Personnel distribution planning system

Abstract

To make a plan for personnel distribution on the basis of the level of skills of individual workers.SOLUTION: A personnel distribution planning system 100 makes a plan for personnel distribution by using a digital twin line 22 so that works of a plurality of workers can achieve a goal processing plan. The digital twin line 22 is formed by modelling a real line 2 made by a plurality of workers in coordination and has the level of the skill of each of the workers as a parameter. The personnel distribution planning system 100 updates the level of the skill of each worker used in the digital twin line 22 on the basis of the work experience obtained under the personnel distribution plan.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The present disclosure relates to a system for planning personnel allocation in a production line or a logistics line. [Background technology]

[0002] Japanese Patent Application Laid-Open No. 2012-174098 discloses a conventional technique for creating a work plan for a manufacturing process in which specifications and delivery dates are set for each product. According to this conventional technique, production indicators such as production volume and delivery date compliance rate are quantitatively predicted. Then, when the production indicators deteriorate due to a lack of worker skills, a product work plan is created that includes a worker allocation plan, taking into account a worker training plan.

[0003] The production capacity in a manufacturing process depends on the proficiency of each worker. A worker's proficiency improves as he or she gains work experience, and as proficiency improves, the production capacity of that worker also improves. This is also true for workers who handle goods in logistics processes. However, the above-mentioned conventional technology does not take into account the proficiency of each worker when creating a work plan.

[0004] In addition to JP-A-2012-174098, JP-A-2010-244176 can be cited as an example of a document showing the state of the art in the technical field related to the present disclosure. [Prior art documents] [Patent documents]

[0005] [Patent Document 1] JP 2012-174098 A [Patent Document 2] JP 2010-244176 A Summary of the Invention [Problem to be solved by the invention]

[0006] The present disclosure has been made in view of the above-mentioned problems. It is an object of the present disclosure to provide a system that can plan personnel allocation taking into account the skill level of each worker. [Means for solving the problem]

[0007] A first aspect of the present disclosure includes a system for planning personnel allocation for a line that is composed of multiple workers working together. The system includes a processor, a memory that is coupled to the processor or built into the processor, and multiple instructions stored in the memory. The multiple instructions cause the processor to execute the following three processes. The first process is a process for receiving a target processing plan for the line. The second process is a process for creating a personnel allocation plan using a simulation model so that the target processing plan is achieved by work by the workers. The simulation model is a model of the line, and has the proficiency of each worker as a parameter. And the third process is a process for updating the proficiency of each worker used in the simulation model based on work experience obtained under the personnel allocation plan. By creating a personnel allocation plan according to the proficiency of each worker and updating the proficiency of each worker every time work is performed according to the personnel allocation plan, it is possible to create a personnel allocation plan that matches the current proficiency of the workers in achieving the target processing plan.

[0008] In a first mode of the first aspect, the instructions may cause the processor to receive a target proficiency distribution among the workers. In that case, creating a personnel allocation plan may include searching for a personnel allocation plan that realizes the target proficiency distribution within a predetermined period of time while achieving the target processing plan, using a simulation model. There is variation in proficiency among workers due to differences in work experience. In addition, it takes a long time to raise the proficiency of all workers to an advanced level. However, in a production line composed of multiple workers who work together, it is known that even if the proficiency of all workers is not necessarily at an advanced level, high work performance can be obtained for the entire line depending on the distribution of proficiency among the workers. Therefore, according to this mode, a desired proficiency distribution can be realized while achieving the target processing plan.

[0009] In the first aspect of the first embodiment, the instructions may cause the processor to accept a time period for realizing a target proficiency distribution as a target value, thereby making it possible to realize a desired proficiency distribution within a desired time period.

[0010] In a second embodiment of the first aspect, the instructions may cause the processor to update the proficiency of each worker by inputting the cumulative work experience of each worker into a proficiency growth curve graph prepared for each worker. By using the proficiency growth curve graph prepared for each worker, the proficiency of each worker can be easily determined.

[0011] In the second mode of the first aspect, the instructions may further cause the processor to execute a process of acquiring ability data of each worker in real space, and a process of correcting the proficiency growth curve graph for each worker based on the ability data for each worker. By reflecting the ability data of the worker acquired in real space in the proficiency growth curve graph, the proficiency growth curve graph can be personalized for each worker, and the accuracy of the proficiency used in the simulation model can be improved.

[0012] A second aspect of the present disclosure includes a system for planning personnel allocation for a line composed of multiple workers working together. The system includes a processor, a memory coupled to the processor or built into the processor, and multiple instructions stored in the memory. The multiple instructions cause the processor to execute the following three processes. The first process is a process for receiving a target processing plan for the line. The second process is a process for creating a personnel allocation plan using a simulation model so that the target processing plan is achieved by the work of the workers. The simulation model is a model of the line, and has the proficiency of each worker for each task as a parameter. And the third process is a process for updating the proficiency of each worker used in the simulation model for each task based on the work experience for each task obtained under the personnel allocation plan. When a worker is engaged in multiple tasks with different contents, he or she gains experience for each task, and his or her proficiency for each task improves. By creating a personnel allocation plan based on the proficiency of each worker for each task, and updating the proficiency of each worker and each task each time work is performed according to the personnel allocation plan, it is possible to create a personnel allocation plan that matches the current proficiency of each worker for each task in order to achieve a target processing plan.

[0013] In a first mode of the second aspect, the instructions may cause the processor to receive a target proficiency distribution for each task among the workers. In this case, creating a personnel allocation plan may include searching for a personnel allocation plan for realizing a target proficiency distribution for each task within a predetermined period of time while achieving the target processing plan, using a simulation model. It is known that in a production line requiring multiple tasks of different content, even if the workers are not necessarily skilled at all tasks, high performance can be achieved in the line as a whole depending on the distribution of proficiency for each task among the workers. Therefore, according to this mode, a desired proficiency distribution for each task can be realized while achieving the target processing plan.

[0014] In the first aspect of the second aspect, the instructions may cause the processor to accept a time period for realizing a target proficiency distribution as a target value, thereby making it possible to realize a desired proficiency distribution for each task within a desired time period.

[0015] In a second mode of the second aspect, the instructions may cause the processor to update the proficiency of each worker for each task by inputting accumulated work experience for each worker and for each task into a proficiency growth curve graph prepared for each worker and for each task. By using the proficiency growth curve graph prepared for each worker and for each task, the proficiency of each worker can be easily calculated for each task.

[0016] In the second mode of the second aspect, the instructions may further cause the processor to execute a process of acquiring ability data of each worker in real space, and a process of correcting the proficiency growth curve graph for each worker and for each task based on the ability data of each worker. By reflecting the ability data of the workers acquired in real space in the proficiency growth curve graph, the proficiency growth curve graph can be personalized for each worker and for each task, and the accuracy of the proficiency used in the simulation model can be improved. Effect of the Invention

[0017] As described above, according to the present disclosure, it is possible to plan personnel allocation that matches the skill levels of current workers in order to achieve a target processing plan. [Brief description of the drawings]

[0018] [Figure 1] FIG. 1 is a diagram illustrating an overview of a personnel deployment planning system. [Diagram 2] FIG. 13 is a diagram illustrating an example of a target proficiency distribution. [Diagram 3] FIG. 13 is a diagram illustrating an example of a skill growth curve graph for each worker. [Figure 4] FIG. 13 is a diagram showing an example of a personnel allocation plan obtained by a simulation. [Diagram 5] FIG. 13 is a diagram showing an example of a target skill level distribution for each operation content. [Figure 6] FIG. 13 is a diagram showing an example of a skill growth curve graph for each worker and each task. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0019] 1. Overview of the personnel allocation planning system 1 is a diagram showing an overview of a personnel deployment planning system 100 according to this embodiment. The personnel deployment planning system 100 is a system that plans the deployment of personnel to a line (hereinafter referred to as a real line) 2 in a factory or a logistics center in the real world.

[0020] Real line 2 includes multiple processes and is made up of multiple workers who work together. In the example shown in Fig. 1, real line 2 includes processes A, B, C, and D. Two workers are assigned to process A, three to process B, three to process C, and two to process D. Workers assigned to the same process form a work group that works together to perform the work.

[0021] The personnel allocation planning system 100 includes a plan creation device 10. The plan creation device 10 is a device that creates a personnel allocation plan to be presented to the real line 2. A target processing plan TPP, a target proficiency distribution TSD, and a target training period TDP are input to the plan creation device 10 as information for creating a personnel allocation plan. The target processing plan TPP is a plan for the amount of processing on the real line 2 in a set period. The set period is set, for example, to a period of one day, one week, one month, etc. The target proficiency distribution TSD is a distribution of the target proficiency of workers. For example, when workers are classified into advanced, intermediate, and beginners according to their proficiency, the target ratios of each are expressed as the target proficiency distribution TSD. The target training period TDP is a target period until a worker is trained to achieve the target proficiency distribution TSD. The target training period TDP is set to a period longer than the set period of the target processing plan TPP, for example, several months, half a year, one year, etc. Input of these target values ​​to the plan creation device 10 can be performed from an input device (not shown) connected to the plan creation device 10. The operator can set any value as the target value.

[0022] In addition, real data RD acquired from the real line 2 is input to the plan creation device 10 as information for creating a personnel allocation plan. The real data RD includes observation data acquired by sensors such as cameras installed in a factory or a logistics center and wearable devices worn by individual workers. The real data RD also includes work performance values ​​of the real line 2 in a unit period such as a day, a week, or a month. The plan creation device 10 is connected to a data collection computer installed in the real line 2 via a network. The real data RD may be transmitted to the plan creation device 10 in real time depending on the content of the data, or may be transmitted to the plan creation device 10 at regular intervals.

[0023] The plan creation device 10 performs a simulation of a personnel allocation plan using a simulator 20. The plan creation device 10 inputs the acquired target process plan TPP, target skill distribution TSD, target training period TDP, and real data RD to the simulator 20.

[0024] The simulator 20 uses a digital twin line 22 to simulate the personnel allocation plan. The digital twin line 22 is a simulation model that reproduces the real line 2 in a virtual space. Therefore, in the example shown in Fig. 1, the digital twin line 22 includes process A, process B, process C, and process D, and two workers are assigned to process A, three workers to process B, three workers to process C, and two workers to process D.

[0025] The parameters of the digital twin line 22 include the proficiency of each worker. In the real world, the proficiency of each worker varies. Like the workers on the real line 2, the proficiency of each worker on the digital twin line 22 is set in a manner similar to that of the workers on the real line 2. The proficiency of each worker is updated in the simulation. The real data RD acquired from the real line 2 is used to update the proficiency. For example, the increase in proficiency of each worker is calculated based on the work time and work performance of each worker included in the real data RD.

[0026] The simulator 20 searches for a personnel allocation pattern that can achieve the goal using the digital twin line 22. That is, a personnel allocation pattern that can achieve the target process plan TPP and the target skill distribution TSD within the target training period TDP is searched for. For example, a genetic algorithm is used for the search for the allocation pattern by the simulator 20. The simulator 20 outputs the search result for the allocation pattern to the plan creation device 10 as a simulation result SR.

[0027] The plan creation device 10 creates a personnel allocation plan PA for the real line 2 based on the simulation results SR. The created personnel allocation plan PA is transmitted to, for example, a management computer for the real line 2. The management computer instructs each worker on the work position on the real line 2 according to the personnel allocation plan PA. By allocating workers on the real line 2 according to the personnel allocation plan PA, it becomes possible to achieve a target processing plan and realize a target proficiency distribution within a target training period.

[0028] The personnel allocation planning system 100 includes at least one processor (hereinafter simply referred to as the processor) and at least one memory (hereinafter simply referred to as the memory) coupled to the processor or built into the processor 12. A program executable by the processor is stored in the memory. The program includes a plurality of instructions. The instructions include instructions for causing the processor to function as the plan creation device 10 and instructions for causing the processor to function as the simulator 20. The program can be stored in a computer-readable non-transitory storage medium.

[0029] Two embodiments of the personnel allocation planning performed by the personnel allocation planning system 100 will be described below.

[0030] 2. Personnel allocation plan for the first embodiment The first embodiment is a personnel allocation plan for a line where the work content is not significantly different between processes. The proficiency of each worker is set as a parameter in the digital twin line 22 of the simulator 20. The plan creation device 10 inputs real data RD to the simulator 20 and simulates a personnel allocation plan that achieves a target proficiency distribution TSD within a target training period TDP while achieving a target process plan TPP through the work of multiple workers working together.

[0031] FIG. 2 is an example of a target proficiency distribution input to the plan creation device 10 in the first embodiment. In the example shown in FIG. 2, when all workers are classified into advanced, intermediate, and beginners according to their proficiency levels, the target is set to set the ratio of advanced workers to 30%, the ratio of intermediate workers to 40%, and the ratio of beginners to 30% among all workers. The target proficiency distribution may be updated every time it is achieved. For example, once the target proficiency distribution shown in FIG. 2 is achieved, the new target may be set to set the ratio of advanced workers to 35%, the ratio of intermediate workers to 50%, and the ratio of beginners to 15%.

[0032] However, the rate at which proficiency improves with work experience slows as proficiency increases. Also, when workers are replaced, advanced workers may leave the line and beginners may join. For this reason, it is realistically difficult to make all workers advanced. Therefore, a proficiency distribution in which there are appropriate proportions of advanced, intermediate, and beginner workers is ultimately set as the final target proficiency distribution.

[0033] The proficiency of each worker is calculated using a proficiency growth curve graph as shown in Figure 3. A proficiency growth curve graph is prepared for each worker. The horizontal axis of the proficiency growth curve graph is the number of times a worker has had work experience, i.e., the cumulative work experience. The proficiency is updated each time a worker gains work experience. When the worker has little work experience, the degree of growth in proficiency is large, but once the worker has gained a certain amount of work experience, the growth in proficiency slows down and reaches a saturation point.

[0034] The proficiency growth curve graph has a different shape for each worker. The initial shape of the proficiency growth curve graph may be the same for all workers, or may differ depending on the attributes (age, sex, physique) and past work experience of each worker. After the worker starts working on the line and gaining work experience, the proficiency growth curve graph is corrected for each worker based on the real data RD acquired from the real line 2. The ability data of each worker, such as processing speed and processing volume, contained in the real data RD is used to correct the proficiency growth curve graph.

[0035] Fig. 4 shows an example of a personnel allocation plan obtained by a simulation using the simulator 20. In Fig. 4, black people indicate advanced users with high levels of proficiency, hatched people indicate intermediate users with medium levels of proficiency, and white people indicate beginners with low levels of proficiency. Of the personnel allocations obtained by the simulation, the upper row is a personnel allocation that prioritizes throughput, and the lower row is a personnel allocation that prioritizes training beginners.

[0036] In personnel allocation that prioritizes throughput, workers are allocated so that the processing capacity is uniform between processes. In personnel allocation that prioritizes training, workers are allocated so that beginners are paired with advanced workers, or beginners are grouped with multiple intermediate or higher level workers. By adopting personnel allocation that prioritizes throughput when the target throughput is large, and by using personnel allocation that prioritizes training when the target throughput is small, it is possible to achieve the target processing plan while also training workers.

[0037] In the first embodiment, a personnel allocation plan is created according to the proficiency of each worker. The proficiency of each worker is updated every time a task is performed according to the personnel allocation plan, so that a personnel allocation plan that matches the current proficiency of each worker can be created to achieve a target processing plan.

[0038] 3. Personnel allocation plan of the second embodiment The second embodiment is a personnel allocation plan for a line where the work content differs greatly between processes. The proficiency of each worker and each work content is set as a parameter in the digital twin line 22 of the simulator 20. The plan creation device 10 inputs real data RD to the simulator 20 and simulates a personnel allocation plan that achieves a target proficiency distribution TSD for each work content within a target training period TDP while achieving a target processing plan TPP by the work of multiple workers working together.

[0039] FIG. 5 is an example of a target proficiency distribution for each task input to the plan creation device 10 in the second embodiment. In the example shown in FIG. 5, a target percentage of advanced workers, intermediate workers, and beginners among all workers is set for each of tasks A and B. The target proficiency distribution may be updated for each task. For example, if the target proficiency distribution for task B is achieved even if the target proficiency distribution for task A has not been achieved, only the target proficiency distribution for task B may be updated. Note that, in the example shown in FIG. 5, a target proficiency distribution is set for two task contents, task A and task B, but a target proficiency distribution may be set for three or more task contents.

[0040] The proficiency of each worker for each task is calculated using a proficiency growth curve graph as shown in FIG. 6. A proficiency growth curve graph is prepared for each worker and for each task. The proficiency growth curve graph has a different shape for each worker and for each task. The initial shape of the proficiency growth curve graph may be common to the tasks, or may be different depending on the difficulty of the tasks. Since each worker has tasks that he or she is good at and tasks that he or she is not good at, the initial shape of the proficiency growth curve graph may be different for each worker and for each task. After the worker starts to gain work experience on the line, the proficiency growth curve graph is corrected for each worker and for each task based on the real data RD acquired from the real line 2. The ability data of each worker, such as the processing speed and the processing amount for each task included in the real data RD, is used to correct the proficiency growth curve graph. The degree of improvement in proficiency with respect to work experience differs depending on whether the worker is good at or not good at the task.

[0041] When a worker is engaged in a plurality of different tasks, the worker gains experience for each task and improves his / her proficiency for each task. In the second embodiment, a personnel allocation plan is created according to the proficiency of each worker for each task. By updating the proficiency of each worker and each task every time a task is performed according to the personnel allocation plan, it is possible to create a personnel allocation plan that matches the current proficiency of each worker for each task in order to achieve a target processing plan. [Explanation of symbols]

[0042] 2 Real Line 10 Planning device 20 Simulator 22 Digital Twin Line 100 Personnel Planning System

Claims

1. A system for planning personnel allocation for a line consisting of a plurality of workers working in cooperation with each other, At least one processor; at least one memory coupled to or embedded in said at least one processor; a plurality of instructions executable by the at least one processor stored in the at least one memory; The instructions are provided to the at least one processor: accepting a target process plan for the line; creating a personnel allocation plan using a simulation model that models the line and has the proficiency levels of the plurality of workers as parameters so that the target processing plan is achieved by the work of the plurality of workers; updating the proficiency of each of the plurality of workers used in the simulation model based on work experience obtained under the personnel allocation plan. A personnel allocation planning system comprising:

2. 2. The personnel allocation planning system according to claim 1, The instructions are further configured to cause the at least one processor to receive a target skill distribution among the plurality of workers; Creating the personnel allocation plan includes searching, using the simulation model, for a personnel allocation plan that realizes the target proficiency distribution within a predetermined period of time while achieving the target processing plan. A personnel allocation planning system comprising:

3. 3. The personnel allocation planning system according to claim 2, The instructions are further configured to cause the at least one processor to accept the predetermined period of time as a target value. A personnel allocation planning system comprising:

4. 2. The personnel allocation planning system according to claim 1, The instructions are configured to cause the at least one processor to update a proficiency level of each of the plurality of workers by inputting a cumulative work experience of each worker into a proficiency growth curve graph prepared for each worker. A personnel allocation planning system comprising:

5. 5. The personnel allocation planning system according to claim 4, The instructions include instructions to the at least one processor: acquiring ability data of each of the plurality of workers in a real space; and correcting the proficiency growth curve graph for each worker based on the ability data for each worker. A personnel allocation planning system comprising:

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