CN114169778A - Enterprise work task distribution system based on artificial intelligence - Google Patents
Enterprise work task distribution system based on artificial intelligence Download PDFInfo
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Abstract
The invention discloses an enterprise work task distribution system based on artificial intelligence, which relates to the field of enterprise task distribution, and comprises a task system and a database, wherein the task system comprises a central processing module, a task entry module, a task identification system, a task matching system, a cloud storage module, a database and a supervision system; the task type can be identified through the task identification system, and then the task is accurately segmented through matching of the task segmentation module, the staff ability evaluation module and the ability and task fitting module in the task matching system and comparing with previous tasks in the database.
Description
Technical Field
The invention relates to the technical field of enterprise task allocation, in particular to an enterprise work task allocation system based on artificial intelligence.
Background
With the change of the technology-changing industry, in recent years, digitalization and informatization technologies are widely applied to various industries, and great changes are brought to various industries. In the manufacturing industry, with the introduction of digitalization and informatization technologies, the industry gradually develops towards the direction of intelligent manufacturing;
in the aspect of personnel task allocation, due to the fact that enterprise personnel skill levels are different, task types are different, and meanwhile available time and personnel cost of each person are different, reasonable allocation of tasks is another key point of task management;
through retrieval, the invention patent with the Chinese patent number of CN111798156A discloses a system and a method for evaluating the workload of task allocation based on a working platform, and relates to the technical field of computer information processing. The system comprises a workload analysis module, a workload evaluation training module, a work difficulty analysis module and a workload distribution module; the workload analysis module comprises a keyword extraction module and a feature extraction module; the workload evaluation training module comprises an extraction unit and a training unit; the work difficulty analysis module comprises a retrieval unit and a difficulty statistic unit; the workload distribution module comprises a matching unit and a reminding unit. According to the method, keywords and features are extracted from the work items, the analysis and statistics of the work difficulty are realized by using the feature extraction, the matching of the work is realized by using the keyword extraction, the evaluation of the task workload is finally completed, the work evaluation accuracy is improved, and the project completion efficiency and progress are accelerated.
However, in the system, the tasks can be distributed only by extracting keywords and features from the work items and using the feature extraction to realize the analysis and statistics of the work difficulty, but in actual work, the enterprise items are too large, the items need to be finely split, and the tasks in the sequential mode are directly distributed, so that a lot of time is consumed for the task progress, meanwhile, the progress of the whole task is reduced, and the most fit staff is difficult to find for the project tasks, and therefore, an enterprise work task distribution system based on artificial intelligence is needed.
Disclosure of Invention
The invention aims to solve the defects that in the prior art, tasks in a sequential mode are directly distributed, so that a great deal of time is consumed for task development, the progress of the whole task is reduced, and the most fit staff is difficult to find for project tasks, and provides an enterprise work task distribution system based on artificial intelligence.
In order to achieve the purpose, the invention adopts the following technical scheme:
an enterprise work task distribution system based on artificial intelligence comprises a task system and a database, wherein the task system comprises a central processing module, a task entering module, a task recognition system, a task matching system, a cloud storage module, a database and a supervision system, the external of the task system is in communication connection with the cloud storage module, the cloud storage module is in communication connection with the database, the task entering module enters tasks in an enterprise, and the task entering module transmits entered task information to the central processing module;
the central processing module is internally provided with a staff data input module and a feedback evaluation module, the central processing module is used for inputting data of staff at work and receiving opinions of the staff during working, the central processing module transmits task information to the task identification system, the task identification system identifies the type of a task, the task identification system is in communication connection with the task matching system, and the central processing module transmits the data information of the staff to the task matching system through the task identification system;
the task matching system comprises a task segmentation module, a staff capability evaluation module and a capability and task fitting module, and is used for segmenting received tasks, matching segmented task occupation ratio with staff capability values from high to low according to capability values of staff corresponding to task directions, and simultaneously performing overall planning on tasks which cannot be completed in time;
the central processing module is in communication connection with the supervision system, the supervision system internally comprises a work log collecting module, a money tracking module and a right and responsibility corresponding module, the supervision system collects the daily work logs and money of the staff, and simultaneously, the authority of the task corresponds to the staff according to different distributed tasks.
The above technical solution further comprises:
the staff data entry module collects data in the database, the collected content comprises past tasks of the enterprise staff, the task completion degree and the completion time, and the feedback evaluation module acquires suggestions fed back by the staff.
The task identification system receives the tasks, identifies the types of the tasks through the sequential mode tasks and the parallel mode tasks, and is in communication connection with the early preparation module.
The staff ability evaluation module scores the abilities of the staff in different tasks according to the data of the staff in the staff data entry module, and the scoring standards comprise that the task completion degree accounts for 60%, the timeliness accounts for 25%, and the enterprise investment resources account for 15%.
When the task is detected to be the sequential mode task, the sequential mode task transmits the task mode to the task matching system, the task segmentation module segments the task, and because the detected task is the sequential progressive type, the sub-tasks which are completed uniformly are integrated into a whole in the segmentation process, and the working direction of the whole task set is defined.
The ability and task fitting module selects the staff corresponding to the task direction to perform task allocation through the evaluation of the abilities of the staff in different tasks in the staff ability evaluation module, and performs early-stage task preparation on the staff needing to be supported by the early-stage tasks through the early-stage preparation module.
When the task is detected to be the parallel mode task, the parallel mode task transmits the task mode to the task matching system, the task is divided by the task dividing module, and the task dividing module accurately divides the task by comparing the past task data in the database in the task dividing process.
The task segmentation module collects the tasks in the same working direction after segmentation, and then selects the staff with the highest attaching degree through the capability and task attaching module, and performs task distribution according to the sequence from top to bottom.
The work log collecting module collects the work logs of the employees distributed to the tasks, the money tracking module tracks the money consumed in the task developing process, and the authority corresponding module establishes different authorities for the employees according to different tasks distributed by the employees.
Compared with the prior art, the invention has the beneficial effects that:
in the invention, the task type can be identified through a task identification system, and then the task is accurately segmented through the matching use of a task segmentation module, a staff capability evaluation module and a capability and task laminating module in a task matching system and the comparison with the previous tasks in a database, and the staff capability evaluation module calculates the data in staff through a staff data input module, so that the scores of the staff in all task directions are obtained, and the detection of the laminating degree between the tasks and the staff can be realized through the capability and task laminating module;
when the tasks in the sequential mode are met, the separated tasks are distributed, meanwhile, the staff needing the front-end task data support can carry out early-stage preparation, the total time consumption of the tasks is reduced, the tasks are accurately distributed to the corresponding staff, the working efficiency of an enterprise is increased, and the resources input by the enterprise are reduced.
Drawings
FIG. 1 is a system diagram of an enterprise work task allocation system based on artificial intelligence according to the present invention;
FIG. 2 is a system block diagram of a central processing module according to the present invention;
FIG. 3 is a system block diagram of a task recognition system of the present invention;
FIG. 4 is a system block diagram of a task matching system of the present invention;
fig. 5 is a system block diagram of a supervisory system in accordance with the present invention.
In the figure: 1. a task system; 2. a central processing module; 3. a task entry module; 4. a task identification system; 5. a task matching system; 6. a cloud storage module; 7. a database; 8. a supervisory system; 9. a staff data entry module; 10. a feedback evaluation module; 11. a sequential mode task; 12. a parallel mode task; 13. a preliminary preparation module; 14. a task segmentation module; 15. a staff capability evaluation module; 16. a capability and task fitting module; 17. a working log summarizing module; 18. a money tracking module; 19. and the authority corresponding module.
Detailed Description
The technical solution of the present invention is further explained with reference to the accompanying drawings and specific embodiments.
Example one
As shown in fig. 1-5, the enterprise work task allocation system based on artificial intelligence provided by the invention comprises a task system 1 and a database 7, wherein the task system 1 comprises a central processing module 2, a task entry module 3, a task recognition system 4, a task matching system 5, a cloud storage module 6, a database 7 and a supervision system 8, the task entry module 3 enters tasks in an enterprise, and the task entry module 3 transmits entered task information to the central processing module 2;
the central processing module 2 internally comprises a staff data input module 9 and a feedback evaluation module 10, the central processing module 2 inputs data of staff and receives opinions of the staff during working, the central processing module 2 transmits task information to the task identification system 4, the task identification system 4 identifies the type of a task, the task identification system 4 is in communication connection with the task matching system 5, and the central processing module 2 transmits the data information of the staff to the task matching system 5 through the task identification system 4;
the task matching system 5 comprises a task segmentation module 14, a staff capability evaluation module 15 and a capability and task fitting module 16, the task matching system 5 segments the received tasks, matches the segmented task proportion with the staff capability value from high to low according to the capability value of the staff corresponding to the task direction, and simultaneously carries out overall planning again on the tasks which cannot be completed in time by the task matching system 5;
the staff data entry module 9 collects data in the database 7, the collected content comprises past tasks of the enterprise staff, the task completion degree and the completion time, and the feedback evaluation module 10 acquires suggestions fed back by the staff.
An enterprise work task allocation system based on artificial intelligence is based on the working principle that when the enterprise work task allocation system works, a task input module 3 inputs tasks inside an enterprise, the task input module 3 transmits input task information to a central processing module 2, the central processing module 2 inputs data of employees at work and receives opinions of the employees during working, an employee data input module 9 acquires data inside a database 7, the acquired content comprises past tasks of the employees of the enterprise, task completion degree and completion time, a feedback evaluation module 10 acquires suggestions fed back by the employees, and the central processing module 2 transmits the task information to a task recognition system 4;
the task identification system 4 identifies the type of the task, the central processing module 2 transmits data information of the staff to the task matching system 5 through the task identification system 4, the task matching system 5 divides the received task, meanwhile, according to the capacity value of the staff corresponding to the task direction, the divided task proportion is matched with the capacity value of the staff from high to low, and meanwhile, the task matching system 5 carries out overall planning again on the tasks which cannot be completed in time.
Example two
As shown in fig. 1 to 5, based on the first embodiment, the task recognition system 4 includes a sequential mode task 11, a parallel mode task 12, and a pre-preparation module 13, the task recognition system 4 receives the tasks, then recognizes the types of the tasks through the sequential mode task 11 and the parallel mode task 12, and the sequential mode task 11 and the pre-preparation module 13 are in communication connection;
the staff capability evaluation module 15 scores the capabilities of the staff in different tasks through the data of the staff in the staff data entry module 9, and the scoring standards are that the task completion degree accounts for 60%, the timeliness accounts for 25%, and the enterprise investment resources account for 15%;
when the task is detected to be the sequential mode task 11, the sequential mode task 11 transmits the task mode to the task matching system 5, the task segmentation module 14 segments the task, and as the detected task is in a sequential progressive mode, the sub-tasks which are completed uniformly are integrated into a whole in the segmentation process, and the working direction of the whole task set is defined;
the ability and task fitting module 16 scores the abilities of the employees in different tasks through the employee ability evaluation module 15, selects the employees corresponding to the task direction to perform task allocation, and performs early-stage task preparation on the employees needing to be supported by the early-stage tasks through the early-stage preparation module 13;
when the task is detected to be the parallel mode task 12, the parallel mode task 12 transmits the task mode to the task matching system 5, the task is divided by the task dividing module 14, and the task dividing module 14 accurately divides the task by comparing the past task data in the database 7 in the task dividing process;
the task segmentation module 14 gathers the tasks in the same working direction after segmentation, and then selects the staff with the highest fitting degree through the capability and task fitting module 16, and performs task distribution according to the sequence from top to bottom.
The design in the embodiment is that during work, the task recognition system 4 receives the tasks, then recognizes the types of the tasks through the sequential mode task 11 and the parallel mode task 12, and the staff capacity evaluation module 15 scores the capacities of the staff in different tasks through the data of the staff in the staff data entry module 9, wherein the scoring standards are that the task completion degree accounts for 60%, the timeliness accounts for 25%, and the enterprise investment resources account for 15%;
when the task is detected to be the sequential mode task 11, the sequential mode task 11 transmits the task mode to the task matching system 5, the task segmentation module 14 segments the task, and as the detected task is sequential progressive, the segmented tasks are integrated into a whole in the segmentation process, and the working direction of the whole task set is defined, the capability and task attachment module 16 scores the capabilities of the staff in different tasks through the staff capability evaluation module 15, selects the staff in the corresponding task direction to distribute the task, and distributes the tasks from high to low according to the occupation ratio and the score in the task, and performs early task preparation on the staff needing to be supported by the early task through the early preparation module 13;
when the task is detected to be the parallel mode task 12, the parallel mode task 12 transmits the task mode to the task matching system 5, the task is divided by the task dividing module 14, the task dividing module 14 accurately divides the task by comparing the past task data in the database 7 in the task dividing process, the task dividing module 14 gathers the divided tasks in the same working direction, and then the task fitting module 16 selects the staff with the highest fitting degree through the capacity, and performs task distribution according to the sequence from the high task proportion to the low task proportion.
EXAMPLE III
As shown in fig. 1 to 5, based on the first or second embodiment, the central processing module 2 is in communication connection with the supervisory system 8, the supervisory system 8 includes a work log summarizing module 17, a money tracking module 18 and a right and responsibility corresponding module 19, the supervisory system 8 summarizes the daily work logs and money of the employees, and simultaneously, according to different assigned tasks, the authority of the tasks corresponds to the employees;
the work log summarizing module 17 summarizes the work logs of the employees distributed to the tasks, the money tracking module 18 tracks the money consumed in the task developing process, the authority corresponding module 19 establishes different authorities for the employees according to different task distributions of the employees, the external of the task system 1 is in communication connection with the cloud storage module 6, and the cloud storage module 6 is in communication connection with the database 7.
In this embodiment, during work, the work log collecting module 17 collects the work logs of the employees assigned to the tasks, the money tracking module 18 tracks the money consumed in the task developing process, the authority corresponding module 19 formulates different authorities for the employees according to different assignment of the tasks of the employees, and meanwhile, the database 7 synchronizes the data inside the task system 1 in real time through the cloud storage module 6, so as to facilitate the pursuit of later-period responsibility.
The above description is only for the preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art should be considered to be within the technical scope of the present invention, and the technical solutions and the inventive concepts thereof according to the present invention should be equivalent or changed within the scope of the present invention.
Claims (9)
1. The enterprise work task distribution system based on artificial intelligence comprises a task system (1) and a database (7), and is characterized in that the task system (1) comprises a central processing module (2), a task entry module (3), a task recognition system (4), a task matching system (5), a cloud storage module (6), a database (7) and a supervision system (8), the external of the task system (1) is in communication connection with the cloud storage module (6), the cloud storage module (6) is in communication connection with the database (7), the task entry module (3) enters tasks inside an enterprise, and the task entry module (3) transmits entered task information to the central processing module (2);
the central processing module (2) comprises a staff data entry module (9) and a feedback evaluation module (10), the central processing module (2) enters data of employees and receives opinions of the employees during working, the central processing module (2) transmits task information to the task identification system (4), the task identification system (4) identifies types of tasks, the task identification system (4) is in communication connection with the task matching system (5), and the central processing module (2) transmits data information of the employees to the task matching system (5) through the task identification system (4);
the task matching system (5) internally comprises a task segmentation module (14), a staff capability evaluation module (15) and a capability and task fitting module (16), the task matching system (5) segments the received tasks, matches the segmented task proportion with the staff capability value from high to low according to the capability value of the staff corresponding to the task direction, and simultaneously carries out overall planning again on the tasks which cannot be completed in time by the task matching system (5);
the central processing module (2) is in communication connection with the supervision system (8), the supervision system (8) internally comprises a work log collecting module (17), a money tracking module (18) and a right and responsibility corresponding module (19), the supervision system (8) collects the daily work logs and money of the staff, and simultaneously, the authority of the task corresponds to the staff according to different distributed tasks.
2. The enterprise work task allocation system based on artificial intelligence is characterized in that the staff member data entry module (9) collects data inside the database (7), the collected data comprises past tasks of enterprise staff members and task completion degree and completion time, and the feedback evaluation module (10) acquires suggestions fed back by the staff members.
3. An artificial intelligence based enterprise work task distribution system according to claim 2, wherein the task recognition system (4) internally comprises a sequential mode task (11), a parallel mode task (12) and a pre-preparation module (13), the task recognition system (4) receives the tasks and then recognizes the type of the tasks through the sequential mode task (11) and the parallel mode task (12), and the sequential mode task (11) and the pre-preparation module (13) are in communication connection.
4. The artificial intelligence based enterprise work task allocation system according to claim 3, wherein the staff capacity evaluation module (15) scores the staff capacity in different tasks according to the staff data in the staff data entry module (9), and the scoring criteria are that the task completion degree accounts for 60%, the timeliness accounts for 25%, and the enterprise investment resources account for 15%.
5. The system for distributing the enterprise work tasks based on the artificial intelligence as claimed in claim 4, wherein when the task is detected to be the sequential pattern task (11), the sequential pattern task (11) transmits the task pattern to the task matching system (5), the task segmentation module (14) segments the task, and since the detected task is sequential progressive, the segmented tasks which are completed uniformly are integrated in the segmentation process, and the working direction of the integrated task set is defined.
6. The system for distributing the enterprise work tasks based on the artificial intelligence as claimed in claim 5, wherein the ability and task matching module (16) selects the employees corresponding to the task direction for task distribution through the scoring of the abilities of the employees in different tasks in the employee ability evaluation module (15), and performs the previous task preparation for the employees needing the support of the previous tasks through the previous preparation module (13).
7. The system for distributing the enterprise work tasks based on the artificial intelligence as claimed in claim 6, wherein when the task is detected to be the parallel mode task (12), the parallel mode task (12) transmits the task mode to the task matching system (5), the task is divided by the task dividing module (14), and the task dividing module (14) precisely divides the task by comparing the past task data in the database (7) during the task dividing process.
8. The system for distributing the enterprise work tasks based on the artificial intelligence as claimed in claim 7, wherein the task segmentation module (14) collects the tasks which are segmented and located in the same work direction, and then the task fitting module (16) selects the staff with the highest fitting degree through the capacity, and distributes the tasks in the order from top to bottom.
9. The system for distributing the enterprise work tasks based on the artificial intelligence according to claim 1, wherein the work log collecting module (17) collects the work logs of the employees distributed to the tasks, the money tracking module (18) tracks the money consumed in the task developing process, and the authority corresponding module (19) establishes different authorities for the employees according to different task distributions of the employees.
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115204849A (en) * | 2022-09-15 | 2022-10-18 | 泰盈科技集团股份有限公司 | Enterprise human resource management method and system based on artificial intelligence |
| CN115630810A (en) * | 2022-10-17 | 2023-01-20 | 南京同科科技发展有限公司 | Cross-platform data sharing system |
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115204849A (en) * | 2022-09-15 | 2022-10-18 | 泰盈科技集团股份有限公司 | Enterprise human resource management method and system based on artificial intelligence |
| CN115204849B (en) * | 2022-09-15 | 2023-11-03 | 泰盈科技集团股份有限公司 | Enterprise human resource management method and system based on artificial intelligence |
| CN115630810A (en) * | 2022-10-17 | 2023-01-20 | 南京同科科技发展有限公司 | Cross-platform data sharing system |
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