Task flow mechanism creation method and system based on state machine template

Abstract

The invention relates to the technical field of task flow mechanism establishment, and particularly discloses a task flow mechanism establishment method and system based on a state machine template. According to task overall information, node topological information is extracted by integrating task node information and directed edge information, so that a task flow structure is concluded, different types of nodes and characteristics of the nodes in the task circulation process are defined, and then the task flow is obtained according to task detail information corresponding to each task node in the task flow node topological information. In combination with previously determined multi-person cooperation judgment information, cooperative operation node information is accurately extracted from numerous node topology information, and then corresponding task allocation strategy information is formulated for each piece of cooperative operation node information, so that orderly and efficient cooperative operation is ensured, and the task allocation efficiency is improved. And then calculating a feasibility value based on progress tracking information obtained by the node circulation condition information, judging whether a task flow mechanism is judged through the feasibility value, and re-optimizing the task flow mechanism according to a judgment result.

Description

Technical Field

[0001] The present invention relates to the technical field of task flow mechanism construction, and in particular to a method and system for creating a task flow mechanism based on a state machine template. Background Art

[0002] The task flow mechanism is a systematic method for organizing, coordinating and managing the task execution process. It ensures that tasks can be completed efficiently according to predetermined rules and sequences by decomposing, sorting, allocating and monitoring tasks. The task flow mechanism is like a detailed task map, which not only specifies the path from the beginning to the end of the task, but also clarifies the specific operations, participants, required resources and the relationship between various tasks at each stage.

[0003] In today's working environment, task processes are highly diverse and complex, and current task flow software can only support relatively simple and conventional task flow models. For those workflows involving multiple departments, multiple business intersections, and complex logical relationships, its design capabilities are insufficient. Existing task flow software cannot accurately build a process model that meets such complex scenarios, which leads to confusion, omissions, or duplication of work during task execution, seriously affecting work efficiency and the smooth progress of the project. Summary of the invention

[0004] The purpose of the present invention is to provide a method and system for creating a task flow mechanism based on a state machine template to solve the technical problems raised in the above background technology.

[0005] To achieve the above object, the present invention provides the following technical solutions:

[0006] A method for creating a task flow mechanism based on a state machine template, comprising:

[0007] Obtaining overall task information, and obtaining multiple task node information and multiple directed edge information according to the overall task information;

[0008] Acquire node topology information according to each of the task node information and each of the directed edge information, wherein the node topology information includes fork node information, summary node information, parallel node information and trunk node information;

[0009] Obtaining comprehensive task estimation information, and obtaining multi-person collaboration determination information based on the comprehensive task estimation information;

[0010] Acquire task detail information corresponding to each task node according to the task flow node topology information, and extract multiple collaboratively operable node information from multiple node topology information according to each of the task detail information and multi-person collaboration determination information;

[0011] Acquire corresponding collaborative operation boundary information according to each collaborative operation node information, and acquire task allocation strategy information corresponding to the collaborative operation node according to each collaborative operation boundary information;

[0012] Acquire multiple task path information according to the multiple task flow node topology information, and acquire multiple node flow condition information according to each of the task path information, wherein the multiple task path information includes trunk task information and branch task information;

[0013] Acquire progress tracking information according to the task allocation strategy information and the node flow condition information, and calculate a feasibility value according to the progress tracking information;

[0014] Determining whether the feasibility value is greater than an expected value;

[0015] If the feasibility value is greater than the expected value, the task flow mechanism is determined to be feasible;

[0016] If the feasibility value is not greater than the expected value, the task flow mechanism is determined to be infeasible. At this time, the process returns to the step of obtaining the comprehensive estimated task information, and adjusts the multi-person collaboration determination information according to the comprehensive estimated task information until the task flow mechanism is feasible.

[0017] Preferably, the step of acquiring node topology information according to each task node information and each directed edge information comprises:

[0018] Acquire corresponding task dependency information according to each of the task node information, and acquire task auxiliary process information according to each of the task dependency information;

[0019] Obtaining corresponding task sequence information according to each of the directed edge information, and obtaining task core process information according to each of the task sequence information;

[0020] Acquire the backbone node information according to the task core process information and the task auxiliary process information;

[0021] Acquire task branch conversion information and task parallelism information according to the task auxiliary process information, and acquire branch node information and summary node information according to the task branch conversion information;

[0022] Parallel node information is acquired according to the task parallelism information.

[0023] Preferably, the step of extracting a plurality of collaboratively operable node information from a plurality of node topology information according to each of the task details information and the multi-person collaboration determination information comprises:

[0024] Obtaining element quantification value information corresponding to each task node according to each of the task details information, wherein the element quantification value information includes a task intensity value, a skill diversity value, and a resource requirement value;

[0025] Acquire task attribute range information of historical tasks, wherein the task attribute range information includes task intensity range information, skill diversity range information and resource requirement range information;

[0026] Acquire a maximum value and a minimum value of task intensity according to the task intensity range information, and acquire a maximum value and a minimum value of skill diversity according to the skill diversity range information;

[0027] The maximum resource requirement and the minimum resource requirement are obtained according to the resource requirement range information, and the single-person collaboration tendency distance value is calculated according to the task intensity value, the minimum task intensity value, the skill diversity value, the minimum skill diversity value, the resource requirement value and the minimum resource requirement value, wherein the calculation formula is:

[0028]

[0029] Among them, D 1 represents the distance value of the single-person collaboration tendency, a represents the task intensity value, and a min represents the minimum task intensity, b represents the skill diversity value, and b min represents the minimum skill diversity, c represents the resource requirement value, and c min Indicates the minimum resource requirement;

[0030] The multi-person collaboration tendency distance value is calculated according to the task intensity value, the maximum task intensity value, the skill diversity value, the maximum skill diversity value, the resource demand value and the maximum resource demand value, wherein the calculation formula is:

[0031]

[0032] Among them, D 2 represents the multi-person collaboration tendency distance value, a represents the task intensity value, a max represents the maximum task intensity, b represents the skill diversity value, and b max represents the maximum value of skill diversity, c represents the resource demand value, and c max Indicates the maximum resource demand;

[0033] The multi-person collaboration demand assessment value is calculated based on the single-person collaboration tendency distance value and the multi-person collaboration tendency distance value, where the calculation formula is:

[0034]

[0035] Among them, T represents the multi-person collaboration demand assessment value, D 1 Indicates the distance value of the single-person collaboration tendency, D 2 Indicates the multi-person collaboration demand assessment value;

[0036] Acquire collaboration benefit prediction information according to the multi-person collaboration determination information, and acquire a multi-person collaboration determination threshold according to the collaboration benefit prediction information;

[0037] Determine whether the multi-person collaboration demand assessment value is greater than the multi-person collaboration determination threshold;

[0038] If the multi-person collaboration demand evaluation value is greater than the multi-person collaboration determination threshold, the node information is determined to be collaboratively operable node information;

[0039] If the multi-person collaboration demand evaluation value is not greater than the multi-person collaboration determination threshold, it is determined that the node information is not collaboratively operable node information.

[0040] Preferably, the step of acquiring task allocation strategy information corresponding to the collaboratively operable node according to each collaborative operation boundary information comprises:

[0041] The collaborative operation boundary information includes collaborative operation target information and collaborative operation pre-information, and the corresponding sub-module element information is obtained according to each collaborative operation target information, and the corresponding pre-associated sub-module information is obtained according to each collaborative operation pre-information;

[0042] Obtain corresponding task submodule information according to each submodule element information and pre-associated submodule information, and obtain skill requirement information of each module and workload information of each module according to each task submodule information;

[0043] Acquire personnel skill matrix information and material resource information according to the resource management information, and acquire corresponding personnel allocation information according to the skill requirement information of each module and the personnel skill matrix information;

[0044] Acquire corresponding material demand information according to the workload information of each module, and acquire corresponding resource allocation information according to each material demand information and material resource information;

[0045] The task allocation strategy information is obtained based on each personnel allocation information and resource allocation information.

[0046] Preferably, the step of acquiring a plurality of node flow condition information according to each of the task path information comprises:

[0047] Acquire the first task information corresponding to each trunk node according to the trunk task information, and acquire the corresponding first task completion indicator information according to each first task information;

[0048] Acquire the second task information corresponding to each parallel node according to the branch task information, and acquire the corresponding second task completion indicator information according to each second task information;

[0049] Acquiring task switching condition information according to the plurality of first task completion indicator information and the plurality of second task completion indicator information;

[0050] According to the branch task information, the first pre-information and task flow information corresponding to each branch node are obtained, and according to each first pre-information, the corresponding first task status information is obtained.

[0051] Acquire corresponding branch path information according to each of the task flow information, and acquire branch condition information corresponding to each branch node according to each of the first task status information and each of the branch path information;

[0052] Acquire the second pre-information and summary index information corresponding to each summary node according to each branch task information, and acquire the corresponding second task status information according to each second pre-information;

[0053] Acquire summary condition information according to each summary indicator information and each second task status information;

[0054] The task gathering and dispersing condition information is obtained according to the branching condition information and the summary condition information, and the node flow information is obtained according to the task gathering and dispersing condition information and the task switching condition information.

[0055] Preferably, the step of calculating the feasibility value according to the progress tracking information comprises:

[0056] Acquire task execution progress information according to the progress tracking information, and acquire task completion ratio value according to the task execution progress information;

[0057] Obtain a first weight coefficient corresponding to the task completion ratio value;

[0058] Acquire task completion stage information according to the task execution progress information, and acquire resource consumption value according to the task completion stage information;

[0059] Obtaining a second weight coefficient corresponding to the resource consumption value;

[0060] Acquire quality inspection information according to the progress tracking information, and acquire the task achievement qualification rate according to the quality inspection information;

[0061] Obtain the third weight coefficient corresponding to the task achievement qualification rate;

[0062] Acquire task evaluation reference information according to historical data information, wherein the task evaluation reference information includes a mean value of task completion ratio, a standard deviation of task completion ratio, a mean value of resource consumption, a standard deviation of resource consumption, a mean value of qualified task results, and a standard deviation of qualified task results;

[0063] The feasibility value is calculated according to the task completion ratio value, the task completion ratio mean value, the task completion ratio standard deviation, the first weight coefficient, the resource consumption value, the resource consumption mean value, the resource consumption standard deviation, the second weight coefficient, the task result qualification rate, the task result qualification mean value, the task result qualification standard deviation and the third weight coefficient, wherein the calculation formula is:

[0064]

[0065] Among them, F represents the feasibility value, P represents the task completion ratio, μ 1 represents the mean of the task completion ratio, σ 1 represents the standard deviation of task completion ratio, ω 1 represents the first weight coefficient, R represents the resource consumption value, μ 2 represents the mean resource consumption, σ 2 represents the standard deviation of resource consumption, ω 2 represents the second weight coefficient, Q represents the task result qualification rate, μ 3 represents the qualified mean value of task results, σ 3 Indicates the task achievement qualification standard, ω 3 Represents the third weight coefficient.

[0066] The present application also provides a task flow mechanism creation system based on a state machine template, including:

[0067] A first acquisition module is used to acquire overall task information, and acquire multiple task node information and multiple directed edge information according to the overall task information;

[0068] A second acquisition module is used to acquire node topology information according to each of the task node information and each of the directed edge information, wherein the node topology information includes fork node information, summary node information, parallel node information and trunk node information;

[0069] A third acquisition module is used to acquire comprehensive task estimation information, and acquire multi-person collaboration determination information based on the comprehensive task estimation information;

[0070] An extraction module, used to obtain task detail information corresponding to each task node according to the task flow node topology information, and extract multiple collaboratively operable node information from multiple node topology information according to each of the task detail information and multi-person collaboration determination information;

[0071] A fourth acquisition module is used to acquire corresponding collaborative operation boundary information according to each collaborative operation node information, and acquire task allocation strategy information corresponding to the collaborative operation node according to each collaborative operation boundary information;

[0072] A fifth acquisition module, used to acquire multiple task path information according to the multiple task flow node topology information, and acquire multiple node flow condition information according to each of the task path information, wherein the multiple task path information includes trunk task information and branch task information;

[0073] A calculation module, used for obtaining progress tracking information according to the task allocation strategy information and the node flow condition information, and calculating a feasibility value according to the progress tracking information;

[0074] A judgment module, used to judge whether the feasibility value is greater than an expected value;

[0075] If the feasibility value is greater than the expected value, the task flow mechanism is determined to be feasible;

[0076] If the feasibility value is not greater than the expected value, the task flow mechanism is determined to be infeasible. At this time, the process returns to the step of obtaining the comprehensive estimated task information, and adjusts the multi-person collaboration determination information according to the comprehensive estimated task information until the task flow mechanism is feasible.

[0077] Preferably, the extraction module comprises:

[0078] A first acquisition unit is used to acquire the element quantization value information corresponding to each task node according to each task detail information, wherein the element quantization value information includes a task intensity value, a skill diversity value, and a resource requirement value;

[0079] A second acquisition unit is used to acquire task attribute range information of historical tasks, wherein the task attribute range information includes task intensity range information, skill diversity range information and resource requirement range information;

[0080] A third acquisition unit, configured to acquire a maximum value and a minimum value of task intensity according to the task intensity range information, and acquire a maximum value and a minimum value of skill diversity according to the skill diversity range information;

[0081] The first calculation unit is used to obtain the maximum resource demand and the minimum resource demand according to the resource demand range information, and calculate the single-person collaboration tendency distance value according to the task intensity value, the minimum task intensity value, the skill diversity value, the minimum skill diversity value, the resource demand value and the minimum resource demand value, wherein the calculation formula is:

[0082]

[0083] Among them, D 1 represents the distance value of the single-person collaboration tendency, a represents the task intensity value, and a min represents the minimum task intensity, b represents the skill diversity value, and b min represents the minimum skill diversity, c represents the resource requirement value, and c min Indicates the minimum resource requirement;

[0084] The second calculation unit is used to calculate the multi-person collaboration tendency distance value according to the task intensity value, the maximum task intensity value, the skill diversity value, the maximum skill diversity value, the resource demand value and the maximum resource demand value, wherein the calculation formula is:

[0085]

[0086] Among them, D 2 represents the multi-person collaboration tendency distance value, a represents the task intensity value, a max represents the maximum task intensity, b represents the skill diversity value, and b max represents the maximum value of skill diversity, c represents the resource demand value, and c max Indicates the maximum resource demand;

[0087] The third calculation unit is used to calculate the multi-person collaboration demand evaluation value according to the single-person collaboration tendency distance value and the multi-person collaboration tendency distance value, wherein the calculation formula is:

[0088]

[0089] Among them, T represents the multi-person collaboration demand assessment value, D 1 Indicates the distance value of the single-person collaboration tendency, D 2 Indicates the multi-person collaboration demand assessment value;

[0090] a fourth acquisition unit, configured to acquire collaboration benefit prediction information according to the multi-person collaboration determination information, and acquire a multi-person collaboration determination threshold according to the collaboration benefit prediction information;

[0091] A judgment unit, used to judge whether the multi-person collaboration demand evaluation value is greater than the multi-person collaboration judgment threshold;

[0092] If the multi-person collaboration demand evaluation value is greater than the multi-person collaboration determination threshold, the node information is determined to be collaboratively operable node information;

[0093] If the multi-person collaboration demand evaluation value is not greater than the multi-person collaboration determination threshold, it is determined that the node information is not collaboratively operable node information.

[0094] The present application also provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of the above method when executing the computer program.

[0095] The present application also provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the steps of the above method are implemented.

[0096] The beneficial effects of the present application are as follows: the present application obtains task node information and directed edge information based on the overall task information, and sorts out the tasks in an orderly manner from macro to micro, so that subsequent analysis and mechanism creation have clear and accurate original materials, and extracts node topology information by integrating task node information and directed edge information. Through this step, the task flow structure can be further summarized, and the different types of nodes and their characteristics in the task flow process can be clarified. Then, based on the task details information corresponding to each task node in the task flow node topology information, and combined with the multi-person collaboration judgment information determined previously, the collaboratively operable node information is accurately extracted from the numerous node topology information, and then for each collaboratively operable node information, the collaboratively operable node information is extracted. The corresponding task allocation strategy information is formulated based on the information, so as to ensure that the collaborative operation is carried out in an orderly and efficient manner. Then, the node flow condition information is obtained based on the topological information of multiple task flow nodes. The flow logic of the task is standardized through the node flow condition information to ensure that the task is carried out in an orderly manner according to the established process. Finally, the actual progress of the task can be grasped in real time according to the progress tracking information, and the feasibility value is calculated based on these progress data. Finally, the calculated feasibility value is compared with the expected value to determine whether the current task flow mechanism is feasible. If not, the feedback mechanism is used to return to the step of obtaining the comprehensive estimate information of the task, and the multi-person collaboration judgment information is adjusted according to the actual situation to re-optimize the task flow mechanism. BRIEF DESCRIPTION OF THE DRAWINGS

[0097] Figure 1 The figure is a schematic diagram of a method flow of an embodiment of the present application.

[0098] Figure 2 A schematic diagram of the system structure of an embodiment of the present application.

[0099] Figure 3 A schematic diagram of the internal structure of a computer device according to an embodiment of the present application.

[0100] The realization of the purpose, functional features and advantages of this application will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0101] It should be understood that the specific embodiments described herein are only used to explain the present invention, and are not used to limit the present invention.

[0102] like Figure 1-3As shown, the present application provides a method for creating a task flow mechanism based on a state machine template, including:

[0103] S1. Obtaining overall task information, and obtaining multiple task node information and multiple directed edge information according to the overall task information;

[0104] S2. Obtain node topology information according to each of the task node information and each of the directed edge information, wherein the node topology information includes fork node information, summary node information, parallel node information and trunk node information;

[0105] S3, obtaining comprehensive task estimation information, and obtaining multi-person collaboration determination information based on the comprehensive task estimation information;

[0106] S4, acquiring task details information corresponding to each task node according to the task flow node topology information, and extracting multiple collaboratively operable node information from multiple node topology information according to each of the task details information and multi-person collaboration determination information;

[0107] S5. Acquire corresponding collaborative operation boundary information according to each collaborative operation node information, and acquire task allocation strategy information corresponding to the collaborative operation node according to each collaborative operation boundary information;

[0108] S6. Acquire multiple task path information according to the multiple task flow node topology information, and acquire multiple node flow condition information according to each of the task path information, wherein the multiple task path information includes trunk task information and branch task information;

[0109] S7, acquiring progress tracking information according to the task allocation strategy information and the node flow condition information, and calculating a feasibility value according to the progress tracking information;

[0110] S8, judging whether the feasibility value is greater than the expected value;

[0111] If the feasibility value is greater than the expected value, the task flow mechanism is determined to be feasible;

[0112] If the feasibility value is not greater than the expected value, the task flow mechanism is determined to be infeasible. At this time, the process returns to the step of obtaining the comprehensive estimated task information, and adjusts the multi-person collaboration determination information according to the comprehensive estimated task information until the task flow mechanism is feasible.

[0113] As described in the above steps S1-S8, the task flow mechanism is a systematic method for organizing, coordinating and managing the task execution process. It ensures that tasks can be completed efficiently according to predetermined rules and sequences by decomposing, sorting, allocating and monitoring tasks. In today's working environment, task processes are highly diverse and complex, and current task flow software can only support relatively simple and conventional task flow models. For those workflows involving multiple departments, multiple business intersections and complex logical relationships, its design capabilities are stretched. Existing task flow software cannot accurately build a process model that meets such complex scenarios, resulting in confusion, omissions or duplication of work during task execution. , which seriously affects work efficiency and the smooth progress of the project. In the present invention, task node information and directed edge information are obtained through task overall information, wherein task overall information refers to relevant information for a comprehensive description of the task, task node information refers to information on each specific task unit obtained by decomposing the task as a whole according to a certain logic and stage, and directed edge information refers to information used to describe the sequence and dependency relationship between task nodes. Tasks are sorted out in an orderly manner from macro to micro to avoid missing important links or having a vague understanding of the task process, so that subsequent analysis and mechanism creation have clear and accurate original materials, ensuring that the entire task flow mechanism is established on the basis of a complete and reasonable task structure. By integrating task node information and directed edge information Information is obtained and node topology information is extracted. Node topology information refers to an abstract and overall structural description of all task nodes in the task process and the connection relationship between them. Through this step, the task process structure can be further summarized, and the different types of nodes and their characteristics in the task flow process are clarified, which can clearly show the complex logic of the task and the diversity of execution paths. Then, a comprehensive consideration is made based on the comprehensive estimation information of the task. Comprehensive estimation information of the task refers to the pre-estimation information of the task in multiple aspects. On this basis, multi-person collaboration judgment information is obtained. Multi-person collaboration judgment information refers to a series of related information based on the comprehensive estimation information of the task, which is used to judge whether each link or part of the task requires multi-person collaboration to complete. ,When the comprehensive estimation information of the task changes, the corresponding multi-person collaboration judgment information will also change, which helps to weigh the costs and benefits brought by multi-person collaboration under the premise of ensuring the quality of the task, so that the task execution can achieve the expected effect and control the cost within a reasonable range, thereby improving the cost performance of the task. Then, based on the task details information corresponding to each task node in the task flow node topology information, the task details information refers to the detailed description information for each task node, and combined with the previously determined multi-person collaboration judgment information, the collaboratively operable node information is accurately extracted from the numerous node topology information. The collaboratively operable node information refers to the task node information suitable for multi-person collaboration, and it is clear which nodes require the joint participation of multiple people in execution.Identify the parts of the task that are suitable for collaborative work, prepare for the subsequent collaborative operation boundary definition and task allocation, and then determine the corresponding collaborative operation boundary information for each collaborative operation node information, where the collaborative operation boundary information refers to the specific working scope of each collaborative operation node. By clarifying the scope of multi-person collaboration, the corresponding task allocation strategy information is formulated based on these boundary information, where the task allocation strategy information refers to the specific task allocation plan information formulated for the collaborative operation node. The task allocation strategy information plans in detail the specific work content and division of labor of each collaborative person or team in the node task to ensure that the collaborative operation is carried out in an orderly and efficient manner. Then, based on the topological information of multiple task flow nodes, the task path information is obtained, where the task path information refers to the description of all possible execution paths of the task from the beginning to the end. The main task information and branch task information are distinguished from the task path information, and the main execution route and branch execution route of the task are clarified. At the same time, for each task path information, multiple node flow condition information is further sorted out, where the node Point flow condition information refers to the condition information that needs to be met for tasks to flow between various task nodes. The node flow condition information is used to standardize the flow logic of tasks to ensure that tasks are carried out in an orderly manner according to the established process. Finally, the progress tracking information is obtained based on the task allocation strategy information and the node flow condition information. Among them, the progress tracking information refers to the information obtained by recording and monitoring the actual progress of each task node during the task execution process. The actual progress of the task can be grasped in real time through the progress tracking information. Then, the feasibility value is calculated based on these progress data, and the feasibility of the current task flow mechanism in actual execution is evaluated from a quantitative perspective, providing an objective basis for judging whether the task flow mechanism is feasible. Finally, the calculated feasibility value is compared with the expected value to determine whether the current task flow mechanism is feasible. If not, the feedback mechanism is used to return to the step of obtaining the comprehensive estimated information of the task, and the multi-person collaborative judgment information is adjusted according to the actual situation. The task flow mechanism is re-optimized, and it is iterated repeatedly until the task flow mechanism reaches a feasible state, thereby forming a closed-loop optimization process. ,

[0114] In one embodiment, the step S2 of acquiring node topology information according to each task node information and each directed edge information includes:

[0115] S21, acquiring corresponding task dependency information according to each of the task node information, and acquiring task auxiliary process information according to each of the task dependency information;

[0116] S22, obtaining corresponding task sequence information according to each of the directed edge information, and obtaining task core process information according to each of the task sequence information;

[0117] S23, acquiring backbone node information according to the task core process information and task auxiliary process information;

[0118] S24, acquiring task branch conversion information and task parallelism information according to the task auxiliary process information, and acquiring branch node information and summary node information according to the task branch conversion information;

[0119] S25. Acquire parallel node information according to the task parallelism information.

[0120] As described in the above steps S21-S25, in the present invention, by analyzing the information of each task node, the dependency relationship between each task is sorted out, and the task auxiliary process information is obtained according to the task dependency information, wherein the task dependency information refers to the mutual dependency relationship between each task node, and the task auxiliary process information refers to those process-related information that supports the main task process but does not directly constitute the realization of the core goal of the task. The task dependency information helps to clarify whether the implementation of a task node requires the results of other tasks as a prerequisite, and the auxiliary process information found based on the task dependency relationship helps to comprehensively consider various supporting activities in the task execution process, and the task sequence information can be interpreted from the directed edge information, wherein the task sequence information refers to the order information of the execution of the task nodes, which provides a clear time clue for the execution of the task, determines when each task should be started and completed, and sorts out the task core process information of the task based on the task sequence information, wherein the task core process information Information refers to the sequence of key steps to directly achieve the task objectives. The task core process information and task auxiliary process information are combined to identify the node information that plays a key supporting role in the entire task process, that is, the trunk node information. By further analyzing the task auxiliary process information, the situations in which branches appear in the task process and the situations in which tasks can be carried out in parallel are discovered, thereby obtaining task branch conversion information and task parallelism information. Among them, task branch conversion information refers to the relevant information about the task switching from one path to another in the task process, and task parallelism information refers to the relevant information that can be carried out simultaneously in the task process. Based on the task branch conversion information, the branch node information and summary node information in the task process are clarified, and the parallel node information is obtained through the task parallelism information. The obtained topological information of each node provides a clear framework for subsequent progress tracking. According to the nature and location of different nodes, corresponding progress monitoring points and indicators can be set to make progress tracking more targeted and systematic.

[0121] In one embodiment, the step S4 of extracting multiple collaboratively operable node information from multiple node topology information according to each of the task details information and the multi-person collaboration determination information includes:

[0122] S41, acquiring the element quantification value information corresponding to each task node according to each of the task details information, wherein the element quantification value information includes the task intensity value, the skill diversity value, and the resource requirement value;

[0123] S42, obtaining task attribute range information of historical tasks, wherein the task attribute range information includes task intensity range information, skill diversity range information and resource requirement range information;

[0124] S43, obtaining a maximum value and a minimum value of task intensity according to the task intensity range information, and obtaining a maximum value and a minimum value of skill diversity according to the skill diversity range information;

[0125] S44. Obtain the maximum resource demand value and the minimum resource demand value according to the resource demand range information, and calculate the single-person collaboration tendency distance value according to the task intensity value, the minimum task intensity value, the skill diversity value, the minimum skill diversity value, the resource demand value, and the minimum resource demand value, wherein the calculation formula is:

[0126]

[0127] Among them, D 1 represents the distance value of the single-person collaboration tendency, a represents the task intensity value, and a min represents the minimum task intensity, b represents the skill diversity value, and b min represents the minimum skill diversity, c represents the resource requirement value, and c min Indicates the minimum resource requirement;

[0128] S45. Calculate the multi-person collaboration tendency distance value according to the task intensity value, the maximum task intensity value, the skill diversity value, the maximum skill diversity value, the resource demand value, and the maximum resource demand value, wherein the calculation formula is:

[0129]

[0130] Among them, D 2 represents the multi-person collaboration tendency distance value, a represents the task intensity value, a max represents the maximum task intensity, b represents the skill diversity value, and b max represents the maximum value of skill diversity, c represents the resource demand value, and c max Indicates the maximum resource demand;

[0131] S46. Calculate the multi-person collaboration demand assessment value according to the single-person collaboration tendency distance value and the multi-person collaboration tendency distance value, wherein the calculation formula is:

[0132]

[0133] Among them, T represents the multi-person collaboration demand assessment value, D 1 Indicates the distance value of the single-person collaboration tendency, D 2 Indicates the multi-person collaboration demand assessment value;

[0134] S47, obtaining collaboration benefit prediction information according to the multi-person collaboration determination information, and obtaining a multi-person collaboration determination threshold according to the collaboration benefit prediction information;

[0135] S48, determining whether the multi-person collaboration demand evaluation value is greater than the multi-person collaboration determination threshold;

[0136] If the multi-person collaboration demand evaluation value is greater than the multi-person collaboration determination threshold, the node information is determined to be collaboratively operable node information;

[0137] If the multi-person collaboration demand evaluation value is not greater than the multi-person collaboration determination threshold, it is determined that the node information is not collaboratively operable node information.

[0138] As described in the above steps S41-S48, in the present invention, the element quantification value information corresponding to each task node is obtained through the task details information, wherein the element quantification value information refers to a data set that quantitatively describes the key attributes of the task node, and the element quantification value information includes task intensity value, skill diversity value, and resource requirement value. These quantitative values ​​can convert the complex characteristics of the task node into measurable data, providing an objective basis for subsequent analysis, and then obtain the task attribute range information of the historical task, wherein the task attribute range information refers to the description information of the attribute distribution range of similar tasks completed in the past, and the single-person collaboration tendency distance value and the multi-person collaboration tendency distance value are calculated according to the element quantification value information, the task attribute range information and the weight coefficient, wherein the single-person collaboration tendency distance value refers to the degree of proximity of a certain task node to the tendency boundary of a single person completing the task, and the multi-person collaboration tendency distance value refers to the distance between a certain task node and the tendency boundary of a single person completing the task. The degree of proximity between the task node and the tendency boundary of multiple people to complete the task is measured, and then the multi-person collaboration demand assessment value is calculated through the single-person collaboration tendency distance value and the multi-person collaboration tendency distance value. This assessment value is a comprehensive indicator, which quantitatively compares the tendencies of single-person collaboration and multi-person collaboration, and is used to measure the degree of demand for multi-person collaboration of the task node. The multi-person collaboration judgment threshold is obtained according to the collaboration benefit prediction information, where the collaboration benefit prediction information refers to the relevant information for pre-estimation of various possible positive results when considering the task to be completed in a multi-person collaboration manner, and the obtained multi-person collaboration judgment threshold is a standard boundary for judging whether multi-person collaboration is needed. The multi-person collaboration demand assessment value is compared with the multi-person collaboration judgment threshold to determine whether the node information is collaboratively operable node information. The entire judgment process is based on the data calculated and the set standards in the previous steps, so that the decision-making process is scientific and objective.

[0139] In one embodiment, the step S5 of acquiring task allocation strategy information corresponding to the cooperatively operable node according to each cooperatively operable boundary information includes:

[0140] S51, the collaborative operation boundary information includes collaborative operation target information and collaborative operation pre-information, and corresponding sub-module element information is acquired according to each collaborative operation target information, and corresponding pre-associated sub-module information is acquired according to each collaborative operation pre-information;

[0141] S52, obtaining corresponding task submodule information according to each of the submodule element information and the pre-associated submodule information, and obtaining skill requirement information of each module and workload information of each module according to each of the task submodule information;

[0142] S53, acquiring personnel skill matrix information and material resource information according to the resource management information, and acquiring corresponding personnel allocation information according to the skill requirement information of each module and the personnel skill matrix information;

[0143] S54, acquiring corresponding material demand information according to the workload information of each module, and acquiring corresponding resource allocation information according to each material demand information and material resource information;

[0144] S55. Obtain task allocation strategy information according to each personnel allocation information and resource allocation information.

[0145] As described in the above steps S51-S55, in the present invention, submodule element information and pre-associated submodule information are respectively obtained through collaborative operation target information and collaborative operation pre-information, wherein the collaborative operation target information refers to the information about the specific goals that each collaborative part expects to achieve regarding the task completed by multiple people, and the collaborative operation pre-information refers to other tasks, conditions or information that a task submodule depends on before performing the collaborative operation. The obtained submodule element information can clarify the specific elements involved in each sub-goal, which helps to refine the task content. At the same time, the obtained pre-associated submodule information can sort out the pre-dependency relationship between tasks, and combine the submodule element information and pre-associated submodule information to obtain complete task submodule information, wherein the task submodule information refers to a detailed description of a complete task submodule, and then based on the task submodule information, the skill requirement information of each module and the workload information of each module are further obtained, which provides key quantitative indicators for subsequent personnel and resource allocation, according to the personnel skill matrix information in the resource management information and the skill requirements of each module Information can be used to determine personnel allocation information, where the personnel skill matrix information shows the types and levels of personnel skills. By matching with the module skill requirement information, the most suitable personnel to complete each task sub-module can be found, and the material requirement information can be determined based on the workload information of each module. Combined with the material resource information, resource allocation information can be obtained. This step can determine the detailed information of the material resources actually allocated to each task sub-module, integrate the personnel allocation information and the resource allocation information to form a complete task allocation strategy information. Among them, task allocation strategy information refers to a set of detailed plan information on how tasks are allocated between personnel and resources after comprehensive consideration of various factors in the context of multi-person collaboration to complete tasks. This strategy information covers which personnel are responsible for each task sub-module, which material resources are needed to support it, etc. It is a summary and sorting of the entire task allocation process, and provides a clear guidance plan for the execution of tasks, ensuring that each task sub-module has clear personnel and resource arrangements, which is conducive to the orderly advancement of tasks according to plan and avoiding problems such as unclear responsibilities and resource confusion.

[0146] In one embodiment, the step S6 of acquiring a plurality of node transfer condition information according to each of the task path information comprises:

[0147] S61, acquiring first task information corresponding to each trunk node according to the trunk task information, and acquiring corresponding first task completion indicator information according to each first task information;

[0148] S62, obtaining second task information corresponding to each parallel node according to the branch task information, and obtaining corresponding second task completion indicator information according to each second task information;

[0149] S63, acquiring task switching condition information according to the plurality of first task completion indicator information and the plurality of second task completion indicator information;

[0150] S64, acquiring first pre-information and task flow information corresponding to each branch node according to the branch task information, and acquiring corresponding first task status information according to each first pre-information,

[0151] S65, acquiring corresponding branch path information according to each of the task flow information, and acquiring branch condition information corresponding to each branch node according to each of the first task status information and each of the branch path information;

[0152] S66, acquiring second pre-information and summary index information corresponding to each summary node according to each branch task information, and acquiring corresponding second task status information according to each second pre-information;

[0153] S67, acquiring summary condition information according to each summary indicator information and each second task status information;

[0154] S68. Obtain task aggregation and dispersion condition information according to the branch condition information and the summary condition information, and obtain node flow information according to the task aggregation and dispersion condition information and the task switching condition information.

[0155] As described in the above steps S61-S68, in the present invention, first task completion index information is obtained according to the first task information corresponding to the trunk node, wherein the first task information refers to the content description of the specific task located at the trunk node in the trunk task, and the first task completion index information refers to a series of standards for measuring whether the first task corresponding to the trunk node is successfully completed, and second task completion index information is obtained according to the second task information corresponding to the parallel node, wherein the second task information refers to the content description of the specific task located at the parallel node in the branch task, and the second task completion index information refers to a series of standards for measuring whether the second task corresponding to the parallel node is successfully completed, and then task switching condition information is obtained according to the first task completion index information and the second task completion index information, wherein the task switching condition information refers to the conditions for switching tasks between the trunk node and the parallel node. The task switching condition information can ensure smooth switching of tasks between various links to avoid confusion and interruption of the task process, and the branch condition information is obtained according to the first pre-information and task flow information corresponding to the branch node, wherein the first pre-information refers to the information such as the task completion status related to the branch node before the branch node of the branch task, which is The description of the prerequisites for starting the branch node task provides a background basis for the decision-making of the branch node. The task flow information refers to the description of the direction of the task path after the branch node. It clarifies how the task will be diverted to different subsequent paths according to different conditions or situations at the branch node, and obtains the summary condition information according to the second pre-information and summary indicator information corresponding to the summary node, wherein the second pre-information refers to the execution status, result status and other related information of each branch task before the summary node, which is the basis for judging whether the summary node can start working. The summary indicator information refers to the specific standard for measuring whether the summary node task is completed, and then the task gathering and dispersion condition information is obtained according to the branch condition information and the summary condition information, wherein the task gathering and dispersion condition information refers to the aggregation and dispersion rules of the task in the process of branching and summarizing, and finally the node flow information is obtained through the task gathering and dispersion condition information and the task switching condition information, wherein the node flow information refers to all the conditions for the task to flow between each node, which is a key information used to guide and control the direction of the task process. By analyzing whether the conditions in the node flow process are reasonable, whether the connection between nodes is close, whether there are redundant links, etc., it is beneficial to optimize the task process.

[0156] In one embodiment, the step S7 of calculating the feasibility value according to the progress tracking information includes:

[0157] S71, obtaining task execution progress information according to the progress tracking information, and obtaining a task completion ratio value according to the task execution progress information;

[0158] S72, obtaining a first weight coefficient corresponding to the task completion ratio;

[0159] S73, obtaining task completion stage information according to the task execution progress information, and obtaining resource consumption value according to the task completion stage information;

[0160] S74, obtaining a second weight coefficient corresponding to the resource consumption value;

[0161] S75, obtaining quality inspection information according to the progress tracking information, and obtaining the task achievement qualification rate according to the quality inspection information;

[0162] S76, obtaining a third weight coefficient corresponding to the task achievement qualification rate;

[0163] S77, acquiring task evaluation reference information according to historical data information, wherein the task evaluation reference information includes a mean value of task completion ratio, a standard deviation of task completion ratio, a mean value of resource consumption, a standard deviation of resource consumption, a mean value of qualified task results, and a standard deviation of qualified task results;

[0164] S78. Calculate the feasibility value according to the task completion ratio, the task completion ratio mean, the task completion ratio standard deviation, the first weight coefficient, the resource consumption value, the resource consumption mean, the resource consumption standard deviation, the second weight coefficient, the task result qualification rate, the task result qualification mean, the task result qualification standard deviation and the third weight coefficient, wherein the calculation formula is:

[0165]

[0166] Among them, F represents the feasibility value, P represents the task completion ratio, μ 1 represents the mean of the task completion ratio, σ 1 represents the standard deviation of task completion ratio, ω 1 represents the first weight coefficient, R represents the resource consumption value, μ 2 represents the mean resource consumption, σ 2 represents the standard deviation of resource consumption, ω 2 represents the second weight coefficient, Q represents the task result qualification rate, μ 3 represents the qualified mean value of task results, σ 3 Indicates the task achievement qualification standard, ω 3 Represents the third weight coefficient.

[0167] As described in the above steps S71-S78, in the present invention, the task execution progress information is obtained through progress tracking information, wherein the task execution progress information refers to a detailed description of the progress of the task in the time dimension, and the task completion ratio value is obtained according to the task execution progress information, wherein the task completion ratio value refers to the percentage of the completed part of the task to the total task amount, and the task completion ratio value provides an objective standard for measuring the progress of the task, which is not excessively interfered by subjective factors, and then the task completion stage information is obtained according to the task execution progress information, and then the resource consumption value is obtained from the task completion stage information, wherein the task completion stage information refers to the specific stage of the task and the completion status of the stage, and the resource consumption value refers to the quantitative value of various resources consumed during the task execution process. This step establishes the connection between task progress and resource consumption, and can understand the progress of the task in the process. How resources are utilized at different stages of the task, and then quality inspection information is obtained. Acquiring quality inspection information refers to the relevant information obtained from quality inspection of task results during task execution. Taking task quality as a key factor into consideration is an important basis for ensuring the effectiveness of the task, and obtaining the weight coefficients corresponding to the task completion ratio, resource consumption value, and task result qualification rate, respectively. Then, task evaluation reference information is obtained. Task evaluation reference information refers to a series of reference standards extracted based on historical data information for evaluating the current task execution status. Finally, the feasibility value is calculated according to a specific formula using the task evaluation reference information, task completion ratio, resource consumption value, and task result qualification rate. The feasibility value intuitively presents the feasibility of the task flow mechanism in a quantitative way, providing an objective basis for judging whether the task flow mechanism needs to be adjusted.

[0168] The present application also provides a task flow mechanism creation system based on a state machine template, including:

[0169] A first acquisition module is used to acquire overall task information, and acquire multiple task node information and multiple directed edge information according to the overall task information;

[0170] A second acquisition module is used to acquire node topology information according to each of the task node information and each of the directed edge information, wherein the node topology information includes fork node information, summary node information, parallel node information and trunk node information;

[0171] A third acquisition module is used to acquire comprehensive task estimation information, and acquire multi-person collaboration determination information based on the comprehensive task estimation information;

[0172] An extraction module, used to obtain task detail information corresponding to each task node according to the task flow node topology information, and extract multiple collaboratively operable node information from multiple node topology information according to each of the task detail information and multi-person collaboration determination information;

[0173] A fourth acquisition module is used to acquire corresponding collaborative operation boundary information according to each collaborative operation node information, and acquire task allocation strategy information corresponding to the collaborative operation node according to each collaborative operation boundary information;

[0174] A fifth acquisition module, used to acquire multiple task path information according to the multiple task flow node topology information, and acquire multiple node flow condition information according to each of the task path information, wherein the multiple task path information includes trunk task information and branch task information;

[0175] A calculation module, used for obtaining progress tracking information according to the task allocation strategy information and the node flow condition information, and calculating a feasibility value according to the progress tracking information;

[0176] A judgment module, used to judge whether the feasibility value is greater than an expected value;

[0177] If the feasibility value is greater than the expected value, the task flow mechanism is determined to be feasible;

[0178] If the feasibility value is not greater than the expected value, the task flow mechanism is determined to be infeasible. At this time, the process returns to the step of obtaining the comprehensive estimated task information, and adjusts the multi-person collaboration determination information according to the comprehensive estimated task information until the task flow mechanism is feasible.

[0179] In one embodiment, the extraction module comprises:

[0180] A first acquisition unit is used to acquire the element quantization value information corresponding to each task node according to each task detail information, wherein the element quantization value information includes a task intensity value, a skill diversity value, and a resource requirement value;

[0181] A second acquisition unit is used to acquire task attribute range information of historical tasks, wherein the task attribute range information includes task intensity range information, skill diversity range information and resource requirement range information;

[0182] A third acquisition unit, configured to acquire a maximum value and a minimum value of task intensity according to the task intensity range information, and acquire a maximum value and a minimum value of skill diversity according to the skill diversity range information;

[0183] The first calculation unit is used to obtain the maximum resource demand and the minimum resource demand according to the resource demand range information, and calculate the single-person collaboration tendency distance value according to the task intensity value, the minimum task intensity value, the skill diversity value, the minimum skill diversity value, the resource demand value and the minimum resource demand value, wherein the calculation formula is:

[0184]

[0185] Among them, D 1 represents the distance value of the single-person collaboration tendency, a represents the task intensity value, and a min represents the minimum task intensity, b represents the skill diversity value, and b min represents the minimum skill diversity, c represents the resource requirement value, and c min Indicates the minimum resource requirement;

[0186] The second calculation unit is used to calculate the multi-person collaboration tendency distance value according to the task intensity value, the maximum task intensity value, the skill diversity value, the maximum skill diversity value, the resource demand value and the maximum resource demand value, wherein the calculation formula is:

[0187]

[0188] Among them, D 2 represents the multi-person collaboration tendency distance value, a represents the task intensity value, a max represents the maximum task intensity, b represents the skill diversity value, and b max represents the maximum value of skill diversity, c represents the resource demand value, and c max Indicates the maximum resource demand;

[0189] The third calculation unit is used to calculate the multi-person collaboration demand evaluation value according to the single-person collaboration tendency distance value and the multi-person collaboration tendency distance value, wherein the calculation formula is:

[0190]

[0191] Among them, T represents the multi-person collaboration demand assessment value, D 1 Indicates the distance value of the single-person collaboration tendency, D 2 Indicates the multi-person collaboration demand assessment value;

[0192] a fourth acquisition unit, configured to acquire collaboration benefit prediction information according to the multi-person collaboration determination information, and acquire a multi-person collaboration determination threshold according to the collaboration benefit prediction information;

[0193] A judgment unit, used to judge whether the multi-person collaboration demand evaluation value is greater than the multi-person collaboration judgment threshold;

[0194] If the multi-person collaboration demand evaluation value is greater than the multi-person collaboration determination threshold, the node information is determined to be collaboratively operable node information;

[0195] If the multi-person collaboration demand evaluation value is not greater than the multi-person collaboration determination threshold, it is determined that the node information is not collaboratively operable node information.

[0196] like Figure 3As shown, the present application also provides a computer device, which may be a server, and its internal structure may be as shown in Figure 3 As shown. The computer device includes a processor, a memory, a network interface and a database connected through a system bus. Among them, the processor designed by the computer is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used for all data required by the process of the task flow mechanism creation method based on the state machine template. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, the task flow mechanism creation method based on the state machine template is implemented.

[0197] Those skilled in the art will understand that Figure 3 The structure shown in is merely a block diagram of a portion of the structure related to the present application solution and does not constitute a limitation on the computer device to which the present application solution is applied.

[0198] An embodiment of the present application also provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, any of the above-mentioned task flow mechanism creation methods and systems based on a state machine template is implemented.

[0199] Those of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media provided in this application and used in the embodiments may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (SSRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0200] It should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, device, article or method including a series of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such process, device, article or method. In the absence of further restrictions, an element defined by the sentence "includes a ..." does not exclude the presence of other identical elements in the process, device, article or method including the element.

[0201] The above description is only a preferred embodiment of the present invention, and does not limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made by using the contents of the present invention specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. A method for creating a task flow mechanism based on a state machine template, characterized in that: include: Obtaining overall task information, and obtaining multiple task node information and multiple directed edge information according to the overall task information; Acquire node topology information according to each of the task node information and each of the directed edge information, wherein the node topology information includes fork node information, summary node information, parallel node information and trunk node information; Obtaining comprehensive task estimation information, and obtaining multi-person collaboration determination information based on the comprehensive task estimation information; Acquire task detail information corresponding to each task node according to the task flow node topology information, and extract multiple collaboratively operable node information from multiple node topology information according to each of the task detail information and multi-person collaboration determination information; Acquire corresponding collaborative operation boundary information according to each collaborative operation node information, and acquire task allocation strategy information corresponding to the collaborative operation node according to each collaborative operation boundary information; Acquire multiple task path information according to the multiple task flow node topology information, and acquire multiple node flow condition information according to each of the task path information, wherein the multiple task path information includes trunk task information and branch task information; Acquire progress tracking information according to the task allocation strategy information and the node flow condition information, and calculate a feasibility value according to the progress tracking information; Determining whether the feasibility value is greater than an expected value; If the feasibility value is greater than the expected value, the task flow mechanism is determined to be feasible; If the feasibility value is not greater than the expected value, the task flow mechanism is determined to be infeasible. At this time, the process returns to the step of obtaining the comprehensive estimated task information, and adjusts the multi-person collaboration determination information according to the comprehensive estimated task information until the task flow mechanism is feasible.

2. A method for creating a task flow mechanism based on a state machine template according to claim 1, characterized in that: The step of acquiring node topology information according to each task node information and each directed edge information comprises: Acquire corresponding task dependency information according to each of the task node information, and acquire task auxiliary process information according to each of the task dependency information; Obtaining corresponding task sequence information according to each of the directed edge information, and obtaining task core process information according to each of the task sequence information; Acquire the backbone node information according to the task core process information and the task auxiliary process information; Acquire task branch conversion information and task parallelism information according to the task auxiliary process information, and acquire branch node information and summary node information according to the task branch conversion information; Parallel node information is acquired according to the task parallelism information.

3. A method for creating a task flow mechanism based on a state machine template according to claim 1, characterized in that: The step of extracting multiple collaboratively operable node information from multiple node topology information according to each of the task details information and the multi-person collaboration determination information includes: Obtaining element quantification value information corresponding to each task node according to each of the task details information, wherein the element quantification value information includes a task intensity value, a skill diversity value, and a resource requirement value; Acquire task attribute range information of historical tasks, wherein the task attribute range information includes task intensity range information, skill diversity range information and resource requirement range information; Acquire a maximum value and a minimum value of task intensity according to the task intensity range information, and acquire a maximum value and a minimum value of skill diversity according to the skill diversity range information; The maximum resource requirement and the minimum resource requirement are obtained according to the resource requirement range information, and the single-person collaboration tendency distance value is calculated according to the task intensity value, the minimum task intensity value, the skill diversity value, the minimum skill diversity value, the resource requirement value and the minimum resource requirement value, wherein the calculation formula is: Among them, D1 represents the distance value of the single-person collaboration tendency, a represents the task intensity value, and a min represents the minimum task intensity, b represents the skill diversity value, and b min represents the minimum skill diversity, c represents the resource requirement value, and c min Indicates the minimum resource requirement; The multi-person collaboration tendency distance value is calculated according to the task intensity value, the maximum task intensity value, the skill diversity value, the maximum skill diversity value, the resource demand value and the maximum resource demand value, wherein the calculation formula is: Among them, D2 represents the multi-person collaboration tendency distance value, a represents the task intensity value, a max represents the maximum task intensity, b represents the skill diversity value, and b max represents the maximum value of skill diversity, c represents the resource demand value, and c max Indicates the maximum resource demand; The multi-person collaboration demand assessment value is calculated based on the single-person collaboration tendency distance value and the multi-person collaboration tendency distance value, where the calculation formula is: Among them, T represents the multi-person collaboration demand evaluation value, D1 represents the single-person collaboration tendency distance value, and D2 represents the multi-person collaboration demand evaluation value; Acquire collaboration benefit prediction information according to the multi-person collaboration determination information, and acquire a multi-person collaboration determination threshold according to the collaboration benefit prediction information; Determine whether the multi-person collaboration demand assessment value is greater than the multi-person collaboration determination threshold; If the multi-person collaboration demand evaluation value is greater than the multi-person collaboration determination threshold, the node information is determined to be collaboratively operable node information; If the multi-person collaboration demand evaluation value is not greater than the multi-person collaboration determination threshold, it is determined that the node information is not collaboratively operable node information.

4. A method for creating a task flow mechanism based on a state machine template according to claim 1, characterized in that: The step of acquiring task allocation strategy information corresponding to the collaboratively operable node according to each collaborative operation boundary information comprises: The collaborative operation boundary information includes collaborative operation target information and collaborative operation pre-information, and the corresponding sub-module element information is obtained according to each collaborative operation target information, and the corresponding pre-associated sub-module information is obtained according to each collaborative operation pre-information; Obtain corresponding task submodule information according to each submodule element information and pre-associated submodule information, and obtain skill requirement information of each module and workload information of each module according to each task submodule information; Acquire personnel skill matrix information and material resource information according to the resource management information, and acquire corresponding personnel allocation information according to the skill requirement information of each module and the personnel skill matrix information; Acquire corresponding material demand information according to the workload information of each module, and acquire corresponding resource allocation information according to each material demand information and material resource information; The task allocation strategy information is obtained based on each personnel allocation information and resource allocation information.

5. A method for creating a task flow mechanism based on a state machine template according to claim 1, characterized in that: The step of acquiring a plurality of node flow condition information according to each of the task path information comprises: Acquire the first task information corresponding to each trunk node according to the trunk task information, and acquire the corresponding first task completion indicator information according to each first task information; Acquire the second task information corresponding to each parallel node according to the branch task information, and acquire the corresponding second task completion indicator information according to each second task information; Acquiring task switching condition information according to the plurality of first task completion indicator information and the plurality of second task completion indicator information; According to the branch task information, the first pre-information and task flow information corresponding to each branch node are obtained, and according to each first pre-information, the corresponding first task status information is obtained. Acquire corresponding branch path information according to each of the task flow information, and acquire branch condition information corresponding to each branch node according to each of the first task status information and each of the branch path information; Acquire the second pre-information and summary index information corresponding to each summary node according to each branch task information, and acquire the corresponding second task status information according to each second pre-information; Acquire summary condition information according to each summary indicator information and each second task status information; The task gathering and dispersing condition information is obtained according to the branching condition information and the summary condition information, and the node flow information is obtained according to the task gathering and dispersing condition information and the task switching condition information.

6. A method for creating a task flow mechanism based on a state machine template according to claim 1, characterized in that: The step of calculating the feasibility value according to the progress tracking information comprises: Acquire task execution progress information according to the progress tracking information, and acquire task completion ratio value according to the task execution progress information; Obtain a first weight coefficient corresponding to the task completion ratio value; Acquire task completion stage information according to the task execution progress information, and acquire resource consumption value according to the task completion stage information; Obtaining a second weight coefficient corresponding to the resource consumption value; Acquire quality inspection information according to the progress tracking information, and acquire the task achievement qualification rate according to the quality inspection information; Obtain the third weight coefficient corresponding to the task achievement qualification rate; Acquire task evaluation reference information according to historical data information, wherein the task evaluation reference information includes a mean value of task completion ratio, a standard deviation of task completion ratio, a mean value of resource consumption, a standard deviation of resource consumption, a mean value of qualified task results, and a standard deviation of qualified task results; The feasibility value is calculated according to the task completion ratio value, the task completion ratio mean value, the task completion ratio standard deviation, the first weight coefficient, the resource consumption value, the resource consumption mean value, the resource consumption standard deviation, the second weight coefficient, the task result qualification rate, the task result qualification mean value, the task result qualification standard deviation and the third weight coefficient, wherein the calculation formula is: Among them, F represents the feasibility value, P represents the task completion ratio, μ1 represents the mean value of the task completion ratio, σ1 represents the standard deviation of the task completion ratio, ω1 represents the first weight coefficient, R represents the resource consumption value, μ2 represents the mean value of resource consumption, σ2 represents the standard deviation of resource consumption, ω2 represents the second weight coefficient, Q represents the task achievement qualification rate, μ3 represents the mean value of task achievement qualification, σ3 represents the task achievement qualification standard, and ω3 represents the third weight coefficient.

7. A task flow mechanism creation system based on a state machine template, characterized in that: include: A first acquisition module is used to acquire overall task information, and acquire multiple task node information and multiple directed edge information according to the overall task information; A second acquisition module is used to acquire node topology information according to each of the task node information and each of the directed edge information, wherein the node topology information includes fork node information, summary node information, parallel node information and trunk node information; A third acquisition module is used to acquire comprehensive task estimation information, and acquire multi-person collaboration determination information based on the comprehensive task estimation information; An extraction module, used to obtain task detail information corresponding to each task node according to the task flow node topology information, and extract multiple collaboratively operable node information from multiple node topology information according to each of the task detail information and multi-person collaboration determination information; A fourth acquisition module is used to acquire corresponding collaborative operation boundary information according to each collaborative operation node information, and acquire task allocation strategy information corresponding to the collaborative operation node according to each collaborative operation boundary information; A fifth acquisition module, used to acquire multiple task path information according to the multiple task flow node topology information, and acquire multiple node flow condition information according to each of the task path information, wherein the multiple task path information includes trunk task information and branch task information; A calculation module, used to obtain progress tracking information according to the task allocation strategy information and the node flow condition information, and calculate a feasibility value according to the progress tracking information; A judgment module, used to judge whether the feasibility value is greater than an expected value; If the feasibility value is greater than the expected value, the task flow mechanism is determined to be feasible; If the feasibility value is not greater than the expected value, the task flow mechanism is determined to be infeasible. At this time, the process returns to the step of obtaining the comprehensive estimated task information, and adjusts the multi-person collaboration determination information according to the comprehensive estimated task information until the task flow mechanism is feasible.

8. A task flow mechanism creation system based on a state machine template according to claim 7, characterized in that: The extraction module comprises: A first acquisition unit is used to acquire the element quantization value information corresponding to each task node according to each task detail information, wherein the element quantization value information includes a task intensity value, a skill diversity value, and a resource requirement value; A second acquisition unit is used to acquire task attribute range information of historical tasks, wherein the task attribute range information includes task intensity range information, skill diversity range information and resource requirement range information; A third acquisition unit, configured to acquire a maximum value and a minimum value of task intensity according to the task intensity range information, and acquire a maximum value and a minimum value of skill diversity according to the skill diversity range information; The first calculation unit is used to obtain the maximum resource demand and the minimum resource demand according to the resource demand range information, and calculate the single-person collaboration tendency distance value according to the task intensity value, the minimum task intensity value, the skill diversity value, the minimum skill diversity value, the resource demand value and the minimum resource demand value, wherein the calculation formula is: Among them, D1 represents the distance value of the single-person collaboration tendency, a represents the task intensity value, and a min represents the minimum task intensity, b represents the skill diversity value, and b min represents the minimum skill diversity, c represents the resource requirement value, and c min Indicates the minimum resource requirement; The second calculation unit is used to calculate the multi-person collaboration tendency distance value according to the task intensity value, the maximum task intensity value, the skill diversity value, the maximum skill diversity value, the resource demand value and the maximum resource demand value, wherein the calculation formula is: Among them, D2 represents the multi-person collaboration tendency distance value, a represents the task intensity value, a max represents the maximum task intensity, b represents the skill diversity value, and b max represents the maximum value of skill diversity, c represents the resource demand value, and c max Indicates the maximum resource demand; The third calculation unit is used to calculate the multi-person collaboration demand evaluation value according to the single-person collaboration tendency distance value and the multi-person collaboration tendency distance value, wherein the calculation formula is: Among them, T represents the multi-person collaboration demand evaluation value, D1 represents the single-person collaboration tendency distance value, and D2 represents the multi-person collaboration demand evaluation value; a fourth acquisition unit, configured to acquire collaboration benefit prediction information according to the multi-person collaboration determination information, and acquire a multi-person collaboration determination threshold according to the collaboration benefit prediction information; A judgment unit, used to judge whether the multi-person collaboration demand evaluation value is greater than the multi-person collaboration judgment threshold; If the multi-person collaboration demand evaluation value is greater than the multi-person collaboration determination threshold, the node information is determined to be collaboratively operable node information; If the multi-person collaboration demand evaluation value is not greater than the multi-person collaboration determination threshold, it is determined that the node information is not collaboratively operable node information.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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