CN114897511A

CN114897511A - Service flow scheduling processing method and system based on RPA technology

Info

Publication number: CN114897511A
Application number: CN202210628811.0A
Authority: CN
Inventors: 魏洁
Original assignee: Industrial and Commercial Bank of China Ltd ICBC
Current assignee: Industrial and Commercial Bank of China Ltd ICBC
Priority date: 2022-06-06
Filing date: 2022-06-06
Publication date: 2022-08-12

Abstract

The application provides a service process scheduling processing method and system based on RPA technology, which relates to the field of artificial intelligence and can be applied to the financial field and other fields, and the method comprises the following steps: generating a task number according to a received service to be processed, and determining a service flow according to the service type of the service to be processed; obtaining a plurality of sub-processes and execution logics of the sub-processes according to the service process splitting, and respectively generating corresponding logic numbers for the logic sequences of the sub-processes in the service process; distributing the sub-processes, the logic numbers and the task numbers to a plurality of RPA sub-module robots according to the processing types corresponding to the sub-processes; and extracting result parameters generated by processing the sub-processes through each RPA sub-module robot in the cache queue according to the task numbers, and integrating the result parameters according to the logic numbers to obtain a processing result of the service to be processed.

Description

Service flow scheduling processing method and system based on RPA technology

Technical Field

The application relates to the field of artificial intelligence, can be applied to the financial field and other fields, and particularly relates to a service flow scheduling processing method and system based on an RPA technology.

Background

In the current society, business handling related to transaction is often accompanied by multi-link processing procedures to avoid potential capital risks; for the staff, when a received service to be handled is received, the handling process needs to be known, the operation steps of each step are authenticated and verified, and the effective handling of the service can be guaranteed, but with the increase of the traffic, the safety of the service can not be guaranteed in a conventional manual handling mode any more, and the increase of the number can cause the concentration of the staff to be obviously reduced, so that unnecessary risks are brought; in addition, the conventional business handling mode has the limitation of the number of personnel, and a large amount of business is temporarily available and has the problem of waiting.

With the development of science and technology, automatic transaction for a certain business process by a program writing mode appears in the prior art, so that the problem of human resource waste is solved; however, financial services are developed along with the market, the types of services are greatly increased, and the way of compiling a corresponding program for each service also has the problems of overlarge labor cost, low program reuse rate, incapability of meeting timeliness and the like, so that the requirements of related users cannot be met.

In view of this, there is a need in the art for an efficient business process handling method to improve the operation efficiency, timeliness and accuracy of business process handling on the basis of saving manpower.

Disclosure of Invention

The application aims to provide a service process scheduling processing method and system based on an RPA technology, which realize the standardization and automation of full-service processing and full-service handover processes in an intelligent robot processing mode, and finally reach all links of the full process.

To achieve the above object, the service process scheduling processing method based on the RPA technology provided in the present application specifically includes: generating a task number according to a received service to be processed, and determining a service flow according to the service type of the service to be processed; obtaining a plurality of sub-processes and execution logics of the sub-processes according to the service process splitting, and respectively generating corresponding logic numbers for the logic sequences of the sub-processes in the service process; distributing the sub-processes, the logic numbers and the task numbers to a plurality of RPA sub-module robots according to the processing types corresponding to the sub-processes; and extracting result parameters generated by processing the sub-processes through each RPA sub-module robot in the cache queue according to the task numbers, and integrating the result parameters according to the logic numbers to obtain a processing result of the service to be processed.

In the above method for scheduling and processing a service flow based on the RPA technology, optionally, the method further includes: the RPA sub-module robot confirms the processing type of the sub-process according to the received logic number; and when the processing type is parallel processing, processing the sub-process to generate a result parameter, and uploading the result parameter to a cache queue according to the logic number and the task number.

In the above method for scheduling and processing a service flow based on RPA technology, optionally, the processing the sub-flow generation result parameter according to the processing type further includes: when the processing type is in-order processing, obtaining a result parameter corresponding to the preorder logic number in the cache queue through the logic number; obtaining a result parameter corresponding to the current logic number according to the result parameter corresponding to the preorder logic number and the sub-process processing; and uploading the corresponding result parameters to a cache queue according to the current logic number and the task number.

In the above method for scheduling and processing a service flow based on RPA technology, optionally, the processing the sub-flow generation result parameter according to the processing type further includes: generating an intervention identifier when the RPA sub-module robot is abnormal in the sub-process processing process; and associating the intervention identification, the sub-process, the logic number and the task number to generate prompt data, and uploading the prompt data to a cache queue.

In the above method for scheduling and processing a service flow based on RPA technology, optionally, the processing the sub-flow generation result parameter according to the processing type further includes: generating prompt information according to the prompt data in the cache queue, and providing the prompt information to a preset position; and acquiring result parameters fed back by the preset position according to the prompt information, acquiring the corresponding logic number and the corresponding task number according to the intervention identification, uploading the received result parameters to a cache queue through the logic number and the task number, and deleting the corresponding prompt data.

In the above method for scheduling and processing a service flow based on an RPA technology, optionally, the allocating the sub-flow, the logic number, and the task number to a plurality of RPA sub-module robots according to the processing type corresponding to the sub-flow further includes: acquiring the load states of a plurality of RPA sub-module robots of corresponding types according to the processing types corresponding to the sub-processes; and distributing the sub-processes, the logic numbers and the task numbers to the corresponding RPA sub-module robots in a load balancing mode according to the load state.

In the above service flow scheduling processing method based on the RPA technology, optionally, the processing type includes a credit data transfer data statistics type, a debit data application transfer processing type, and an electronic subscription system archiving type.

The application also provides a service flow scheduling processing system based on the RPA technology, which comprises a scheduling robot and a plurality of RPA sub-module robots; the scheduling robot is used for generating a task number according to the received service to be processed and determining a service flow according to the service type of the service to be processed; obtaining a plurality of sub-processes and execution logics of the sub-processes according to the service process splitting, and respectively generating corresponding logic numbers for the logic sequences of the sub-processes in the service process; distributing the sub-processes, the logic numbers and the task numbers to a plurality of RPA sub-module robots according to the processing types corresponding to the sub-processes; extracting result parameters generated by processing the sub-processes through each RPA sub-module robot in the task number extraction cache queue, and integrating the result parameters according to the logic numbers to obtain a processing result of the service to be processed; the RPA sub-module robot is used for confirming the processing type of the sub-process according to the received logic number; when the processing type is parallel processing, processing the sub-process to generate a result parameter, and uploading the result parameter to a cache queue according to the logic number and the task number; and when the processing type is in-sequence processing, obtaining a result parameter corresponding to the preorder logic number in the cache queue through the logic number, obtaining a result parameter corresponding to the current logic number according to the result parameter corresponding to the preorder logic number and the sub-process processing, and uploading the corresponding result parameter to the cache queue according to the current logic number and the task number.

The application also provides an electronic device, which comprises a memory, a processor and a computer program stored on the memory and capable of running on the processor, wherein the processor executes the computer program to realize the method.

The present application also provides a computer-readable storage medium storing a computer program for executing the above method.

The present application also provides a computer program product comprising computer programs/instructions which, when executed by a processor, implement the steps of the above-described method.

The beneficial technical effect of this application lies in: the intelligent robot replaces the processing for the repeated labor link needing to manually input information and click options based on the RPA technology simulation of each post personnel in the service processing, so that the service efficiency is improved, and the labor cost is saved; by setting the task scheduling center, the manual and RPA processing modes can be well compatible; splitting a service flow, and setting a scheduling robot and a sub-module robot, wherein the scheduling robot is responsible for creating tasks and scheduling the sub-module robot to execute corresponding task plates; therefore, after the task 1 is handed over to the sub-module robot, the scheduling robot can create a new loan task, so that the execution efficiency is improved, and the problem is conveniently searched; the RPA robot expansion is supported according to the processing traffic of a certain submodule, if the module A has larger processing traffic and long queuing time, the operation processing efficiency of the link is expanded.

Drawings

The accompanying drawings, which are included to provide a further understanding of the application, are incorporated in and constitute a part of this application, and are not intended to limit the application. In the drawings:

fig. 1 is a schematic flow chart of a service flow scheduling processing method based on an RPA technique according to an embodiment of the present application;

fig. 2 is a schematic diagram of a parallel task processing flow of an RPA sub-module robot according to an embodiment of the present application;

fig. 3 is a schematic view illustrating a process flow of an associated task of an RPA sub-module robot according to an embodiment of the present application;

fig. 4 is a schematic diagram illustrating an exception task processing flow of an RPA sub-module robot according to an embodiment of the present application;

fig. 5 is a schematic diagram of an exception recovery processing flow of an RPA sub-module robot according to an embodiment of the present application;

fig. 6 is a schematic view of a load balancing process flow of a dispatching robot according to an embodiment of the present application;

fig. 7 is a schematic structural diagram of a service flow scheduling processing system based on RPA technology according to an embodiment of the present application;

fig. 8 is a schematic structural diagram of an electronic device according to an embodiment of the application.

Detailed Description

The following detailed description will be provided with reference to the drawings and examples to explain how to apply the technical means to solve the technical problems and to achieve the technical effects. It should be noted that, as long as there is no conflict, the embodiments and the features of the embodiments in the present application may be combined with each other, and the technical solutions formed are all within the scope of the present application.

Additionally, the steps illustrated in the flow charts of the figures may be performed in a computer system such as a set of computer-executable instructions and, although a logical order is illustrated in the flow charts, in some cases, the steps illustrated or described may be performed in an order different than here.

Referring to fig. 1, a service flow scheduling processing method based on RPA technology provided in the present application specifically includes:

s101, generating a task number according to a received service to be processed, and determining a service flow according to the service type of the service to be processed;

s102, obtaining a plurality of sub-processes and execution logics of the sub-processes according to the business process splitting, and respectively generating corresponding logic numbers for the logic sequences of the sub-processes in the business process;

s103, distributing the sub-processes, the logic numbers and the task numbers to a plurality of RPA sub-module robots according to the processing types corresponding to the sub-processes;

s104, extracting result parameters generated by processing the sub-processes through each RPA sub-module robot in the cache queue according to the task numbers, and integrating the result parameters according to the logic numbers to obtain a processing result of the service to be processed.

In the above embodiment, the RPA technology refers to robot process automation, which is one of artificial intelligent applications, and aims to complete repetitive operation tasks with certain rules and scales between application systems and systems by the RPA without changing the functions of the original application systems, so that user experience can be greatly improved, labor cost can be reduced, operation efficiency and accuracy can be improved, and operation risk can be reduced. According to statistics, after the RPA is used, the RPA runs continuously by 7 multiplied by 24, the operation efficiency is improved by 60 percent, the operation risk is reduced to zero, and the accuracy reaches 100 percent. The method and the device have the advantages that RPA configuration is carried out on the whole process of the service by applying the RPA technology, and the operation instruction sent by the dispatching center is responded at any time, so that an intelligent and distinctive processing mode of the service is realized. In order to improve the utilization rate of the RPA robot, the method is different from the mode that the prior robot executes the process to the end, the method splits the business process, and sets a dispatching robot and a sub-module robot. The scheduling robot is responsible for creating loan tasks and schedules the sub-module robot to execute corresponding task plates. Therefore, after the task 1 is handed over to the sub-module robot, the scheduling robot can create a new loan task, so that the execution efficiency is improved, and the problem is conveniently searched; meanwhile, if the workload is large, a plurality of RPA robots can be introduced into the same sub-process, the RPA robots are distinguished through IP addresses, and the scheduling system selects the RPA robot receiving the task according to the state of the RPA robot.

Referring to fig. 2, in an embodiment of the present application, the method further includes:

s201, the RPA sub-module robot confirms the processing type of the sub-process according to the received logic number;

s202, when the processing type is parallel processing, processing the sub-process to generate a result parameter, and uploading the result parameter to a buffer queue according to the logic number and the task number.

Referring to fig. 3 again, in another embodiment, the processing the sub-process generated result parameter according to the processing type further includes:

s301, when the processing type is in-order processing, obtaining a result parameter corresponding to the preorder logic number in the cache queue through the logic number;

s302, according to the result parameter corresponding to the preorder logic number and the sub-process, obtaining a result parameter corresponding to the current logic number;

s303, uploading the corresponding result parameters to a cache queue according to the current logic number and the task number.

Specifically, in actual work, irrelevant or relevant situations exist in a business process, irrelevant sub-processes can adopt a parallel processing mode for improving the processing efficiency, and at the moment, each RPA sub-module robot can process the sub-processes in parallel, so that the business handling time is greatly shortened; when the correlation exists, the sub-processes need to be processed in sequence at the moment, the result parameter extraction position is determined by the RPA sub-module robot according to the logic number in a mode of citing a cache queue, and then the whole ordered execution is realized in a self-extracting processing mode.

Referring to fig. 4, in an embodiment of the present application, processing the sub-process generated result parameter according to the processing type further includes:

s401, when the RPA sub-module robot processes the exception in the sub-process, generating an intervention identifier;

s402, associating the intervention identification, the sub-process, the logic number and the task number to generate prompt data, and uploading the prompt data to a cache queue.

Further, as shown in fig. 5, the processing the sub-process result generation parameter according to the processing type may further include:

s501, generating prompt information according to the prompt data in the cache queue, and providing the prompt information to a preset position;

s502, obtaining result parameters fed back by a preset position according to the prompt information, obtaining the corresponding logic number and the corresponding task number according to the intervention identification, uploading the received result parameters to a cache queue through the logic number and the task number, and deleting the corresponding prompt data.

Specifically, in actual work, because the business process cannot guarantee that no abnormal state can be generated in the processing process, in the embodiment, manual processing is introduced through the intervention identification, for example, when the business process executes the third step, a server fails to read data, the current business processing is suspended, and a supervisor is reminded to inquire related data through the intervention identification to process the sub-process of the link; after the manual processing finishes the feedback, the feedback is transmitted into a cache queue and a subsequent RPA submodule continues a subsequent process; of course, the abnormal state in the actual work includes various situations, which is substantially the situation that the expected result cannot be obtained by currently adopting the defined process processing mode, and at this time, the above-mentioned mode can be introduced to be completed manually, and of course, some subjectively defined sub-processes can also be introduced to be processed by supervisors in an abnormal mode according to the actual needs, such as review comments, trend analysis, and the like, and the details of the application are not given here.

Referring to fig. 6, in an embodiment of the present application, the allocating the sub-process, the logic number, and the task number to a plurality of RPA sub-module robots according to the processing type corresponding to the sub-process further includes:

s601, acquiring load states of a plurality of RPA sub-module robots of corresponding types according to the processing types corresponding to the sub-processes;

and S602, distributing the sub-processes, the logic numbers and the task numbers to the corresponding RPA sub-module robots in a load balancing mode according to the load states. The processing type may include a credit data handover data statistic type, a debit application handover processing type and an electronic subscription system archiving type.

In this embodiment, mainly for the case where multiple RPA sub-module robots are used simultaneously, in order to improve the processing efficiency of the service process, after the scheduling robot confirms the sub-processes, each sub-process may be allocated to the RPA robot IP in an idle or busy state in a load balancing manner, so as to invoke the corresponding sub-module RPA robot to complete the corresponding sub-process processing.

For better understanding, the present application provides a specific application of the above embodiments, which are described in the following by taking the loan transaction flow as an example:

firstly, the scheduling robot reads a user name and a password in a configuration file, completes initial loan information creation and entry according to file information, and creates a loan processing task.

Thereafter, the scheduling robot may process multiple tasks in parallel. And the scheduling robot generates a number according to the received task and stores the corresponding scheduling task to a cache queue according to the number. And the scheduling robot calls corresponding flow configuration information according to the loan basic information and distributes tasks to each RPA sub-module robot. And sequentially executing by each RPA sub-module robot. And when the scheduling robot distributes the loan task to the sub-module robot, returning to the flow starting point to create a new loan task according to the configuration file information. After each sub-module robot completes corresponding processing, storing corresponding processing results into a cache queue according to the numbers and modifying the scheduling task identification; the subsequent sub-module robot extracts the processing result in the cache queue according to the serial number to complete subsequent service logic; and finally, the scheduling robot determines the task completion condition according to the identification in the scheduling task corresponding to each number in the cache queue, and counts the result feedback. In the process, the scheduling robot can receive the next assigned task without waiting for the completion of the current task, store the next assigned task into the cache queue according to the flow, and schedule the tasks according to the working state of each sub-module robot.

And then, if the RPA processing submodule throws an exception, the scheduling robot marks the step as manual processing and prompts corresponding business personnel to enter a core system for processing, at the moment, the core task is suspended, and the state is set as waiting. Continuing after the manual processing is finished; the scheduling robot can determine the IP of the RPA robot in an idle state by inquiring the state of each RPA robot according to the process configuration information, so that the corresponding sub-module RPA robot is scheduled.

And configuring loan transaction processing flows according to different loan transaction types and the change of the contained parameters, wherein the operation mode of each processing flow is manual or RPA. Different flow program numbers can correspond to the same step number, and if the step numbers of the flow 001 and the flow 002 are both 001, the scheduling task schedules the two flows to perform service processing simultaneously. The sub-process with step number 002 can be advanced after all the processes with step 001 are processed. The dispatching mode of the dispatching robot can be realized based on a table building mode, and each parameter table can refer to the following tables 1, 2 and 3:

TABLE 1

TABLE 2

TABLE 3

RPA Module numbering	RPA robot IP address	Status of state
			001

The configuration mode of each RPA submodule robot can be as follows:

an RPA sub-module robot for credit data transfer data statistics:

1. the RPA robot reads the user name and password in the configuration file, captures the data elements of 'new generation personal loan management and customer service' system, business transaction, personal loan data transfer/reception, loan data transfer data statistics, and carries out click operation.

File receiving mechanism code input: selecting product types: and (3) the person purchases a loan in one hand (the person purchases a loan in the other hand, and the loan of the person is a commercial house, which is selected according to the actually processed loan variety).

Inputting a process name: XXX credits were processed together (1.0).

The robot clicks "query" and clicks "confirm".

2. The RPA captures an 'information query' button on a page, clicks and finishes clicking operation according to the sequence of user job management-personal submission of user job query.

On the day of submitting the time list entry query, "query" is clicked.

Clicking to download, clicking to open, decompressing the file and obtaining the EXCEL table of the data.

And screening data of receiving time of the loan approval post and receiving-free time of the loan payment post in an EXCEL table.

3. The RPA robot captures the factors of the service organization, the client number, the certificate number and the contract agreement number, fills the factors of result feedback, and submits the factors to a dispatching system for later borrow application and flow handover for calling.

Secondly, borrowing the RPA sub-module robot applied:

1. the RPA robot clicks in turn according to a system of 'new generation personal loan management and customer service', business transaction, business application and loan application.

In the institution selection input box, the institution name in the configuration file is entered, and the "query" is clicked.

Select the corresponding client/client type "personal client", enter the client host number, click "query".

Selecting the corresponding loan application record/agreement list area-selecting the corresponding loan application record-clicking "query".

2. The RPA robot grabs the page 'data list' button and clicks 'withdraw'.

The system prompts whether to make a loan contract online download first to ensure that the account is consistent with the contract information of the host, and clicks the confirmation after clicking the confirmation.

Automatic billing flag/"automatic billing flag" selection "yes;

and checking/clicking the right inverted triangle of the first loan account to check the account.

The date of interest rate validation selects the date of application for borrowing (the date of the loan), clicks on for saving, and submits to examination and approval.

Selecting a 'personal loan data issuing process', clicking 'confirm'/popping up to directly confirm success, and clicking 'confirm'.

Thirdly, completing the RPA sub-module robot for handover processing according to the application:

the RPA robot selects 'the mechanism to be processed' according to the entering 'the new generation personal loan management and customer service' system, the business handling, the personal loan data transfer and the personal loan data processing, inputs 'the organization to which the business belongs' and 'the customer certificate number', clicks 'inquiry', clicks 'checking' and 'claiming'.

And (5) prompting information to claim successfully, and clicking to determine.

In the user processing, the user certificate number is input, the user can click and inquire, the serial number is selected, and the user can click and send the user.

Clicking the 'archive management post', selecting the next handler 'Wanliyun', and clicking 'sending'.

Send successfully, click "ok". And finishing the electronic flow handover.

Fourthly, the RPA sub-module robot filed by the electronic signing system:

the RPA robot selects 'to-be-approved service' click 'to inquire' at 'contract state'.

And selecting 'filing audit' and 'viewing contract filing materials'.

Clicking the top right "red fork" exits the click "determination".

And repeating the preset steps until the archiving is completed.

Referring to fig. 7, the present application further provides a service flow scheduling processing system based on RPA technology, where the system includes a scheduling robot and a plurality of RPA sub-module robots; the scheduling robot is used for generating a task number according to the received service to be processed and determining a service flow according to the service type of the service to be processed; obtaining a plurality of sub-processes and execution logics of the sub-processes according to the service process splitting, and respectively generating corresponding logic numbers for the logic sequences of the sub-processes in the service process; distributing the sub-processes, the logic numbers and the task numbers to a plurality of RPA sub-module robots according to the processing types corresponding to the sub-processes; extracting result parameters generated by processing the sub-processes through each RPA sub-module robot in the task number extraction cache queue, and integrating the result parameters according to the logic numbers to obtain a processing result of the service to be processed; the RPA sub-module robot is used for confirming the processing type of the sub-process according to the received logic number; when the processing type is parallel processing, processing the sub-process to generate a result parameter, and uploading the result parameter to a cache queue according to the logic number and the task number; and when the processing type is in-sequence processing, obtaining a result parameter corresponding to the preorder logic number in the cache queue through the logic number, obtaining a result parameter corresponding to the current logic number according to the result parameter corresponding to the preorder logic number and the sub-process processing, and uploading the corresponding result parameter to the cache queue according to the current logic number and the task number. The specific interaction mode of the scheduling robot and the RPA sub-module robot and the actual processing flow of the business flow are described in detail in the foregoing embodiments, and are not described in detail herein.

As shown in fig. 8, the electronic device 600 may further include: communication module 110, input unit 120, audio processing unit 130, display 160, power supply 170. It is noted that the electronic device 600 does not necessarily include all of the components shown in FIG. 8; furthermore, the electronic device 600 may also comprise components not shown in fig. 8, which may be referred to in the prior art.

As shown in fig. 8, the central processor 100, sometimes referred to as a controller or operational control, may include a microprocessor or other processor device and/or logic device, the central processor 100 receiving input and controlling the operation of the various components of the electronic device 600.

The memory 140 may be, for example, one or more of a buffer, a flash memory, a hard drive, a removable media, a volatile memory, a non-volatile memory, or other suitable device. The information relating to the failure may be stored, and a program for executing the information may be stored. And the central processing unit 100 may execute the program stored in the memory 140 to realize information storage or processing, etc.

The input unit 120 provides input to the cpu 100. The input unit 120 is, for example, a key or a touch input device. The power supply 170 is used to provide power to the electronic device 600. The display 160 is used to display an object to be displayed, such as an image or a character. The display may be, for example, but is not limited to, an LCD display.

The memory 140 may be a solid state memory such as Read Only Memory (ROM), Random Access Memory (RAM), a SIM card, or the like. There may also be a memory that holds information even when power is off, can be selectively erased, and is provided with more data, an example of which is sometimes called an EPROM or the like. The memory 140 may also be some other type of device. Memory 140 includes buffer memory 141 (sometimes referred to as a buffer). The memory 140 may include an application/function storage section 142, and the application/function storage section 142 is used to store application programs and function programs or a flow for executing the operation of the electronic device 600 by the central processing unit 100.

The memory 140 may also include a data store 143, the data store 143 for storing data, such as contacts, digital data, pictures, sounds, and/or any other data used by the electronic device. The driver storage portion 144 of the memory 140 may include various drivers of the electronic device for communication functions and/or for performing other functions of the electronic device (e.g., messaging application, address book application, etc.).

The communication module 110 is a transmitter/receiver 110 that transmits and receives signals via an antenna 111. The communication module (transmitter/receiver) 110 is coupled to the central processor 100 to provide an input signal and receive an output signal, which may be the same as in the case of a conventional mobile communication terminal.

Based on different communication technologies, a plurality of communication modules 110, such as a cellular network module, a bluetooth module, and/or a wireless local area network module, may be provided in the same electronic device. The communication module (transmitter/receiver) 110 is also coupled to a speaker 131 and a microphone 132 via an audio processor 130 to provide audio output via the speaker 131 and receive audio input from the microphone 132 to implement general telecommunications functions. Audio processor 130 may include any suitable buffers, decoders, amplifiers and so forth. In addition, an audio processor 130 is also coupled to the central processor 100, so that recording on the local can be enabled through a microphone 132, and so that sound stored on the local can be played through a speaker 131.

As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.

The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

The above-mentioned embodiments are further described in detail for the purpose of illustrating the invention, and it should be understood that the above-mentioned embodiments are only illustrative of the present invention and are not intended to limit the scope of the present invention, and any modifications, equivalent substitutions, improvements, etc. made within the spirit and principle of the present invention should be included in the scope of the present invention.

Claims

1. A service flow scheduling processing method based on RPA technology is characterized in that the method comprises:

generating a task number according to a received service to be processed, and determining a service flow according to the service type of the service to be processed;

obtaining a plurality of sub-processes and execution logics of the sub-processes according to the service process splitting, and respectively generating corresponding logic numbers for the logic sequences of the sub-processes in the service process;

distributing the sub-processes, the logic numbers and the task numbers to a plurality of RPA sub-module robots according to the processing types corresponding to the sub-processes;

and extracting result parameters generated by processing the sub-processes through each RPA sub-module robot in the cache queue according to the task numbers, and integrating the result parameters according to the logic numbers to obtain a processing result of the service to be processed.

2. The RPA technology-based traffic scheduling processing method according to claim 1, further comprising:

the RPA sub-module robot confirms the processing type of the sub-process according to the received logic number;

and when the processing type is parallel processing, processing the sub-process to generate a result parameter, and uploading the result parameter to a cache queue according to the logic number and the task number.

3. The RPA technology-based traffic flow scheduling processing method according to claim 2, wherein processing the sub-flow generation result parameter according to the processing type further includes:

when the processing type is in-order processing, obtaining a result parameter corresponding to the preorder logic number in the cache queue through the logic number;

obtaining a result parameter corresponding to the current logic number according to the result parameter corresponding to the preorder logic number and the sub-process processing;

and uploading the corresponding result parameters to a cache queue according to the current logic number and the task number.

4. The RPA technology-based traffic flow scheduling processing method according to claim 2, wherein processing the sub-flow generation result parameter according to the processing type further includes:

generating an intervention identifier when the RPA sub-module robot is abnormal in the sub-process processing process;

and associating the intervention identification, the sub-process, the logic number and the task number to generate prompt data, and uploading the prompt data to a cache queue.

5. The RPA technology-based traffic flow scheduling processing method according to claim 4, wherein processing the sub-flow generation result parameter according to the processing type further includes:

generating prompt information according to the prompt data in the cache queue, and providing the prompt information to a preset position;

and acquiring result parameters fed back by the preset position according to the prompt information, acquiring the corresponding logic number and the corresponding task number according to the intervention identification, uploading the received result parameters to a cache queue through the logic number and the task number, and deleting the corresponding prompt data.

6. The RPA technology-based business process scheduling processing method of claim 1, wherein assigning the sub-process, the logic number, and the task number to a plurality of RPA sub-module robots according to the processing type corresponding to the sub-process further comprises:

acquiring the load states of a plurality of RPA sub-module robots of corresponding types according to the processing types corresponding to the sub-processes;

and distributing the sub-processes, the logic numbers and the task numbers to the corresponding RPA sub-module robots in a load balancing mode according to the load state.

7. The RPA technology-based business process scheduling processing method of claim 1, wherein the processing types include a credit data transfer data statistics type, a debit application transfer processing type, and an electronic subscription system archiving type.

8. A service process scheduling processing system based on RPA technology is characterized in that the system comprises a scheduling robot and a plurality of RPA sub-module robots;

the scheduling robot is used for generating a task number according to the received service to be processed and determining a service flow according to the service type of the service to be processed; obtaining a plurality of sub-processes and execution logics of the sub-processes according to the service process splitting, and respectively generating corresponding logic numbers for the logic sequences of the sub-processes in the service process; distributing the sub-processes, the logic numbers and the task numbers to a plurality of RPA sub-module robots according to the processing types corresponding to the sub-processes; extracting result parameters generated by processing the sub-processes through each RPA sub-module robot in the task number extraction cache queue, and integrating the result parameters according to the logic numbers to obtain a processing result of the service to be processed;

the RPA sub-module robot is used for confirming the processing type of the sub-process according to the received logic number; when the processing type is parallel processing, processing the sub-process to generate a result parameter, and uploading the result parameter to a cache queue according to the logic number and the task number; and when the processing type is in-sequence processing, obtaining a result parameter corresponding to the preorder logic number in the cache queue through the logic number, obtaining a result parameter corresponding to the current logic number according to the result parameter corresponding to the preorder logic number and the sub-process processing, and uploading the corresponding result parameter to the cache queue according to the current logic number and the task number.

9. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the method of any of claims 1 to 7 when executing the computer program.

10. A computer-readable storage medium, characterized in that the computer-readable storage medium stores a computer program for executing the method of any one of claims 1 to 7 by a computer.

11. A computer program product comprising computer program/instructions, characterized in that the computer program/instructions, when executed by a processor, implement the steps of the method of any of claims 1 to 7.