work status processing unit, updates the allocation of workers and robots, which are resources required for subsequent work in the work plan, to the work;
Run
the work resource processing unit compares the work efficiency of other tasks similar to each of the tasks in the work plan after detecting a status abnormality from the data and stored in a database between manual and automatic operations, and if the manual work efficiency of the other tasks is high, specifies a work classification for manually performing each of the tasks, and if the automatic work efficiency of the other tasks is high, updates the work plan by specifying a work classification for automatically performing each of the tasks.
A work plan updating method comprising:

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