CN116050597A - Task risk identification and optimization system and task risk identification and optimization method - Google Patents

Abstract

The invention provides a task risk identification and optimization system and a task risk identification and optimization method. The processor inputs the multi-task data to the problem detection module so that the problem detection module detects the multi-task data according to the abnormality detection table to generate a problem list. The task establishing module generates task items according to the problem list, and the risk judging module generates risk grades and processing suggestion information of the corresponding task items according to the risk judging standard table. The task risk identification and optimization system and the task risk identification and optimization method can automatically identify the risk of the task project and generate the corresponding processing suggestion information of the risk task, thereby improving the efficiency of task management and solving the abnormal risk.

Description

Task risk identification and optimization system and task risk identification and optimization method

Technical Field

The invention relates to a task project management technology and an abnormality detection technology related to product research and development or production, in particular to a task risk identification and optimization system and a task risk identification and optimization method.

Background

In the process of executing the product research and development task, due to the fact that the project management of research and development products is various and the task distribution is complex, the research and development project is easy to delay because of insufficient classification fineness, insufficient experience of engineers, difficult cross-department assistance and other conditions. The existing method is that a project manager records the abnormal conditions, stages, reasons and solutions manually, and makes the recorded results into an experience teaching manual so that the similar conditions can be met next time and the solutions can be found according to the experience teaching manual. However, solutions are still difficult to obtain at the first time of the problem occurrence, and cross-department assistance, notification, and communication are not performed efficiently. In this regard, how to effectively identify risks for production or development task management and provide suggested methods for process optimization and solution have been an important topic in the art.

Disclosure of Invention

The invention is directed to a task risk recognition and optimization system and a task risk recognition and optimization method, which can automatically perform task processing for the purpose of performing the process and provide the process -based construction , thereby generating corresponding processing suggestion information of any task of the process .

According to an embodiment of the invention, the task risk identification and optimization system comprises a storage device and a processor. The storage device stores an abnormality detection table, a risk judgment standard table, a problem detection module, a task building module and a risk judgment module. The processor is coupled with the storage device and executes the problem detection module, the task establishment module and the risk judgment module. The processor inputs the multi-task data to the problem detection module so that the problem detection module detects the multi-task data according to the abnormality detection table to generate a problem list. The task establishing module generates task items according to the problem list, and the risk judging module generates risk grades and processing suggestion information of the corresponding task items according to the risk judging standard table.

According to an embodiment of the present invention, the task risk identification and optimization method of the present invention includes the steps of: inputting task data to a problem detection module; detecting a plurality of task data according to the abnormality detection table by a problem detection module to generate a problem list; generating task items according to the problem list through a task building module; and generating risk grades and suggested processing information of the corresponding task items according to the risk judging standard table by the risk judging module.

Based on the above, the task risk recognition and optimization system and the task risk recognition and optimization method of the present invention can automatically detect the abnormality of task data according to the historical data about task risk and abnormal situation to generate a problem list, and automatically generate the associated task abnormality information corresponding to the problem list, and generate the processing suggestion information related to the solution means according to the parameter setting and the historical data, so as to effectively improve the efficiency and accuracy of project/task management, and further enable the manager and the associated personnel of the task to more quickly learn the abnormal occurrence situation and the solution means suggestion information.

In order to make the above features and advantages of the present invention more comprehensible, embodiments accompanied with figures are described in detail below.

Drawings

FIG. 1 is a schematic diagram of a task risk identification and optimization system according to an embodiment of the present invention;

FIG. 2 is a flow chart of a task risk identification and optimization method according to an embodiment of the present invention;

FIG. 3 is a flow chart illustrating the operation of a task risk identification and optimization method according to an embodiment of the present invention.

Description of the reference numerals

100: task risk identification and optimization system;

110: a processor;

120: a storage device;

121: a problem detection module;

122: a task building module;

123: a risk judging module;

124: an optimization suggestion module;

125: a data conversion module;

u1, U2, U3: associating personnel;

301: project data;

302: task data;

303: a problem list;

304: a problem list;

305: historical data;

306: identifying a result;

s210 to S240, S331 to S338: and (3) step (c).

Detailed Description

Reference will now be made in detail to the exemplary embodiments of the present invention, examples of which are illustrated in the accompanying drawings. Wherever possible, the same reference numbers are used in the drawings and the description to refer to the same or like parts.

FIG. 1 is a schematic diagram of a task risk identification and optimization system according to an embodiment of the present invention. Referring to fig. 1, a task risk identification and optimization system 100 includes a processor 110 and a storage 120. The processor 110 is coupled to the storage device 120. In the present embodiment, the processor 110 may include a processing circuit or a chip with data operation function, such as a central processing unit (Central Processing Unit, CPU), a microprocessor (Microprocessor Control Unit, MCU) or a field programmable gate array (Field Programmable Gate Array, FPGA), but the invention is not limited thereto. The storage device 120 may be a Memory (Memory) or a database (database), wherein the Memory may be a nonvolatile Memory such as a Read Only Memory (ROM), an erasable programmable Read Only Memory (Erasable Programmable Read Only Memory, EPROM), a volatile Memory such as a random access Memory (Random Access Memory, RAM), a hard disk drive (hard drive), a semiconductor Memory, etc., and is used for storing data related to product requirements, in-factory inventory data, out-factory inventory data, parameter setting values, information related to productivity, various programs, data calculation rules, data value rules, data presentation rules, image presentation parameters, data filtering rules, productivity data, bill of materials data, and various information.

In this embodiment, the storage device 120 may store a plurality of specific modules, algorithms, software, etc. for the processor 110 to access and execute to implement the relevant functions and operations described in the various embodiments of the present invention. It should be noted that the modules and units described in the embodiments of the present invention may be implemented by corresponding one or more algorithms and/or software, respectively, and the related functions and operations described in the embodiments may be implemented according to the execution result of one or more algorithms and/or software.

In the present embodiment, the storage device 120 may store the problem detection module 121, the task creation module 122, and the risk determination module 123. The processor 110 may read these modules stored in the storage 120 and, by executing these modules, perform the functions of analyzing project data for developing new products, generating a problem list and associated task reminder authorities related to the task data, and automatically generating risk levels for the task project and processing advice information, etc., based on the rules and history data. In this embodiment, the task risk recognition and optimization system 100 may be, for example, a computer host installed in an enterprise, and provides a user interface or a terminal device for a user to operate, so as to input task settings, project data, project flow, anomaly detection table, anomaly detection set (i.e. detection rule), risk judgment criteria table (i.e. judgment rule), associated personnel information, data analysis range, and set threshold value.

Alternatively, in an embodiment, the task risk recognition and optimization system 100 may be implemented, for example, in a cloud server system architecture. The User can connect to the cloud server to perform the related parameter and rule setting operation by executing a User Interface (UI) program of the electronic device. In this regard, the user may operate the content of the user interface displayed on the display of the electronic device, so that the user interface, the application program interface (Application Programming Interface, API) or the related program may provide corresponding user operation instructions and setting data to the cloud server. The cloud server may be, for example, a software-as-a-service (Software as a Service, saaS) server, and the application program interface corresponds to a software-as-a-service application, such that the task risk identification and optimization system 100 may be disposed in the software-as-a-service server and receive and transmit data to a database of an enterprise resource planning (Enterprise Resource Planning, ERP) system via the application program interface.

But the present invention is not limited thereto. Alternatively, in an embodiment, the task risk recognition and optimization system 100 may be disposed in a ground server inside the enterprise, and further connected to a database of the enterprise resource planning system and a cloud database in the ground server to input/output data, so as to provide functions of task management, task flow management, risk analysis and generation of processing advice information through different application programming interfaces. In one embodiment, the problem detection module 121, the task creation module 122, and the risk determination module 123, as well as other modules and units, may be implemented in a program language such as JSON (JavaScript Object Notation), extensible markup language (Extensible Markup Language, XML), or YAML, but the present invention is not limited thereto.

In other words, the task/process association personnel, production manager and user can operate the task risk recognition and optimization system 100 and the application program interface of the storage device 120 to input the multiple project data, task data and parameter values of each setting provided by the client into the storage device 120 and the processor 110, and the task risk recognition and optimization system 100 can automatically execute the problem detection module 121, the task creation module 122 and the risk judgment module 123 according to the prediction data and the inventory data to generate the relevant risk analysis level, the judgment information and the processing suggestion information (such as problem solving means or problem solving suggestion).

In this embodiment, the processor 110 and the storage device 120 may be configured to receive/read/write inventory data, risk determination rules, task data, flow data, history data, set values, processing methods and abnormality detection rules stored in the terminal device and the enterprise resource planning system, so that the problem detection module 121, the task creation module 122 and the risk determination module 123 may receive a plurality of project data or task data of the user, and flow conditions and abnormality records of the enterprise resource planning system.

FIG. 2 is a flow chart of a task risk identification and optimization method according to an embodiment of the present invention. Referring to fig. 1 and 2, the task risk recognition and optimization system 100 of the present embodiment may perform the following steps S210 to S240. In this embodiment, the user can operate the application program interfaces of the problem detection module 121, the task creation module 122, and the risk determination module 123. In step S210, the processor 110 inputs the task data to the problem detection module 121. Specifically, the task data may be data related to at least one task item in the new product development process, for example, the task data may be data related to a production product or a development product, such as a production size of the component a, a production quantity of the component a, a test data set value of the test component B, and development planning process data.

In step S220, the processor 110 detects the task data according to the anomaly detection table through the problem detection module 121 to generate a problem list. The abnormality detection table may be a detection rule related to task data abnormality, such as overdue task of developing new product, pause task item, and change of delivery object, for example, overdue task, severely overdue/delayed development process, or abnormality caused by failure of task item due to insufficient components, which may cause the problem detection module 121 to generate a problem list. The problem list includes at least one of a task number, a project serial number, a task name, a description of the problem (e.g., project A overdue or project B delivery has changed), an occurrence time, associated personnel information, a task status, and a solution.

In step S230, the processor 110 generates a task item according to the problem list through the task creation module 122. The task item may be a checking task, a production task, a secondary research and development task, or a detection task, etc. related to a research and development product. In step S240, the processor 110 generates, by the risk judging module 123, a risk level of the corresponding task item and processing advice information (i.e., advice processing information) according to the risk judging criteria table. The risk determination criteria table (i.e. risk determination rule) may determine a risk condition according to a task overdue time or determine a risk condition according to a difference between a current process and a predetermined process. The risk level may be, for example, a high risk level, a medium risk level, or a low risk level. The process advice information is a process advice related to solving the abnormal situation, and the process advice information may be, for example, checking the equipment temperature, tracking the development progress, establishing a new test task, or a new production work order. That is, the risk determination module 123 may generate a corresponding risk level and an abnormality resolution suggestion (i.e. processing suggestion information) according to the determination rule, so that the task association personnel can quickly learn the task risk status and the suggested processing mode capable of eliminating the risk, thereby increasing the efficiency of product development or product manufacturing process management and abnormality handling.

FIG. 3 is a flow chart illustrating the operation of a task risk identification and optimization method according to an embodiment of the present invention. Reference is made to fig. 1 and 3. In one embodiment, the task risk identification and optimization system 100 can execute steps S331 to S338 as follows to generate the processing suggestion information corresponding to the project data 301 or the task data 302 according to the rule and the history data 305.

In this embodiment, the task risk identification and optimization system 100 further includes a data conversion module for converting the project data 301 into task data 302. The processor 110 inputs the plurality of items of data 301 to the data conversion module 125. In step S331, the data conversion module 125 converts the multi-pen item data 310 into the multi-pen task data 302 according to the task lookup table. In one embodiment, the task lookup table may be, for example, a lookup table of product A against task A, a lookup table of test item against task B, etc. related to the item parameters/item data 301 and various tasks. For example, user input

In the present embodiment, the processor 110 inputs the multi-task data 302 into the problem detection module 121. In step S332, the processor 110 outputs the plurality of task data 302 to the corresponding associated person (U1, U2, U3) accordingly. That is, the processor 110 can notify the corresponding associated personnel (U1, U2, U3) of the task data 302, respectively, so as to reduce the time cost of personnel communication between the cross departments or the cross tasks. Project data 301 includes at least one of a question description, a task number, a product number, a task assignment time, assigner information, an associated task.

In step S333, the problem detection module 121 performs an abnormality detection mechanism on the multi-task data 302 according to the abnormality detection table to generate corresponding problem lists (303, 304). In one embodiment, the task performer inputs parameters related to the task (i.e., the project data 301) into the processor 110, and the problem detection module 121 divides the project data 301 into a plurality of task data 302 according to the task. Next, the problem detection module 121 finds abnormal portions of the task data 302 according to the set value, the normal range value or the detection rule (step S333), and further creates a problem list (303, 304) for recording the abnormal conditions.

In another embodiment, when the task executor finds that the task is abnormal, the task executor uses the abnormal data, the cause of the abnormality and the description of the abnormality as the item data 301 and inputs the item data into the processor 110, so that the problem detection module 121 forms a corresponding problem list according to the abnormal number, the source of the abnormality, the task record, the problem occurrence time, the corresponding responsible person and the processing method (303, 304). That is, the problem detection module 121 not only can identify whether there is an abnormal condition (such as overdue, too high/too low temperature, or failed detection) in the product development or production process for the current task parameter/data, but also the problem detection module 121 can receive the problem record (such as an error in the installation position) found by the task executor, after the executor inputs the problem record (the project data 301 includes the data of the problem list (303, 304)), the problem detection module 121 can generate the associated task content according to the problem content and output the reminding information to the executor/responsible person of the associated task.

In one embodiment, the problem detection module 121 includes an association notification unit for obtaining an association task from the task data 302 and/or the problem list 303 and outputting the association task to the associated person (U1, U2, U3). The storage device 120 further stores a task association table, and the task association table is associated with the plurality of task data 302 and associated task information (including associated persons (U1, U2, U3) and notification information) corresponding to the plurality of task data 302. In step S334, the association notification unit generates notification information (including the association task and the notification content) and the associated person (U1, U2, U3) corresponding to the task data 302 from the task association lookup table and the problem list (303, 304), and outputs the notification information to the associated person (e.g., the associated person U2) corresponding to the task data.

In other words, the problem detection module 121 may detect the abnormality of the task data 302, and the associated notification unit may recognize that the related task (e.g. the pre-task of the abnormal task, the task associated with the abnormal task) may also be at risk according to the history data 305 and/or the task abnormality rule, and further transmit the problem list 303 to the associated person U2 to automatically alert the task of the risk.

In another embodiment, the task risk recognition and optimization system 100 can automatically screen the inventory, personnel attendance status (e.g. leave data) and abnormal data, determine other tasks or processes that may possibly generate risk status, and further automatically alert the associated responsible person or project manager of the related task. For example, when the amount of material remaining is greater than twenty percent (too much) of the desired amount, or less than twenty percent (too little) of the desired amount, the task risk identification and optimization system 100 automatically sends a reminder notification to the information about the material.

On the other hand, the task risk recognition and optimization system 100 may screen inventory data and then give information to the associated personnel (U1, U2, U3) to alert the inventory, such as that the cushion is not in stock, which may affect the testing or production process. Alternatively, the task risk identification and optimization system 100 generates alert confirmation information to the associated personnel (U1, U2, U3) based on the plurality of project data 301 and the task data 302 detecting that the design failure mode and the result analysis (Design Failure Mode and Effect Analysis, DFMEA) are inconsistent with the tolerance records in the standard work process.

That is, the task risk identification and optimization system 100 may generate associated task information according to the task parameters in the problem list 303 and the abnormality occurrence node (e.g. the link of occurrence of the abnormality and the time), so that the problem detection module 121 transmits the associated task information to the associated person (e.g. the associated person U2). For example, the problem of temperature anomaly occurred in the process a in the product development process, and the problem detection module 121 creates a problem list of the process a according to the temperature anomaly problem (303, 304). Next, the problem detection module 121 generates a process B (e.g. quality detection) related to the temperature of the process a according to the task association table, so as to generate a quality detection reminder for reminding a responsible person (associated person U2) responsible for quality detection of the process B to perform quality detection reminding again, which may be different due to the temperature, thereby improving the management efficiency of the production management or the research and development management and providing possibility of eliminating the abnormal situation and possibly deriving other problems from the abnormality.

In step S335, the problem detection module 121 detects the task data 302 to generate a problem list (303, 304) corresponding to the task data 302. That is, in step S335, the problem detection module 121 performs an anomaly detection mechanism on the associated task information and data to obtain the problem list 304 (e.g. quality detection anomaly) associated with the process B. In one embodiment, the problem detection module 121 uses the problem list (303, 304) as the history data 305 and stores the problem list in the history database. It should be noted that the history data 305 may be data of any of the rule set values described above.

In step S336, the task creation module 122 generates task items according to the problem list (303, 304). For example, if the problem list (303, 304) includes an abnormal problem that the production is overdue, the task creation module 122 creates a task item that tracks the production progress again. In another example, the problem list (303, 304) may be, for example, a problem of a device temperature anomaly, and the task creation module 122 generates a plurality of task items (e.g., redesign the device, re-detect the temperature after adjusting the parameters, and other parameters) that exclude the temperature anomaly.

In one embodiment, the historical data 305 includes a plurality of risk level tables, risk condition categories, and historical processing information. In step S337, the risk judging module 123 may generate a risk level of the corresponding task item according to the history data 305 and the risk judging criteria table, and the risk judging module 123 generates corresponding processing advice information according to the history processing information. The risk level may be, for example, a level of importance related to the length of time that has expired, to the likelihood of an engineering/procedure occurring, and to the procedure in which an abnormal condition occurred. For example, some of the product development or product production processes belong to important processes (e.g., important stages such as generating bill of materials tables, generating standard operation programs, generating development flowcharts, or generating operation flowcharts).

In other words, the risk judging module 123 identifies the risk level, record abnormal node and recommended solution (judging result 306) corresponding to the current task item according to the problem list (303, 304), task item and history data 305. That is, the risk determination module 123 may determine the risk level (e.g. the degree of influence or the overdue days in the whole process) of the current task item according to the abnormal condition of which stage the task item of the corresponding problem list (303, 304) belongs to and according to the historical abnormal data of the similar process in the historical data 305. For example, the project/task period is 100 days, when the risk determination module 123 finds that the current flow of the project only goes to half of the flow, but the task period is only 30 days, the risk determination module 123 correspondingly generates the risk level reminder and the information content.

In one embodiment, the task risk identification and optimization system 100 further includes an optimization suggestion module 124, the optimization suggestion module 124 generating flow suggestion information based on historical data 305 and the plurality of tasks data 302. That is, the history data 305 generates risk judgment and recommended solution corresponding to the current situation according to the task type, the product type or the content of the project data 301. Also, the optimization suggestion module may generate feedback questions and optimization flow suggestions based on the historical data 305. For example, the optimization flow suggestion may be, for example, a task item for newly adding a mold for adjustment and test in the work decomposition structure, or a task item for newly adding an optimization task item for improving the success rate of trial installation according to the frequent abnormal situation before pilot-trial installation in the history data. Therefore, the product manager can adjust the process of developing new products according to the optimization process suggestion, and further, the process steps of developing the products are further perfected.

For example, when the history data 305 includes an excessive temperature, and the produced samples are all failed, the risk determination module 123 generates a task confirmation task according to the history data 305, and then pushes/sends a reminder to the associated personnel. In this way, the optimization suggestion module 124 may give suggestions about tasks to the task responsible person based on the historical data 305. In other words, the task risk recognition and optimization system 100 can record the history data 305 according to machine learning, and automatically generate the reminding data and the recognition result 306, so as to effectively reduce the risk of overdue task. In step S338, when the risk determination module 123 determines that the risk of the current task and the like belong to the low risk level, the information without abnormality is output, and the task risk identification and optimization flow is ended.

That is, the task risk recognition and optimization system 100 can pop up the display screen of the related person (U1, U2, U3) in the form of reminding information to remind according to the historical emergency situation (such as important problem, minor important problem, attention problem in the judgment rule) in the historical data 305, when the similar task and the similar situation occur to the current task, the task risk recognition and optimization system 100 can further reduce the abnormal occurrence probability of product research and development or product production, and avoid the situation that the abnormal occurrence is caused by insufficient experience of the person.

In summary, the task risk recognition and optimization system 100 and the task risk recognition and optimization method of the present invention can automatically analyze and risk recognition according to the plurality of item data 301, the history data 305, and the task data 302, so as to generate the corresponding problem list (303, 304), the task item, the risk level, and the processing suggestion information. Thus, the time cost required by the cross-department notification can be effectively and greatly reduced, and the occurrence probability of abnormality caused by the fear that the experience of new processing personnel is insufficient due to personnel mobilization is reduced. Meanwhile, related tasks are found out automatically according to the problem lists (303, 304) and the whole standard operation program, so that responsible personnel of the related tasks are reminded to carry out corresponding processing (for example, if the front task is abnormal, follow-up tasks are reminded to check abnormal data together). In this way, the history data 305 is integrated and classified as an experience training manual through machine learning, so as to reduce the time required by the training staff and the time cost and labor cost of production/research and development management.

Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present invention, and not for limiting the same; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some or all of the technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit of the invention.

Claims (18)

1. A task risk identification and optimization system, comprising:

the storage device is used for storing the abnormality detection table, the risk judgment standard table, the problem detection module, the task building module and the risk judgment module; and

a processor coupled to the storage device and executing the problem detection module, the task creation module, and the risk determination module,

wherein the processor inputs a plurality of tasks data to the problem detection module,

wherein the problem detection module detects the plurality of task data according to an abnormality detection table to generate a problem list,

the task establishing module generates task items according to the problem list, and the risk judging module generates risk grades and processing suggestion information corresponding to the task items according to the risk judging standard table.

2. The task risk identification and optimization system of claim 1, wherein the problem list includes at least one of task numbers, item serial numbers, task names, problem descriptions, time of occurrence, associated personnel information, task status, and solutions.

3. The task risk identification and optimization system of claim 1, wherein the problem detection module uses the problem list as historical data and stores it in a historical database.

4. A task risk identification and optimization system as claimed in claim 3, further comprising:

and the optimization suggestion module is used for generating flow suggestion information according to the historical data and the multi-stroke task data.

5. The task risk identification and optimization system of claim 3, wherein the historical data includes a plurality of risk level tables, risk condition categories, and historical processing information, wherein the risk determination module generates the risk level corresponding to the task item based on the historical data and the risk determination criteria table, and wherein the risk determination module generates the corresponding processing advice information based on the historical processing information.

6. The task risk recognition and optimization system according to claim 1, wherein the problem detection module includes an association notification unit, wherein the storage device further stores a task association lookup table, and the task association lookup table is associated with a plurality of the task data and associated task information corresponding to the plurality of the task data, wherein the association notification unit generates notification information of the corresponding task data and associated personnel according to the problem list, and outputs the notification information to the associated personnel of the corresponding task data.

7. The task risk identification and optimization system of claim 6, wherein the problem detection module detects the corresponding task data to generate the problem list corresponding to the corresponding task data.

8. The task risk identification and optimization system of claim 6, further comprising a data conversion module,

wherein the processor inputs a plurality of items of data to the data conversion module so that the data conversion module converts the plurality of items of data into the plurality of tasks of data according to a task comparison table so that the processor inputs the plurality of tasks of data to the problem detection module,

wherein the processor correspondingly outputs the plurality of tasks data to the corresponding associated person.

9. The task risk identification and optimization system of claim 8, wherein the project data includes at least one of a question description, a task number, a product number, a task assignment time, an assigner information, an associated task.

10. A task risk identification and optimization method, comprising:

inputting the multiple tasks data to the problem detection module,

detecting the plurality of task data according to an abnormality detection table by the problem detection module to generate a problem list,

and generating task items according to the problem list through a task establishing module, and generating risk grades and processing suggestion information corresponding to the task items through the risk judging module according to the risk judging standard table.

11. The task risk identification and optimization method of claim 10, wherein the problem list includes at least one of task number, project serial number, task name, problem description, time of occurrence, associated personnel information, task status, and solution.

12. The task risk identification and optimization method of claim 10, further comprising: and using the problem list as historical data through the problem detection module, and storing the historical data in a historical database.

13. The task risk identification and optimization method of claim 12, further comprising:

and generating flow proposal information according to the historical data and the multi-stroke task data through an optimization proposal module.

14. The task risk identification and optimization method according to claim 12, wherein the historical data includes a plurality of risk level tables, risk condition categories, and historical process information,

wherein the step of judging the risk level of the tracking task item according to the risk judgment standard table by the risk judgment module to process the recommended information further comprises:

and generating the risk grade corresponding to the task item according to the historical data and the risk judgment standard table through the risk judgment module, and generating the corresponding processing suggestion information according to the historical processing information through the risk judgment module.

15. The task risk identification and optimization method according to claim 10, wherein the storage device further stores a task association lookup table, and the task association lookup table is related to a plurality of the task data and associated task information corresponding to the plurality of task data,

wherein the task risk identification and optimization system further comprises:

generating notification information of corresponding task data and associated personnel according to the problem list through an associated notification unit, and outputting the notification information to the associated personnel of the corresponding task data through the associated notification unit.

16. The task risk identification and optimization method of claim 15, further comprising: detecting the corresponding task data by the problem detection module to generate the problem list corresponding to the corresponding task data.

17. The task risk identification and optimization method of claim 15, wherein the step of inputting the plurality of tasks data to the problem detection module further comprises:

inputting a plurality of items of data to a data conversion module,

converting the multi-pen project data into the multi-pen task data according to a task comparison table through the data conversion module, and

inputting the multi-task data into the problem detection module,

wherein the plurality of tasks data is correspondingly output to the corresponding associated person by a processor.

18. The task risk identification and optimization method of claim 17, wherein the project data includes at least one of a question description, a task number, a product number, a task assignment time, an assigner information, an associated task.

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