A Service-Oriented Platform-Based RPA Robot Operation Monitoring and Analysis Method

Abstract

This invention provides a method for monitoring and analyzing the operation of an RPA robot based on a service-oriented platform, belonging to the field of RPA robot technology. Specifically, it includes: determining, using read failure data within different file data volume ranges, that the RPA robot does not have any business interfaces whose operational status does not meet requirements; based on read failure data within different file data volume ranges and historical read data, determining the read problem coefficients and problem data volume ranges of the business interfaces within different file data volume ranges; determining the overlapping operational data of the problem data volume ranges of different business interfaces of the RPA robot based on the analysis results; and combining the read problem coefficients of different problem data volume ranges to determine whether the business interfaces of the RPA robot need to be optimized, thereby improving the operational reliability of the RPA robot.

Description

Technical Field

[0001] This invention belongs to the field of RPA robot technology, and particularly relates to a method for monitoring and analyzing the operation of RPA robots based on a service-oriented platform. Background Technology

[0002] To improve data processing efficiency and reduce the data processing burden on staff, power companies have deployed a large number of RPA robots based on different business needs. This makes it an urgent technical problem to solve how to monitor the operation of RPA robots and ensure the efficiency and accuracy of data processing.

[0003] In specific existing technical solutions, such as CN202310753900.2 "A Power Grid Work Order Monitoring Method, System and Device Based on RPA Robot", real-time automatic monitoring and reminders for various power grid work orders save manpower and improve work order processing efficiency. However, the above technical solutions have the following technical problems:

[0004] During the operation of an RPA robot, there may be a mismatch between the business interface and the file size of the uploaded file, which may cause the business call of the RPA robot to fail. Therefore, if the business interface is not adjusted accordingly, the reliability of the RPA robot's operation cannot be guaranteed.

[0005] To address the aforementioned technical problems, this invention provides a method for monitoring and analyzing the operation of RPA robots based on a service-oriented platform. Summary of the Invention

[0006] To achieve the objectives of this invention, the following technical solution is adopted:

[0007] To address the aforementioned technical problems, the present invention provides the following technical solution to achieve its objectives:

[0008] According to one aspect of the present invention, a method for monitoring and analyzing the operation of RPA robots based on a service-oriented platform is provided.

[0009] A method for monitoring and analyzing the operation of RPA robots based on a service-oriented platform, specifically including:

[0010] S1 uses the parsing results of the RPA robot's operation data on the service platform to obtain the reading failure data of the RPA robot's business interface. Based on the reading failure data of different business interfaces during business processing, if the RPA robot's operation status meets the requirements, proceed to the next step.

[0011] S2 divides the read failure data into different file data ranges based on the corresponding file data, and uses the read failure data in different file data ranges to determine that the PRA robot does not have a business interface whose operating status does not meet the requirements, and then proceeds to the next step.

[0012] S3 determines the reading problem coefficient and problem data range of the business interface in different file data volume ranges based on the reading failure data and historical reading data in different file data volume ranges;

[0013] S4 determines the overlapping running data of the problem data volume range of different business interfaces of the RPA robot based on the analysis results, and determines whether the business interface of the RPA robot needs to be optimized by combining the reading problem coefficient of different problem data volume ranges.

[0014] A further technical solution is that the operation data of the RPA robot is determined based on the parsing results of the operation logs of the RPA robot of the service platform.

[0015] A further technical solution is that the read failure data includes the file type, file data volume, and corresponding time corresponding to different read failure counts.

[0016] A further technical solution is that the overlapping operation data includes the historical call counts of different business interfaces of the RPA robot all being in the problem data volume range, as well as the runtime of different historical call counts.

[0017] A further technical solution involves determining whether the business interface of the RPA robot needs to be optimized, specifically including:

[0018] The problem data volume ranges of different business interfaces are combined and processed, and different overlapping operation reference states are determined by using the problem data volume ranges of different business interfaces as variables.

[0019] The historical call count and runtime of different historical call counts are determined by the overlapping operation data under different overlapping operation reference states. The operation problem coefficient under different overlapping operation reference states is determined by combining the reading problem coefficient of the problem data volume range of different business interfaces under the overlapping operation reference states.

[0020] The comprehensive operational problem coefficient of the RPA robot is determined based on the operational problem coefficients under different overlapping operational reference states, and the comprehensive operational problem coefficient is used to determine whether the business interface of the RPA robot needs to be optimized.

[0021] A further technical solution is that when the overall operational problem coefficient of the RPA robot does not meet the requirements, it is determined that the business interface of the RPA robot needs to be optimized.

[0022] The beneficial effects of this invention are as follows:

[0023] 1. By utilizing read failure data within different file data volume ranges, it is determined whether the PRA robot has any business interfaces whose operating status does not meet the requirements. This avoids the technical problem of not being able to comprehensively consider different business interfaces due to solely considering the read failure data of the RPA robot. It achieves the screening of business interfaces whose operating status does not meet the requirements from the perspective of read failure data, ensuring the reliability of the operating status of business interfaces, and also avoiding the impact of abnormal read failure data of a certain business interface on the normal operation of the RPA robot.

[0024] 2. By analyzing overlapping operational data within different problem data ranges of various business interfaces and the reading problem coefficients within different problem data ranges, it is determined whether optimization of the RPA robot's business interfaces is necessary. This approach comprehensively considers abnormal operational situations where different business interfaces of the RPA robot are all within problem data ranges, avoiding technical issues such as the RPA robot's operational status failing to meet requirements due to frequent abnormal operation. It enables differentiated optimization of the RPA robot's business interfaces, ensuring the operational reliability of the RPA robot.

[0025] Other features and advantages will be set forth in the description which follows, and will be apparent in part from the description, or may be learned by practicing the invention. The objects and other advantages of the invention are realized and obtained through the structures particularly pointed out in the description and the drawings.

[0026] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, preferred embodiments are described below in detail with reference to the accompanying drawings. Attached Figure Description

[0027] The above and other features and advantages of the present invention will become more apparent from a detailed description of exemplary embodiments thereof with reference to the accompanying drawings.

[0028] Figure 1 This is a flowchart of a service-oriented platform-based RPA robot operation monitoring and analysis method;

[0029] Figure 2 This is a flowchart illustrating the method for determining whether the operating status of an RPA robot meets the requirements.

[0030] Figure 3This is a flowchart illustrating the method for determining the reading coefficients of business interfaces across different file data volume ranges. Detailed Implementation

[0031] Exemplary embodiments will now be described more fully with reference to the accompanying drawings. However, these exemplary embodiments can be implemented in many forms and should not be construed as limited to the embodiments set forth herein; rather, they are provided so that the invention will be thorough and complete, and the concept of the exemplary embodiments will be fully conveyed to those skilled in the art. The same reference numerals in the drawings denote the same or similar structures, and therefore their detailed description will be omitted.

[0032] The terms “a,” “one,” “the,” and “the” are used to indicate the existence of one or more elements / components / etc.; the terms “including” and “having” are used to indicate an open-ended meaning of inclusion and that other elements / components / etc. may exist in addition to the listed elements / components / etc.

[0033] To solve the above problems, according to one aspect of the present invention, such as Figure 1 As shown, according to one aspect of the present invention, a method for monitoring and analyzing the operation of an RPA robot based on a service-oriented platform is provided, specifically including:

[0034] S1 uses the parsing results of the RPA robot's operation data on the service platform to obtain the reading failure data of the RPA robot's business interface. Based on the reading failure data of different business interfaces during business processing, if the RPA robot's operation status meets the requirements, proceed to the next step.

[0035] S2 divides the read failure data into different file data ranges based on the corresponding file data, and uses the read failure data in different file data ranges to determine that the PRA robot does not have a business interface whose operating status does not meet the requirements, and then proceeds to the next step.

[0036] S3 determines the reading problem coefficient and problem data range of the business interface in different file data volume ranges based on the reading failure data and historical reading data in different file data volume ranges;

[0037] S4 determines the overlapping running data of the problem data volume range of different business interfaces of the RPA robot based on the analysis results, and determines whether the business interface of the RPA robot needs to be optimized by combining the reading problem coefficient of different problem data volume ranges.

[0038] Furthermore, the operating data of the RPA robot is determined based on the parsing results of the operating logs of the RPA robot on the service platform.

[0039] Specifically, the read failure data includes the file type, file data volume, and corresponding time for different read failure counts.

[0040] It should be noted that, as Figure 2 As shown, determining that the operating status of the RPA robot meets the requirements specifically includes:

[0041] The number of read failures of the RPA robot's business interface is determined by the read failure data when the RPA robot is performing business processing, and the failure read problem coefficient of the RPA robot is determined by the proportion of the read failures in the historical read counts of the RPA robot.

[0042] Identify the business interfaces that have failed to read data and designate them as problematic business interfaces. Determine the interface problem coefficient of different problematic business interfaces based on the number of read failures of the problematic business interfaces. Determine the interface problem coefficient of the RPA robot based on the proportion of the problematic business interfaces in the number of business interfaces of the RPA robot and the interface problem coefficient of different problematic business interfaces.

[0043] The operating status value of the RPA robot is determined by the failure reading problem coefficient and the interface problem coefficient, and the operating status value is used to determine whether the operating status of the RPA robot meets the requirements.

[0044] Furthermore, if the operating status value of the RPA robot is not within the preset range, it is determined that the operating status of the RPA robot does not meet the requirements.

[0045] It is understandable that when the operating status of the RPA robot does not meet the requirements, it is determined that the business interface of the RPA robot needs to be optimized.

[0046] Additionally, it should be noted that ensuring the RPA robot's operating status meets the requirements specifically includes:

[0047] S11 determines the number of read failures of the RPA robot's business interface based on the read failure data when the RPA robot is performing business processing, obtains the business interface with read failure data, and identifies it as the problematic business interface.

[0048] S12 determines the interface problem coefficient of different problematic service interfaces by the number of read failures of the problematic service interfaces;

[0049] S13 determines the interface problem coefficient of the RPA robot based on the proportion of the problematic business interfaces in the number of business interfaces of the RPA robot and the interface problem coefficient of different problematic business interfaces. The running status value of the RPA robot is determined by the failure reading problem coefficient and the interface problem coefficient of the RPA robot, and the running status value is used to determine whether the running status of the RPA robot meets the requirements.

[0050] Optionally, step S11 above includes the following:

[0051] S111 determines the number of read failures of the RPA robot's business interface based on the read failure data when the RPA robot is performing business processing, and determines whether the number of read failures of the RPA robot's business interface is greater than the preset number of failures. If yes, proceed to the next step; otherwise, proceed to step S12.

[0052] S112 determines the failure reading problem coefficient of the RPA robot by using the proportion of the number of read failures in the historical read counts of the RPA robot, and determines whether the failure reading problem coefficient of the RPA robot meets the requirements. If yes, proceed to the next step; otherwise, determine that the operating status of the RPA robot does not meet the requirements.

[0053] S113 Obtain the business interface with failed data reading and designate it as the problematic business interface. Determine whether the proportion of the problematic business interface in the number of business interfaces of the RPA robot meets the requirements. If yes, proceed to step S12. If no, determine that the operating status of the RPA robot does not meet the requirements.

[0054] Optionally, step S12 above includes the following:

[0055] The interface problem coefficient of different problem service interfaces is determined by the number of read failures of the problem service interface. It is then determined whether there are any problem service interfaces whose interface problem coefficients do not meet the requirements. If so, it is determined that the running status of the RPA robot does not meet the requirements. If not, proceed to step S13.

[0056] Furthermore, the failed read data is divided into different file data size ranges, specifically including:

[0057] By utilizing the file data size range corresponding to different read failure data, the read failure data is divided into different file data size ranges.

[0058] It is understood that the PRA robot is determined to have no business interfaces whose operating status does not meet the requirements, specifically including:

[0059] Based on the read failure data of the business interface in different file data volume ranges, determine the number of read failures of the business interface in different file data volume ranges, and determine the range problem coefficient of different file data volume ranges based on the number of read failures in different file data volume ranges.

[0060] The range of file data volume with an interval problem coefficient greater than a preset coefficient threshold is used as the filter problem range, and the number of the filter problem ranges is used to determine whether the running status of the business interface meets the requirements.

[0061] It should be noted that when the number of the selected problem intervals is greater than the preset number of intervals, it is determined that the operating status of the business interface does not meet the requirements.

[0062] Furthermore, if the PRA robot does not have any business interfaces whose operating status does not meet the requirements, then it is determined that the business interfaces of the PRA robot need to be optimized.

[0063] It is understood that the PRA robot is determined to have no business interfaces whose operating status does not meet the requirements, specifically including:

[0064] S21 identifies the failed read data within different file data volume ranges using the aforementioned business interface, and denotes the file data volume ranges containing failed read data as potential anomaly ranges.

[0065] S22 determines the interval problem coefficient for different file data size intervals based on the number of read failures within those intervals;

[0066] S23 determines the weight value of different potential anomaly intervals by the proportion of historical reads in different potential anomaly intervals, and determines the comprehensive problem coefficient by combining the interval problem coefficient of different potential anomaly intervals, and uses the comprehensive problem coefficient to determine whether the running status of the business interface meets the requirements.

[0067] Optionally, step S21 includes the following:

[0068] S211 determines whether the number of read failures of the service interface meets the requirements. If yes, proceed to the next step; otherwise, determine that the running status of the service interface does not meet the requirements.

[0069] S212 takes the failed read data of the business interface in different file data volume ranges, and takes the file data volume range with failed read data as potential abnormal ranges. It determines whether the number of potential abnormal ranges meets the requirements. If yes, proceed to the next step; otherwise, proceed to step S22.

[0070] S213 Obtain the number of read failures of the business interface in different potential abnormal intervals, and determine whether the total number of read failures of the business interface in different potential abnormal intervals meets the requirements. If yes, determine that the running status of the business interface meets the requirements. If no, proceed to the next step.

[0071] Based on the number of read failures in different potential abnormal intervals, S214 determines whether there is a potential abnormal interval where the number of read failures exceeds a preset threshold. If yes, proceed to step S22; otherwise, determine that the operating status of the service interface meets the requirements.

[0072] Optionally, step S22 includes the following:

[0073] Based on the number of read failures within different file data volume ranges, determine the range problem coefficient for each file data volume range. Then, determine whether the number of file data volume ranges with range problem coefficients greater than a preset problem coefficient threshold meets the requirements. If yes, proceed to step S23; otherwise, determine that the operating status of the business interface does not meet the requirements.

[0074] Specifically, such as Figure 3 As shown, the method for determining the reading problem coefficient of the business interface in different file data volume ranges is as follows:

[0075] Based on the read failure data of the business interface in the file data volume range, determine the number of read failures of the business interface in the file data volume range, and combine the historical read counts of the business interface in the file data volume range to determine the failure problem coefficient of the file data volume range;

[0076] Based on the historical read data of the business interface in the file data volume range, the read latency of different historical read times in the file data volume range is determined, and the latency problem coefficient of the file data volume range is determined by the proportion of historical read times with read latency greater than a preset duration.

[0077] The reading problem coefficient of the business interface in the file data volume range is determined based on the weights of the latency problem coefficient and the failure problem coefficient.

[0078] Furthermore, the reading problem coefficient of the business interface in the file data volume ranges from 0 to 1. When the reading problem coefficient of the business interface in the file data volume range is greater than a preset problem coefficient threshold, the file data volume range is determined to be a problem data volume range.

[0079] Additionally, it should be noted that the method for determining the reading problem coefficient of the aforementioned business interface in different file data volume ranges is as follows:

[0080] S31 determines the number of times the service interface fails to read within the file data range based on the failed read data of the service interface within the file data range;

[0081] S32 determines the failure problem coefficient of the file data volume range based on the historical number of reads and the number of read failures of the service interface in the file data volume range, determines the latency problem coefficient of the file data volume range by using the proportion of historical reads with a read latency greater than a preset duration, and determines the read problem coefficient of the service interface in the file data volume range based on the weighted sum of the latency problem coefficient and the failure problem coefficient.

[0082] Optionally, step S31 above includes the following:

[0083] S311 determines whether the business interface has read failure data in the file data volume range. If yes, proceed to the next step; otherwise, determine that the file data volume range does not belong to the problem data volume range.

[0084] S312 Based on the read failure data of the service interface in the file data volume range, determine the number of read failures of the service interface in the file data volume range, and determine whether the number of read failures of the service interface in the file data volume range is less than a preset failure number threshold. If yes, proceed to the next step; otherwise, proceed to step S32.

[0085] S313 Based on the historical read data of the service interface in the file data volume range, determine the read latency of different historical read times in the file data volume range, and determine whether the average read latency of different historical read times in the file data volume range is less than the preset latency. If so, determine that the file data volume range does not belong to the problem data volume range. If not, proceed to the next step.

[0086] S314 determines whether the number of historical reads with a read delay greater than a preset duration is less than a preset delay count threshold. If yes, it determines that the file data volume range does not belong to the problem data volume range. If no, it proceeds to step S32.

[0087] Furthermore, the overlapping operation data includes the historical call counts of different business interfaces of the RPA robot all falling within the problem data volume range, as well as the runtime of different historical call counts.

[0088] It is understandable that determining whether the business interface of the RPA robot needs to be optimized includes:

[0089] The problem data volume ranges of different business interfaces are combined and processed, and different overlapping operation reference states are determined by using the problem data volume ranges of different business interfaces as variables.

[0090] The historical call count and runtime of different historical call counts are determined by the overlapping operation data under different overlapping operation reference states. The operation problem coefficient under different overlapping operation reference states is determined by combining the reading problem coefficient of the problem data volume range of different business interfaces under the overlapping operation reference states.

[0091] The comprehensive operational problem coefficient of the RPA robot is determined based on the operational problem coefficients under different overlapping operational reference states, and the comprehensive operational problem coefficient is used to determine whether the business interface of the RPA robot needs to be optimized.

[0092] Furthermore, if the overall operational problem coefficient of the RPA robot does not meet the requirements, then it is determined that the business interface of the RPA robot needs to be optimized.

[0093] The various embodiments in this specification are described in a progressive manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. In particular, the embodiments of apparatus, devices, and non-volatile computer storage media are basically similar to the method embodiments, so the descriptions are relatively simple; relevant parts can be referred to the descriptions of the method embodiments.

[0094] The foregoing has described specific embodiments of this specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims may be performed in a different order than that shown in the embodiments and may still achieve the desired result. Furthermore, the processes depicted in the drawings do not necessarily require the specific or sequential order shown to achieve the desired result. In some embodiments, multitasking and parallel processing are possible or may be advantageous.

[0095] The above description is merely one or more embodiments of this specification and is not intended to limit this specification. Various modifications and variations can be made to the one or more embodiments of this specification by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principle of one or more embodiments of this specification should be included within the scope of the claims of this specification.

Claims

1. A method for monitoring and analyzing the operation of an RPA robot based on a service-oriented platform, characterized in that, Specifically, it includes: Based on the parsing results of the RPA robot's operation data on the service platform, the reading failure data of the RPA robot's business interface is obtained. When the reading failure data of different business interfaces during business processing is determined to meet the requirements, the next step is taken. The read failure data is divided into different file data volume ranges based on the corresponding file data. When the read failure data in different file data volume ranges is used to determine that the RPA robot does not have a business interface whose operating status does not meet the requirements, the next step is performed. Based on the read failure data and historical read data in different file data volume ranges, the read problem coefficient and problem data volume range of the business interface in different file data volume ranges are determined. Based on the analysis results, the overlapping running data of the problem data volume range of different business interfaces of the RPA robot are determined, and the problem coefficients of different problem data volume ranges are combined to determine whether the business interfaces of the RPA robot need to be optimized. Determining that the operating status of the RPA robot meets the requirements specifically includes: The number of read failures of the RPA robot's business interface is determined by the read failure data when the RPA robot is performing business processing, and the failure read problem coefficient of the RPA robot is determined by the proportion of the read failures in the historical read counts of the RPA robot. Identify the business interfaces that have failed to read data and designate them as problematic business interfaces. Determine the interface problem coefficient of the problematic business interface based on the number of read failures. Determine the interface problem coefficient of the RPA robot based on the proportion of the problematic business interfaces in the number of business interfaces of the RPA robot and the interface problem coefficients of different problematic business interfaces. The operating status value of the RPA robot is determined by the failure reading problem coefficient and the interface problem coefficient of the RPA robot, and the operating status value is used to determine whether the operating status of the RPA robot meets the requirements. Determining that the RPA robot does not have any business interfaces whose operating status does not meet the requirements specifically includes: Based on the read failure data of the business interface in different file data volume ranges, determine the number of read failures of the business interface in different file data volume ranges, and determine the range problem coefficient of different file data volume ranges based on the number of read failures in different file data volume ranges. The range of file data volume with an interval problem coefficient greater than a preset coefficient threshold is used as the filter problem range, and the number of the filter problem ranges is used to determine whether the running status of the business interface meets the requirements.

2. The RPA robot operation monitoring and analysis method based on a service-oriented platform as described in claim 1, characterized in that, The operation data of the RPA robot is determined based on the parsing results of the operation logs of the RPA robot of the service platform.

3. The RPA robot operation monitoring and analysis method based on a service-oriented platform as described in claim 1, characterized in that, The read failure data includes the file type, file data size, and corresponding time for different read failure counts.

4. The RPA robot operation monitoring and analysis method based on a service-oriented platform as described in claim 1, characterized in that, When the operating status of the RPA robot does not meet the requirements, it is determined that the business interface of the RPA robot needs to be optimized.

5. The RPA robot operation monitoring and analysis method based on a service-oriented platform as described in claim 1, characterized in that, The failed read data is divided into different file data size ranges, specifically including: By utilizing the file data size range corresponding to different read failure data, the read failure data is divided into different file data size ranges.

6. The RPA robot operation monitoring and analysis method based on a service-oriented platform as described in claim 1, characterized in that, If the RPA robot does not have any business interfaces whose operating status does not meet the requirements, then it is determined that the business interfaces of the RPA robot need to be optimized.

7. The RPA robot operation monitoring and analysis method based on a service-oriented platform as described in claim 1, characterized in that, The overlapping operation data includes the historical call counts of different business interfaces of the RPA robot all falling within the problem data range, as well as the runtime of different historical call counts.

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