Delay risk prediction apparatus, delay risk prediction method, and program

Abstract

To provide a technology for assigning workers in consideration of a delay risk when work is performed over a long period.SOLUTION: An estimation unit estimates the number of people required to execute work based on contents of the work and a schedule of the work, a selection unit selects one or more workers corresponding to the number of people required to execute the work from among a plurality of candidates, a calculation unit calculates the magnitude of a risk of the work being delayed when the selected one or more workers execute the work, and an output unit outputs information indicating the magnitude of the risk for the selected one or more workers.SELECTED DRAWING: Figure 3

Description

[Technical field]

[0001] The present disclosure relates to a delay risk prediction device, a delay risk prediction method, and a program, and in particular to a delay risk prediction device, a delay risk prediction method, and a program that assign tasks to workers according to the content of the tasks. [Background technology]

[0002] Related technology involves the development of tools that automatically assign tasks to workers (e.g., designers, builders, maintenance workers, factory workers) based on the content of the work (e.g., the type of work, the technology required for the work, the work load).

[0003] Furthermore, Patent Document 1 describes scheduling work so as to satisfy the required workload of a task, taking into consideration the processing efficiency of each worker (agent). [Prior art documents] [Patent documents]

[0004] [Patent Document 1] JP 2007-142502 A Summary of the Invention [Problem to be solved by the invention]

[0005] Related technologies are suitable for one-off or short-term work. On the other hand, when work is carried out over a long period of time, delays are likely to occur due to various factors. Therefore, existing tools are not suitable for construction work, which is carried out over a long period of time.

[0006] The present disclosure has been made in consideration of the above-mentioned problems, and has as its purpose to provide a technique for assigning tasks to workers while taking into account the risk of delays when work is performed over a long period of time. [Means for solving the problem]

[0007] A delay risk prediction device according to one embodiment of the present disclosure includes an estimation means for estimating the number of people required to complete a task based on the content of the task and the schedule of the task, a selection means for selecting one or more workers equivalent to the number of people required to complete the task from among a plurality of candidates, a calculation means for calculating the magnitude of risk that the task will be delayed if the selected one or more workers complete the task, and an output means for outputting information indicating the calculated magnitude of the risk.

[0008] In a delay risk prediction method according to one embodiment of the present disclosure, a computer estimates the number of people required to complete a task based on the content of the task and the schedule of the task, selects one or more workers equivalent to the number of people required to complete the task from among multiple candidates, calculates the magnitude of risk that the task will be delayed if the selected one or more workers complete the task, and outputs information indicating the calculated magnitude of the risk.

[0009] A program according to one embodiment of the present disclosure causes a computer to execute the following processes: estimating the number of people required to complete a task based on the content of the task and a schedule for the task; selecting one or more workers equivalent to the number of people required to complete the task from among multiple candidates; calculating the magnitude of risk that the task will be delayed if the selected one or more workers complete the task; and outputting information indicating the calculated magnitude of the risk. Effect of the Invention

[0010] According to one aspect of the present disclosure, tasks can be assigned to workers taking into consideration the risk of delays when work is performed over a long period of time. [Brief description of the drawings]

[0011] [Figure 1] 1 is a diagram illustrating an example of a delay risk prediction system including a delay risk prediction device according to an embodiment. [Diagram 2] 2 is a diagram illustrating an example of data stored in a worker database provided in the delay risk prediction system illustrated in FIG. 1. FIG. [Diagram 3] 1 is a block diagram showing a configuration of a delay risk prediction device according to an embodiment. FIG. [Figure 4] 4 is a flowchart showing the operation of the delay risk prediction device according to one embodiment. [Diagram 5] 1 is a block diagram showing a configuration of a delay risk prediction device according to an embodiment. FIG. [Figure 6] 4 is a flowchart showing the operation of the delay risk prediction device according to one embodiment. [Figure 7] FIG. 2 is a diagram illustrating an example of a hardware configuration of a delay risk prediction device according to an embodiment. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0012] Hereinafter, embodiments of the present disclosure will be described with reference to the drawings.

[0013] (Delay Risk Prediction System 1) Fig. 1 is a diagram illustrating an example of a delay risk prediction system 1 including any of delay risk prediction devices 10, 20 (Fig. 3, Fig. 5) according to the below-described embodiment 1 or 2. The delay risk prediction system 1 provides a service of assigning a task to a worker according to the content and schedule of the task requested by a user.

[0014] As shown in Fig. 1, the delay risk prediction system 1 includes a delay risk prediction device 10 (20), a user terminal 100, a worker terminal 200, and a worker database 300. Here, the "delay risk prediction device 10 (20)" means any of the delay risk prediction devices 10, 20 (Figs. 3 and 5) according to the first and second embodiments. The delay risk prediction device 10 (20), the user terminal 100, the worker terminal 200, and the worker database 300 can communicate with each other through any communication network.

[0015] The user terminal 100 is used by a user to input information related to the work requested by the user, such as the content of the work and the schedule of the work.

[0016] The worker terminal 200 is used by the worker to receive instructions for the work that the worker is to undertake. The worker also inputs information indicating the worker's own skill level (e.g., whether or not the worker has a qualification related to the work) into the worker terminal 200. In addition, after the work, the worker inputs a work completion report into the worker terminal 200.

[0017] The worker database 300 stores information about people who can be entrusted with a task (hereinafter, referred to as candidates).

[0018] The delay risk prediction device 10 (20) acquires information about the work requested by the user, which is input to the user terminal 100. The information about the work includes information indicating the content of the work and the schedule of the work.

[0019] The delay risk prediction device 10 (20) estimates the number of people required to complete a task based on the content and schedule of the task. The delay risk prediction device 10 (20) selects one or more workers corresponding to the number of people required to complete the task from among multiple candidates registered in the worker database 300 (FIG. 2).

[0020] The delay risk prediction device 10 (20) calculates the magnitude of risk that a task will be delayed when one or more workers perform a task based on data (particularly the candidate's work track record and the candidate's skill level) stored in the worker database 300. An example of an index showing the magnitude of risk that a task will be delayed will be described later.

[0021] Then, the delay risk prediction device 10 (20) outputs information indicating the magnitude of risk for the selected one or more workers.

[0022] The delay risk prediction device 10 (20) will be described in detail in the following first and second embodiments.

[0023] (An example of the worker database 300) Fig. 2 is a diagram illustrating an example of data stored in worker database 300. In the example illustrated in Fig. 2, data such as the work performance of candidates and the skill levels of the candidates are stored in worker database 300 in association with candidate IDs for identifying the candidates.

[0024] In one example, the candidate's work performance includes the work the candidate has performed in the past and the number of times the candidate has performed the work, and the candidate's skill level indicates whether the candidate has a qualification related to the work.

[0025] 2 is merely an example. In another example, in the worker database 300, in addition to the work track record of the candidate and the skill level of the candidate, attributes of the candidate may also be linked to the candidate ID.

[0026] [Embodiment 1] The first embodiment will be described with reference to FIG. 3 and FIG.

[0027] (Configuration of delay risk prediction device 10) Fig. 3 is a block diagram showing the configuration of the delay risk prediction device 10 according to the embodiment 1. As shown in Fig. 3, the delay risk prediction device 10 includes an estimation unit 11, a selection unit 12, a calculation unit 13, and an output unit 14.

[0028] The estimation unit 11 estimates the number of people required to perform a task based on the content of the task and the schedule of the task. The estimation unit 11 is an example of an estimation means.

[0029] For example, the estimation unit 11 acquires information including the content of the work and the schedule of the work, which is input by the user terminal 100. The estimation unit 11 also calculates the total man-hours according to the content of the work. The estimation unit 11 estimates the number of people required to complete the work from the calculated total man-hours and the schedule of the work. Specifically, the estimation unit 11 can estimate the number of people required to complete the work by dividing the total man-hours by the number of days available for work. The estimation unit 11 outputs information indicating the number of people required to complete the work to the selection unit 12.

[0030] The selection unit 12 selects one or more workers corresponding to the number of people required to carry out the work from among a plurality of candidates. The selection unit 12 is an example of a selection means.

[0031] For example, the selection unit 12 receives information indicating the number of people required to perform the work from the estimation unit 11. The selection unit 12 refers to the worker database 300 (FIG. 2) and selects, from among the multiple candidates, one or more workers corresponding to the number of people required to perform the work. Specifically, the selection unit 12 can select, as a worker, a candidate from among the multiple candidates who has an available time slot in the schedule for the work date.

[0032] The selection unit 12 outputs information indicating the selected one or more workers to the calculation unit 13.

[0033] The calculation unit 13 calculates a delay risk value (unitless) which is an index showing the magnitude of the risk that the work will be delayed. The delay risk value indicates the magnitude of the risk that the work will be delayed when the selected one or more workers perform the work. The calculation unit 13 is an example of a calculation means.

[0034] For example, the calculation unit 13 receives information indicating one or more workers selected by the selection unit 12. The calculation unit 13 refers to the worker database 300 and calculates a delay risk value for each of the selected one or more workers based on at least one of the work track record of the worker and the skill level of the worker.

[0035] In one example, if the cumulative number of times that the worker has performed a task in the past is 10 or more, the calculation unit 13 calculates that the delay risk value is 0. If the cumulative number of times that the worker has performed a task in the past is 5 or more and less than 10, the calculation unit 13 calculates that the delay risk value is 10. If the cumulative number of times that the worker has performed a task in the past is 4 or less, the calculation unit 13 calculates that the delay risk value is 30.

[0036] In another example, when the worker has a qualification related to the work content, the calculation unit 13 calculates that the delay risk value is 0. On the other hand, when the worker does not have a qualification related to the work content, the calculation unit 13 calculates that the delay risk value is 20.

[0037] In yet another example, the calculation unit 13 calculates the delay risk based on both the track record of the work performed by the worker and the skill level of the worker. Specifically, as in the above example, the calculation unit 13 calculates a delay risk value based on the track record of the work performed by the worker and a delay risk value based on the skill level of the worker, and adds up the calculation results.

[0038] The calculation unit 13 outputs information indicating the calculated delay risk value to the output unit 14.

[0039] The output unit 14 outputs information indicating the magnitude of risk for the selected one or more workers. The output unit 14 is an example of an output means.

[0040] For example, the output unit 14 receives information indicating the delay risk value calculated by the calculation unit 13. The output unit 14 outputs information indicating the magnitude of risk for the selected one or more workers. In one example, the output unit 14 outputs information indicating the sum of the delay risk values ​​for the selected one or more workers to the user terminal 100 (FIG. 1).

[0041] (Operation of the delay risk prediction device 10) FIG. 4 is a flowchart showing the operation of the delay risk prediction device 10 according to the first embodiment.

[0042] 4, the estimation unit 11 estimates the number of people required to perform a task based on the content and schedule of the task (S101). In one example, the estimation unit 11 can use information indicating the content and schedule of the task input to the user terminal 100.

[0043] The selection unit 12 refers to the worker database 300 (FIG. 2) and selects, from among a plurality of candidates, one or a plurality of workers equivalent to the number of people required to carry out the work (S102).

[0044] The calculation unit 13 calculates the magnitude of the risk of the work being delayed when the selected one or more workers perform the work (S103). In one example, the calculation unit 13 can use information indicating the track record of the work by the workers and information indicating the skill level of the workers, which are stored in the worker database 300 (FIG. 2).

[0045] The output unit 14 outputs information indicating the magnitude of risk for the selected one or more workers (S104). In one example, the output unit 14 outputs information indicating the sum of the delay risk values ​​calculated for each of the selected one or more workers.

[0046] This is the end of the operation of the delay risk prediction device 10 according to the first embodiment.

[0047] (Effects of this embodiment) According to the configuration of this embodiment, the estimation unit 11 estimates the number of people required to complete a task based on the content and schedule of the task. The selection unit 12 selects one or more workers corresponding to the number of people required to complete the task from among multiple candidates. The calculation unit 13 calculates the magnitude of risk that the task will be delayed if the selected one or more workers complete the task. The output unit 14 outputs information indicating the magnitude of risk for the selected one or more workers.

[0048] This makes it possible to visualize the risk of delay when a worker carries out a task, allowing service users to assign tasks to workers while taking into account the risk of delay when the task is carried out over a long period of time.

[0049] [Embodiment 2] A second embodiment will be described with reference to Fig. 5 and Fig. 6. In the second embodiment, a configuration will be described in which an error is output when the sum of the delay risk values ​​for one or more workers exceeds a predetermined value.

[0050] In the second embodiment, for components common to the first embodiment, the description in the first embodiment will be referred to, and overlapping descriptions will be omitted.

[0051] (Configuration of delay risk prediction device 20) Fig. 5 is a block diagram showing the configuration of a delay risk prediction device 20 according to the present embodiment 2. As shown in Fig. 5, the delay risk prediction device 20 includes an estimation unit 11, a selection unit 12, a calculation unit 13, and an output unit 24. The output unit 24 is an example of an output means.

[0052] The process executed by the output unit 24 differs depending on whether the sum of the delay risk values ​​for one or more workers is equal to or less than a predetermined value or exceeds the predetermined value. Specifically, when the sum of the delay risk values ​​calculated for each of the one or more workers is equal to or less than a predetermined value, the output unit 24 outputs information indicating the magnitude of risk for the selected one or more workers. On the other hand, when the sum of the delay risk values ​​for one or more workers exceeds the predetermined value, the output unit 24 outputs an error.

[0053] Alternatively, when the sum of the delay risk values ​​for one or more workers exceeds a predetermined value, the output unit 24 may output information indicating that it is impossible to assign the task to a worker.

[0054] (Operation of the delay risk prediction device 20) FIG. 6 is a flowchart showing the operation of the delay risk prediction device 20 according to the second embodiment.

[0055] 6, the estimation unit 11 estimates the number of people required to perform a task based on the content and schedule of the task (S201). In one example, the estimation unit 11 can use information indicating the content and schedule of the task input to the user terminal 100.

[0056] The selection unit 12 refers to the worker database 300 (FIG. 2) and selects, from among a plurality of candidates, one or a plurality of workers equivalent to the number of people required to carry out the work (S202).

[0057] The calculation unit 13 calculates the magnitude of the risk of the work being delayed when the selected one or more workers perform the work (S203). In one example, the calculation unit 13 can use information indicating the track record of the work by the workers and information indicating the skill level of the workers, which are stored in the worker database 300 (FIG. 2).

[0058] The output unit 24 determines whether the sum of the delay risk values ​​for the one or more workers selected by the selection unit 12 is equal to or less than a predetermined value (S204).

[0059] If the sum of the delay risk values ​​for one or more workers is equal to or less than the predetermined value (Yes in S204), the output unit 24 outputs information indicating the magnitude of the risk for the selected one or more workers (S205A). In one example, the output unit 24 outputs information indicating the sum of the delay risk values ​​calculated for each of the selected one or more workers.

[0060] On the other hand, if the sum of the delay risk values ​​for one or more workers is less than or equal to the predetermined value (No in S204), the output unit 24 outputs information indicating the magnitude of risk for the selected one or more workers (S205B).

[0061] This is the end of the operation of the delay risk prediction device 20 according to the second embodiment.

[0062] (Effects of this embodiment) According to the configuration of this embodiment, the estimation unit 11 estimates the number of people required to complete a task based on the content and schedule of the task. The selection unit 12 selects one or more workers corresponding to the number of people required to complete the task from among multiple candidates. The calculation unit 13 calculates the magnitude of risk that the task will be delayed if the selected one or more workers complete the task. The output unit 24 outputs information indicating the magnitude of risk for the selected one or more workers.

[0063] This makes it possible to visualize the risk of delay when a worker carries out a task, allowing service users to assign tasks to workers while taking into account the risk of delay when the task is carried out over a long period of time.

[0064] Furthermore, according to the configuration of this embodiment, when the sum of the delay risk values ​​for one or more workers is equal to or less than a predetermined value, the output unit 24 outputs information indicating the magnitude of risk for the selected one or more workers. On the other hand, when the sum of the delay risk values ​​for one or more workers exceeds a predetermined value, the output unit 24 outputs an error. This allows the user of the service to carefully consider whether to assign a worker when the delay risk is too high.

[0065] (Hardware configuration of delay risk prediction devices 10 and 20) Each component of the delay risk prediction devices 10, 20 (FIGS. 3, 5) described in the first and second embodiments is shown as a functional block. Some or all of these components are realized by an information processing device as shown in FIG. 7. FIG. 7 is a block diagram showing an example of the hardware configuration of the information processing device.

[0066] 7, the computer 110 includes a CPU (Central Processing Unit) 111, a main memory 112, a storage device 113, an input interface 114, a display controller 115, a data reader / writer 116, and a communication interface 117. These components are connected to each other via a bus 121 so as to be able to communicate data with each other. Note that the computer 110 may include a GPU (Graphics Processing Unit) or an FPGA (Field-Programmable Gate Array) in addition to the CPU 111 or instead of the CPU 111.

[0067] The CPU 111 loads the programs (codes) in this embodiment stored in the storage device 113 into the main memory 112 and executes them in a predetermined order to perform various calculations. The main memory 112 is typically a volatile storage device such as a dynamic random access memory (DRAM). The programs in this embodiment are provided in a state stored in a computer-readable recording medium 120. The programs in this embodiment may be distributed over the Internet connected via a communication interface 117.

[0068] Specific examples of the storage device 113 include a hard disk drive and a semiconductor storage device such as a flash memory. The input interface 114 mediates data transmission between the CPU 111 and input devices 118 such as a keyboard and a mouse. The display controller 115 is connected to a display device 119 and controls the display on the display device 119.

[0069] Data reader / writer 116 mediates data transmission between CPU 111 and recording medium 120, reads programs from recording medium 120, and writes processing results in computer 110 to recording medium 120. Communication interface 117 mediates data transmission between CPU 111 and other computers.

[0070] Specific examples of recording medium 120 include general-purpose semiconductor storage devices such as CF (Compact Flash (registered trademark)) and SD (Secure Digital), magnetic recording media such as a flexible disk, or optical recording media such as a CD-ROM (Compact Disk Read Only Memory).

[0071] A part or all of the above-described embodiments can be described as, but is not limited to, the following supplementary notes.

[0072] (Appendix 1) A prediction means for predicting the number of people required to perform the work based on the content of the work and the schedule of the work; A selection means for selecting, from among a plurality of candidates, one or a plurality of workers corresponding to the number of people required to perform the work; A calculation means for calculating a magnitude of a risk that the work will be delayed if the selected one or more workers perform the work; and an output means for outputting information indicating the magnitude of the calculated risk. Delay risk prediction device.

[0073] (Appendix 2) The calculation means calculates a delay risk value indicating the magnitude of the risk that the work will be delayed when the one or more workers perform the work, based on the track record of the work by the one or more workers. 2. A delay risk prediction device according to claim 1.

[0074] (Appendix 3) The calculation means calculates a delay risk value indicating the magnitude of the risk that the work will be delayed when the one or more workers perform the work, based on the skill level of the one or more workers. 2. A delay risk prediction device according to claim 1.

[0075] (Appendix 4) The selection means selects the one or more workers so that the delay risk value is equal to or less than a predetermined value. 4. A delay risk prediction device according to claim 2 or 3.

[0076] (Appendix 5) The output means further outputs information indicating the one or more workers selected from the plurality of candidates. 2. A delay risk prediction device according to claim 1.

[0077] (Appendix 6) When the delay risk value exceeds a predetermined value, the output means outputs an error. 4. A delay risk prediction device according to claim 2 or 3.

[0078] (Appendix 7) The computer Estimating the number of people required to perform the work based on the work content and the schedule of the work; Selecting one or more workers from among the multiple candidates, the number of workers corresponding to the number of people required to perform the work; Calculating the magnitude of a risk that the work will be delayed if the selected one or more workers perform the work; Output information indicating the magnitude of the calculated risk. Delay risk prediction method.

[0079] (Appendix 8) The computer, Calculating a delay risk value indicating the magnitude of the risk that the work will be delayed when the one or more workers perform the work based on the performance of the work by the one or more workers 8. A method for predicting a risk of delay according to claim 7.

[0080] (Appendix 9) The computer, Calculating a delay risk value indicating the magnitude of the risk that the work will be delayed when the one or more workers perform the work based on the skill level of the one or more workers 8. A method for predicting a risk of delay according to claim 7.

[0081] (Appendix 10) The computer, The one or more workers are selected so that the delay risk value is equal to or less than a predetermined value. 10. The method for predicting risk of delay according to claim 8 or 9.

[0082] (Appendix 11) The computer, and further outputting information indicating the one or more workers selected from the plurality of candidates. 8. A method for predicting a risk of delay according to claim 7.

[0083] (Appendix 12) If the delay risk value exceeds a predetermined value, The computer, Print an error 11. The method for predicting risk of delay according to claim 9 or 10.

[0084] (Appendix 13) A process of estimating the number of people required to perform the work based on the content of the work and the schedule of the work; A process of selecting one or more workers corresponding to the number of people required to perform the work from among a plurality of candidates; A process of calculating a magnitude of a risk that the work will be delayed if the selected one or more workers perform the work; A process of outputting information indicating the magnitude of the calculated risk; A program for causing a computer to execute the following.

[0085] (Appendix 14) The computer includes: A process of calculating a delay risk value indicating the magnitude of the risk that the work will be delayed when the one or more workers perform the work, based on the performance of the work by the one or more workers. The program according to claim 13, characterized in that it causes the program to execute the above steps.

[0086] (Appendix 15) The computer includes: A process of calculating a delay risk value indicating the magnitude of the risk that the work will be delayed when the one or more workers perform the work, based on the skill level of the one or more workers. The program according to claim 13, characterized in that it causes the program to execute the above steps.

[0087] (Appendix 16) The computer includes: A process of selecting the one or more workers so that the delay risk value is equal to or less than a predetermined value. 16. The program according to claim 14 or 15,

[0088] (Appendix 17) The computer includes: and outputting information indicating the one or more workers selected from the plurality of candidates. The program according to claim 13, characterized in that it causes the program to execute the above steps.

[0089] (Appendix 18) If the delay risk value exceeds a predetermined value, The computer includes: Error output process 16. The program according to claim 14 or 15,

[0090] The present disclosure has been described above with reference to several embodiments. However, the present disclosure is not limited to the above embodiments. Each embodiment can be appropriately combined with other embodiments. In addition, various modifications that can be understood by a person skilled in the art can be made to the configurations and details of the above embodiments within the scope of the present disclosure. [Industrial Applicability]

[0091] The present disclosure can be used by businesses that provide services to assign services to workers. [Explanation of symbols]

[0092] 1. Delay risk prediction system 10 Delay risk prediction device 11 Guessing part 12 Selection section 13 Calculation section 14 Output section 20 Delay risk prediction device 24 Output section 100 User terminals 200 Worker terminal 300 Worker Database

Claims

1. A prediction means for predicting the number of people required to perform the work based on the content of the work and the schedule of the work; a selection means for selecting, from among a plurality of candidates, one or a plurality of workers corresponding to the number of people required to perform the work; A calculation means for calculating a magnitude of a risk that the work will be delayed if the selected one or more workers perform the work; and an output means for outputting information indicating the magnitude of the calculated risk. Delay risk prediction device.

2. The calculation means calculates a delay risk value indicating the magnitude of the risk that the work will be delayed when the one or more workers perform the work, based on the track record of the work by the one or more workers.

2. The delay risk prediction device according to claim 1 .

3. The calculation means calculates a delay risk value indicating the magnitude of the risk that the work will be delayed when the one or more workers perform the work, based on the skill level of the one or more workers.

2. The delay risk prediction device according to claim 1 .

4. The selection means selects the one or more workers so that the delay risk value is equal to or less than a predetermined value.

4. The delay risk prediction device according to claim 2 or 3.

5. The output means further outputs information indicating the one or more workers selected from the plurality of candidates.

2. The delay risk prediction device according to claim 1 .

6. When the delay risk value exceeds a predetermined value, the output means outputs an error.

4. The delay risk prediction device according to claim 2 or 3.

7. The computer Estimating the number of people required to perform the work based on the work content and the schedule of the work; Selecting one or more workers corresponding to the number of people required to perform the work from among the multiple candidates; Calculating a magnitude of a risk that the work will be delayed if the selected one or more workers perform the work; Output information indicating the magnitude of the calculated risk. Delay risk prediction method.

8. A process of estimating the number of people required to perform the work based on the content of the work and the schedule of the work; A process of selecting one or more workers corresponding to the number of people required to perform the work from among a plurality of candidates; A process of calculating a magnitude of a risk that the work will be delayed if the one or more selected workers perform the work; A process of outputting information indicating the magnitude of the calculated risk; A program for causing a computer to execute the following.

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