An efficient operation audit method and system based on RPA

Abstract

The present invention proposes an efficient operation audit method and system based on RPA, which relates to the field of operation audit technology. The vehicle use process is obtained according to the current rental information of the vehicle, split to obtain the audit group, and obtain each audit package of the vehicle, and the remaining life cycle of the vehicle order is obtained, and the remaining life cycle is sorted to obtain the cycle sorting. Each audit group is audited by RPA in the order of the cycle sorting to obtain a preliminary audit result, and the audit information update rate is calculated. The vehicle update data is inserted and re-audited according to the audit information update rate to obtain a secondary judgment result, and an operation abnormality warning and audit accuracy calculation are performed according to the secondary judgment result to determine whether to re-audit and obtain a tertiary judgment result. The present invention can automatically split and manage the vehicle use process, perform efficient and accurate audits through RPA, and perform priority processing according to the remaining life cycle of the vehicle order.

Description

Technical Field

[0001] The present invention proposes an efficient operation audit method and system based on RPA, which relate to the field of operation audit technology, and specifically to the field of efficient operation audit technology based on RPA. Background Art

[0002] With the rapid rise of the sharing economy and travel service industry, vehicle rental services have become more and more common. In order to ensure that vehicles always maintain compliance and safety during use, it is crucial to effectively monitor and manage the vehicle use process. However, existing vehicle rental services have many shortcomings in process monitoring and management, such as cumbersome processes, inefficiency, and inaccurate audits. Therefore, it is necessary to develop an efficient and accurate vehicle use process monitoring and management system to improve the quality and safety of vehicle rental services. Existing vehicle rental services usually rely on manual review and management, which is not only inefficient but also prone to errors. In addition, due to the diversity and complexity of vehicle use processes, traditional manual review methods are difficult to fully cover and accurately judge the compliance of each link. Therefore, a technical solution is needed that can automatically split and manage vehicle use processes and conduct efficient and accurate audits through intelligent algorithms. In addition, the existing technology lacks effective management of the remaining life cycle of vehicle orders. Different vehicles may have different usage frequencies and cycles, so a technical means is needed to sort and prioritize according to the remaining life cycle of vehicle orders to ensure that the vehicles are always in the best use state. Summary of the invention

[0003] The present invention provides an efficient operation audit method and system based on RPA to solve many deficiencies in the process monitoring and management of existing vehicle rental services, such as cumbersome processes, low efficiency, inaccurate audits, etc. Therefore, existing vehicle rental services usually rely on manual review and management, which is not only inefficient but also prone to errors. In addition, due to the diversity and complexity of the vehicle use process, traditional manual review methods are difficult to fully cover and accurately judge the compliance of each link. Therefore, there is a need for a technical solution that can automatically split and manage the vehicle use process and perform efficient and accurate audits through intelligent algorithms.

[0004] The present invention proposes an efficient operation audit method and system based on RPA, the method comprising:

[0005] S11. Obtaining a vehicle use process according to the current rental information of the vehicle, splitting the vehicle use process into multiple process type blocks, extracting the process type blocks of the same type for all vehicles, obtaining an audit group, and obtaining each audit package of the vehicle;

[0006] S21. Obtain the remaining life cycle of the vehicle order, sort the remaining life cycle of the current audit packages of all vehicles, obtain the cycle sorting, and audit each audit group through RPA according to the cycle sorting order to obtain the preliminary audit results;

[0007] S31, obtain the audit abnormality information and combine it with the vehicle information update data, calculate the audit information update rate, perform insertion determination and re-audit determination on the vehicle update data according to the audit information update rate, and obtain a secondary determination result;

[0008] S41. Perform an abnormal operation warning and audit accuracy calculation based on the secondary determination result, determine whether to conduct a re-audit, and obtain a tertiary determination result.

[0009] Furthermore, the S11 includes:

[0010] Obtain the current rental information of each vehicle, and generate a process sheet for the current rental information according to preset process rules through RPA to obtain the vehicle usage process;

[0011] The vehicle use process is divided into a plurality of process type blocks according to preset vehicle process types, the process type blocks are audited and grouped to obtain audit groups, and the audit packages of the workshop orders are obtained according to the process type blocks.

[0012] Furthermore, the audit grouping of the process type blocks to obtain the audit group and obtaining the audit package of the workshop order according to the process type blocks include:

[0013] Extract the corresponding process type block of the vehicle use process of each vehicle's current rental information according to the specific vehicle process type, and obtain the audit group of the specific vehicle process type;

[0014] All process type blocks of each order of each vehicle are packaged to generate an audit package for the corresponding vehicle order. Each vehicle has multiple historical audit packages and one current audit package. Each audit package of each vehicle is subject to targeted supervision and the supervision results are stored.

[0015] Further, the S21 includes:

[0016] For each vehicle's current audit package, a remaining life cycle is generated according to the rental time, and the remaining life cycles of all vehicles are sorted from short to long to obtain a cycle sorting; the remaining life cycle is the remaining rental time or the remaining audit time.

[0017] Multiple process type blocks of each audit group are audited in the order of period sorting to obtain preliminary audit results.

[0018] Further, the S31 includes:

[0019] During the audit process, abnormal audit information is obtained, and vehicle information update data corresponding to the abnormal audit information is obtained, and the audit information update rate is calculated by combining the abnormal audit information with the vehicle information update data;

[0020] The vehicle update data is inserted and judged by the review information update rate to obtain a judgment result, and a judgment is made on whether to review again based on the judgment result to obtain a secondary judgment result.

[0021] Furthermore, the insertion determination of the vehicle update data is performed by using the audit information update rate to obtain the determination result, including:

[0022] When the update rate of the audit information reaches 50%, it is determined to insert the vehicle update data into the original vehicle audit information to obtain the first replacement data;

[0023] When the update rate of the audit information reaches 80%, it is determined to replace the vehicle update data with the original vehicle audit information to obtain second replacement data;

[0024] When the review information update rate does not reach 50%, it is determined to continue to obtain vehicle update information.

[0025] Further, the determining whether to review again according to the determination result to obtain a secondary determination result includes:

[0026] When the update rate of the audit information reaches 50%, a vehicle use process is generated according to the first replacement data, a second audit is performed, and a first audit result is obtained;

[0027] When the update rate of the audit information reaches 80%, a vehicle use process is generated according to the second replacement data, a second audit is performed, and a second audit result is obtained;

[0028] When the update rate of the audit information does not reach 50%, no secondary audit will be conducted and the preliminary audit results will be obtained.

[0029] Further, the S41 includes:

[0030] Acquire audit error information according to the secondary determination result, and issue an operational abnormality warning according to the audit error information;

[0031] Calculate the audit accuracy rate by reviewing the error information and combining it with the secondary judgment results;

[0032] The audit accuracy rate is compared with a preset accuracy rate threshold to obtain a comparison result, and a determination is made based on the comparison result whether to conduct a re-audit to obtain three determination results.

[0033] Furthermore, obtaining audit error information according to the secondary determination result and issuing an operational abnormality warning according to the audit error information include:

[0034] When the audit error information is obtained, the audit error information is marked to obtain error marking information;

[0035] An error warning is generated through the error marking information, and the warning is released after the error information is modified.

[0036] Furthermore, the system comprises:

[0037] An audit grouping module is used to obtain a vehicle use process according to the current rental information of the vehicle, split the vehicle use process into multiple process type blocks, extract the same type of process type blocks of all vehicles, obtain an audit group, and obtain each audit package of the vehicle;

[0038] The cycle sorting module is used to obtain the remaining life cycle of vehicle orders, sort the remaining life cycle of the current audit packages of all vehicles, obtain the cycle sorting, and audit each audit group through RPA according to the cycle sorting order to obtain the preliminary audit results;

[0039] An update determination module is used to obtain audit exception information and combine it with vehicle information update data, calculate the audit information update rate, perform insertion determination and re-audit determination on the vehicle update data according to the audit information update rate, and obtain a secondary determination result;

[0040] The re-audit determination module is used to issue an abnormal operation warning and calculate the audit accuracy rate based on the secondary determination results, determine whether to conduct a re-audit, and obtain the tertiary determination results.

[0041] Beneficial effects of the present invention:

[0042] The present invention proposes an efficient operation audit method and system based on RPA. By splitting the process, the system can manage the use process of each vehicle in more detail to ensure that each link complies with the regulations. The formation of the audit group improves the audit efficiency because the same type of processes can be processed in batches, reducing duplication of work. The audit package provides comprehensive and structured information for auditors, making the audit process more standardized and efficient. Through sorting, the system prioritizes vehicles with a shorter remaining life cycle to ensure that the vehicles always remain in compliance. The use of RPA technology greatly improves the audit efficiency, reduces manual operations, reduces the error rate, and allows more audit tasks to be processed in a shorter time. By processing abnormal information, the system can promptly discover and correct non-compliant situations to ensure the compliance of vehicle use. The calculation of the audit information update rate provides feedback on the audit quality and helps to continuously improve the audit process. Determine whether the timeliness of information affects the audit. Insertion judgment and re-audit judgment ensure the accuracy and completeness of the data and improve the reliability of the entire audit process. Operation abnormality warning can promptly discover potential problems, reduce the occurrence of safety accidents, and ensure the safety of vehicles and passengers. The calculation of the audit accuracy rate provides an evaluation of the effectiveness of the audit process, which helps to discover and improve deficiencies in the process. Re-audit judgment ensures the accuracy and reliability of the audit results and improves the quality of the entire audit process. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 A schematic diagram of an efficient operation audit method based on RPA is shown;

[0044] Figure 2 It is a schematic diagram of the audit package for the audit team;

[0045] Figure 3 It is a schematic diagram of insertion determination;

[0046] Figure 4 This is a schematic diagram of secondary determination. DETAILED DESCRIPTION

[0047] The preferred embodiments of the present invention are described below in conjunction with the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0048] In one embodiment of the present invention, a method and system for efficient operation review based on RPA is proposed by the present invention, and the method includes:

[0049] S11. Obtaining a vehicle use process according to the current rental information of the vehicle, splitting the vehicle use process into multiple process type blocks, extracting the process type blocks of the same type for all vehicles, obtaining an audit group, and obtaining each audit package of the vehicle;

[0050] S21. Obtain the remaining life cycle of the vehicle order, sort the remaining life cycle of the current audit packages of all vehicles, obtain the cycle sorting, and audit each audit group through RPA according to the cycle sorting order to obtain the preliminary audit results;

[0051] S31, obtain the audit abnormality information and combine it with the vehicle information update data, calculate the audit information update rate, perform insertion determination and re-audit determination on the vehicle update data according to the audit information update rate, and obtain a secondary determination result;

[0052] S41. Perform an abnormal operation warning and audit accuracy calculation based on the secondary determination result, determine whether to conduct a re-audit, and obtain a tertiary determination result.

[0053] The working principle of the above technical solution is: based on the current rental information of the vehicle, the system identifies and obtains the vehicle usage process.

[0054] The use process is divided into multiple different process type blocks, which represent different links of vehicle use, such as vehicle inspection, rental preparation, return processing, etc. The system extracts the same type of process type blocks in all vehicles to form audit groups. Each audit group contains a group of process blocks of the same type, which is convenient for centralized audit and management. At the same time, the system generates one or more audit packages for each vehicle, which contain all relevant information that needs to be audited in the vehicle use process. The system obtains the remaining life cycle of each vehicle order, that is, the time from the current state of the vehicle to the next audit or expiration. The remaining life cycle of the current audit packages of all vehicles is sorted to generate a cycle sorting list. The system uses RPA (Robotic Process Automation) technology to audit each audit group in the order of cycle sorting. RPA technology can simulate human operations and automatically perform repetitive tasks. The system obtains audit exception information during the preliminary audit process and updates it in combination with vehicle information. The audit information update rate is calculated, that is, the proportion of abnormal information that needs to be updated, which helps to evaluate the audit quality and the effectiveness of the process. Based on the audit information update rate, the system makes an insertion judgment on the vehicle update data and decides whether the new information needs to be inserted into the vehicle record. At the same time, the system will conduct a re-review based on the update rate. If the update rate is high, a secondary review process may be triggered. The system will issue an abnormal operation warning based on the secondary judgment result. If a possible problem is detected, the relevant personnel will be notified in time to handle it. At the same time, the system calculates the review accuracy rate, that is, the proportion of vehicles that successfully passed the review, which reflects the effectiveness of the review process. Based on the review accuracy rate, the system determines whether a re-review is required. If the review accuracy rate is low, a more stringent re-review process may be triggered.

[0055] The technical effect of the above technical solution is: by splitting the process, the system can manage the use process of each vehicle in a more detailed manner to ensure that each link complies with the regulations. The formation of the audit group improves the audit efficiency, because the same type of process can be processed in batches, reducing duplication of work. The audit package provides comprehensive and structured information for auditors, making the audit process more standardized and efficient. Through sorting, the system prioritizes vehicles with a shorter remaining life cycle to ensure that the vehicles always remain in compliance. The use of RPA technology has greatly improved the audit efficiency, reduced manual operations, reduced the error rate, and allowed more audit tasks to be processed in a shorter time. By processing abnormal information, the system can promptly discover and correct non-compliant situations to ensure the compliance of vehicle use. The calculation of the audit information update rate provides feedback on the audit quality and helps to continuously improve the audit process. Determine whether the timeliness of information affects the audit. Insertion judgment and re-audit judgment ensure the accuracy and completeness of the data and improve the reliability of the entire audit process. Operation abnormality warning can promptly discover potential problems, reduce the occurrence of safety accidents, and ensure the safety of vehicles and passengers. The calculation of the audit accuracy rate provides an evaluation of the effectiveness of the audit process, which helps to discover and improve deficiencies in the process. Re-audit judgment ensures the accuracy and reliability of the audit results and improves the quality of the entire audit process.

[0056] In one embodiment of the present invention, the S11 includes:

[0057] Obtain the current rental information of each vehicle, and generate a process sheet for the current rental information according to preset process rules through RPA to obtain the vehicle usage process;

[0058] The vehicle use process is divided into a plurality of process type blocks according to preset vehicle process types, the process type blocks are audited and grouped to obtain audit groups, and the audit packages of the workshop orders are obtained according to the process type blocks.

[0059] The working principle of the above technical solution is as follows: Based on the Robotic Process Automation (RPA) technology, combined with the preset process rules and vehicle rental information, the comprehensive monitoring and management of the vehicle use process is realized. First, the system obtains the current rental information of each vehicle from multiple data sources. This information may include the vehicle's status, location, rental time, lessee information, etc. Once this information is obtained, the RPA engine will analyze and process this information according to the preset process rules to generate the corresponding process sheet. These process sheets describe in detail the entire process of the vehicle from rental preparation to return processing, ensuring that each step complies with the regulations. Then, the system will split the generated process sheet according to the preset vehicle process type to form multiple process type blocks. Each process type block represents a specific link in the vehicle use process, such as vehicle inspection, rental preparation, return processing, etc. In order to improve the audit efficiency, the system will audit and group these process type blocks to form multiple audit groups. Each audit group contains a group of process type blocks of the same type, which is convenient for centralized audit and management. Finally, according to the specific content of each process type block, the system will obtain the order audit package of the corresponding workshop. These audit packages contain all relevant information that needs to be reviewed during the use of the vehicle, such as vehicle status, lessee information, rental time, etc.

[0060] The technical effects of the above technical solution are as follows: through the automated processing of RPA technology, manual operations are greatly reduced and audit efficiency is improved. At the same time, grouping process type blocks for audit further improves the centralization and efficiency of the audit. RPA technology can accurately and quickly process large amounts of data, avoiding errors and omissions that may be caused by manual operations, thereby improving the accuracy of data. Through comprehensive monitoring and management of vehicle use processes, this technology can promptly discover and correct problems in the process, optimize process management, and improve service quality. By generating detailed process sheets and audit packages, this technology can provide users with more comprehensive and accurate information, thereby improving service quality. In summary, this technology combines RPA technology with preset process rules to achieve efficient and accurate monitoring and management of vehicle use processes, improving audit efficiency, data accuracy, and service quality.

[0061] In one embodiment of the present invention, the audit grouping of the process type blocks to obtain the audit group, and obtaining the audit package of the workshop order according to the process type blocks, includes:

[0062] Extract the corresponding process type block of the vehicle use process of each vehicle's current rental information according to the specific vehicle process type, and obtain the audit group of the specific vehicle process type;

[0063] All process type blocks of each order of each vehicle are packaged to generate an audit package for the corresponding vehicle order. Each vehicle has multiple historical audit packages and one current audit package. Each audit package of each vehicle is subject to targeted supervision and the supervision results are stored.

[0064] The working principle of the above technical solution is as follows: First, the system obtains the current rental information of each vehicle from the database. This information includes the vehicle's status, location, rental time, lessee information, etc. The system selects the corresponding process type blocks from the extracted rental information according to the preset vehicle process types (such as vehicle inspection, rental preparation, return processing, etc.). These process type blocks are key links in the vehicle use process, and each link has specific standards and requirements. For each specific vehicle process type, the system combines the process type blocks of the same type to form a corresponding audit group. In this way, each process type has a corresponding audit group, which is convenient for subsequent unified management and audit. Next, the system packages all relevant process type blocks into an audit package based on each order of each vehicle. Each vehicle will have multiple historical audit packages (representing past audit records) and a current audit package (representing the current audit status). For each audit package of each vehicle, the system will conduct targeted supervision. The content of supervision may include the execution of the process, compliance inspection, etc. The supervision results will be stored for subsequent analysis and improvement.

[0065] The technical effect of the above technical solution is: by classifying and packaging the vehicle use process, the system can manage and audit more efficiently. This reduces the need for manual intervention and improves work efficiency. By accurately extracting and classifying rental information, the system can ensure the accuracy and completeness of the data. This helps with subsequent analysis and decision-making. Targeted supervision of each audit package for each vehicle can promptly detect and correct non-compliance situations, thereby improving the supervision effect. At the same time, the stored supervision results also provide data support for subsequent improvements. Through strict management and supervision of the vehicle use process, the system can ensure that the vehicle is always kept in the best use state, thereby improving the service quality. In summary, through the steps of extraction, classification, packaging and supervision, efficient management and supervision of the vehicle use process are achieved, and management efficiency, data accuracy, supervision effect and service quality are improved.

[0066] In one embodiment of the present invention, the S21 includes:

[0067] For each vehicle's current audit package, a remaining life cycle is generated according to the rental time, and the remaining life cycles of all vehicles are sorted from short to long to obtain a cycle sorting; the remaining life cycle is the remaining rental time or the remaining audit time.

[0068] Multiple process type blocks of each audit group are audited in the order of period sorting to obtain preliminary audit results.

[0069] The working principle of the above technical solution is as follows: for each vehicle's current audit package, the remaining life cycle is generated according to the rental time, and the remaining life cycles of all vehicles are sorted from short to long to obtain a cycle sorting; the remaining life cycle is the remaining rental time or the remaining audit time. According to the order of the cycle sorting, multiple process type blocks of each audit group are audited to obtain preliminary audit results. The audit starts from the process type block with the shortest remaining life cycle of each audit group to ensure that the rules and content of the audit of each audit group are roughly unified, and the ones with the short remaining life cycle are audited first, which improves the audit efficiency while ensuring the audit quality and taking into account the limitations of the order life cycle.

[0070] The technical effect of the above technical solution is: by generating the remaining life cycle of the current audit package of each vehicle according to the rental time, and sorting the remaining life cycles of all vehicles from short to long, the system can give priority to vehicles with shorter remaining life cycles. In this way, not only the timeliness of the audit is guaranteed, but also long waiting or delays are avoided, which greatly improves the audit efficiency. The multiple process type blocks of each audit group are audited in the order of cycle sorting, ensuring that the rules and contents followed by each audit group during the audit are roughly unified. This reduces the influence of human factors and subjective judgments and improves the consistency and fairness of the audit. According to the sorting of the remaining life cycle, the system can reasonably allocate audit resources. For vehicles with shorter remaining life cycles, the system can invest more resources for priority audit, thereby ensuring the quality of the audit and using resources more efficiently. By giving priority to vehicles with shorter remaining life cycles, the technical solution also fully considers the limitations of the order life cycle. This means that the system can complete the audit in time before the end of the order life cycle, avoiding unnecessary troubles and disputes caused by expired orders. In summary, this technical solution significantly improves the audit efficiency by optimizing resource allocation and giving priority to vehicles with a shorter remaining life cycle while ensuring the audit quality, and takes into account the limitations of the order life cycle. This helps to improve the overall quality and user experience of vehicle rental services.

[0071] In one embodiment of the present invention, the S31 includes:

[0072] During the audit process, abnormal audit information is obtained, and vehicle information update data corresponding to the abnormal audit information is obtained, and the audit information update rate is calculated by combining the abnormal audit information with the vehicle information update data;

[0073] The calculation formula for the audit information update rate is:

[0074]

[0075] in, To review the information update rate, is the number of times vehicle information is collected, The duration of vehicle information collection. To preset the vehicle information collection frequency, The amount of vehicle information collected is is the original amount of vehicle information, The original amount of vehicle information is the same as the amount of vehicle information collected. To review the amount of abnormal information.

[0076] The vehicle update data is inserted and judged by the review information update rate to obtain a judgment result, and a judgment is made on whether to review again based on the judgment result to obtain a secondary judgment result.

[0077] The working principle of the above technical solution is as follows: during the audit process, the system will first monitor and capture any audit exception information. Such exception information may include data inconsistency, process violation, time expiration, and any other situations that do not meet the preset audit standards. Once the abnormal information is detected, the system will immediately trigger the exception handling mechanism. Then, the system will obtain the corresponding vehicle information update data from the database based on the captured audit exception information. These update data may include vehicle status changes, lessee information changes, rental time adjustments, etc. Then, the system will calculate the audit information update rate through a certain algorithm based on the audit exception information and vehicle information update data. This update rate reflects the proportion or frequency of vehicle information that needs to be updated due to audit exceptions. Finally, the system uses this audit information update rate to make an insertion judgment on the vehicle update data. This judgment process may involve checking the legality, validity, and whether the updated data matches the current audit status. Based on this judgment result, the system will make a secondary judgment on whether a re-audit is required.

[0078] The technical effects of the above technical solution are: Improved accuracy and reliability of audits: By capturing and processing audit exception information, the system can more accurately identify situations that do not meet audit standards and make corrections in a timely manner, thereby improving the accuracy and reliability of audits. Optimized resource allocation: By making insertion decisions for vehicle update data based on the audit information update rate, the system can more reasonably allocate audit resources, avoid unnecessary audits of data that does not need to be updated, and improve audit efficiency. Improved user experience: By timely capturing and processing audit exception information, the system can respond to user needs and changes more quickly, improving the user experience. Enhanced system flexibility and adaptability: By calculating the audit information update rate and making insertion decisions, the system can more flexibly respond to various audit scenarios and needs, enhancing the system's adaptability and scalability. Through the formula The amount of information in the collected data that is different from the original amount can be calculated, and the ratio of the amount of information to the total amount of information can be calculated by using the formula The ratio of the current acquisition frequency to the preset acquisition frequency can be calculated by using the formula The average proportion of updated data in the original data can be calculated. The vehicle information update rate that takes into account various situations can be calculated through the overall calculation formula, thereby realizing the quantitative processing of vehicle review information updates. In summary, by capturing and processing review exception information, calculating the review information update rate, and making insertion and re-review decisions, the review accuracy, efficiency, user experience and system flexibility are significantly improved.

[0079] In one embodiment of the present invention, the step of performing insertion determination on vehicle update data by using the audit information update rate to obtain a determination result includes:

[0080] When the update rate of the audit information reaches 50%, it is determined to insert the vehicle update data into the original vehicle audit information to obtain the first replacement data;

[0081] When the update rate of the audit information reaches 80%, it is determined to replace the vehicle update data with the original vehicle audit information to obtain second replacement data;

[0082] When the review information update rate does not reach 50%, it is determined to continue to obtain vehicle update information.

[0083] The working principle of the above technical solution is as follows: First, the system continuously monitors and records abnormal information that occurs during the audit process. These abnormal information may involve changes in the status of the vehicle, inconsistencies in the lessee information, adjustments to the rental time, etc. Whenever abnormal information is detected, the system will automatically trigger an abnormality handling process. In the abnormality handling process, the system will first obtain vehicle update data related to the abnormal information. These data usually include the latest vehicle status, lessee information, rental time, etc. Next, the system will calculate the audit information update rate based on the captured abnormal information and the acquired vehicle update data. This update rate is a percentage that reflects the proportion of vehicle information that needs to be updated due to audit anomalies. According to the calculated audit information update rate, the system will perform a series of judgment operations. Specifically: when the audit information update rate reaches 50%, the system will determine to insert the vehicle update data into the original vehicle audit information. This means that on the basis of retaining the original information, some updated information is added or appended to generate the first replacement data. When the audit information update rate reaches 80%, the system will determine to replace the corresponding part of the original vehicle audit information with the vehicle update data. This means that most or all of the original information will be replaced by the updated data, thus generating the second replacement data. If the audit information update rate does not reach 50%, the system will determine that the abnormal information has little impact on the vehicle information, so the replacement operation will not be performed immediately. At this time, the system will continue to monitor and obtain vehicle update information, and wait for the next audit cycle or reach a higher update rate threshold before taking corresponding actions.

[0084] The technical effects of the above technical solution are: Improved data accuracy and consistency: By calculating the update rate of audit information and deciding how to process vehicle update data according to its size, the system can more accurately reflect the actual situation of vehicle information and avoid decision-making errors caused by data lag or inaccuracy. Optimized data processing flow: By adopting different processing strategies (insert or replace) according to different update rate thresholds, the system can process a large amount of vehicle information more efficiently, improving the speed and efficiency of data processing. Enhanced system flexibility and adaptability: By setting different update rate thresholds, the system can be flexibly adjusted according to different audit scenarios and requirements, enhancing the flexibility and adaptability of the system. Reduced system maintenance costs: Through automated processing and judgment processes, the system reduces the need for manual intervention, reduces maintenance costs and error rates. In summary, by calculating the update rate of audit information and deciding how to process vehicle update data according to its size, data accuracy is improved, data processing flow is optimized, system flexibility and adaptability are enhanced, and system maintenance costs are reduced.

[0085] In one embodiment of the present invention, the step of determining whether to conduct a re-examination based on the determination result to obtain a secondary determination result includes:

[0086] When the update rate of the audit information reaches 50%, a vehicle use process is generated according to the first replacement data, a second audit is performed, and a first audit result is obtained;

[0087] When the update rate of the audit information reaches 80%, a vehicle use process is generated according to the second replacement data, a second audit is performed, and a second audit result is obtained;

[0088] When the update rate of the audit information does not reach 50%, no secondary audit will be conducted and the preliminary audit results will be obtained.

[0089] The working principle of the above technical solution is as follows: when the update rate of the audit information reaches 50%, the system determines to insert the vehicle update data into the original vehicle audit information to generate the first replacement data. Subsequently, the system regenerates the vehicle use process based on these first replacement data. This process involves re-evaluation of the vehicle status, confirmation of the lessee information, and adjustment of the rental time. After generating the new vehicle use process, the system will conduct a secondary review. According to the inserted data, the original data is deleted as reference data. The secondary review may include process compliance checks, data consistency verification, etc. to ensure that the new use process meets all requirements and standards. After completing the secondary review, the system obtains the first review result, which is the final judgment on whether the vehicle use process meets the requirements. When the update rate of the audit information reaches 80%, the system determines to replace the corresponding part of the original vehicle audit information with the vehicle update data to generate the second replacement data. This means that most or all of the original vehicle information has been replaced by the updated data. Based on these second replacement data, the system will rebuild the vehicle use process. The original information is corrected according to the replacement information, and then the system will also conduct a secondary review. This audit may be more rigorous and comprehensive because most of the vehicle information has changed. After completing the second audit, the system obtains the second audit result, which reflects whether the vehicle use process still complies with all regulations and requirements after a large amount of information has been updated. If the audit information update rate does not reach 50%, it means that the changes in vehicle information are small or there are no significant changes. In this case, the system determines that a second audit is not required. Therefore, the system will directly output the preliminary audit result, which is based on the original vehicle audit information and may contain some minor warnings or suggestions, but does not require large-scale adjustments or re-audits of the vehicle use process.

[0090] The technical effect of the above technical solution is: according to different audit information update rates, the system can flexibly adjust the audit strategy, so as to more accurately reflect the actual changes in vehicle information and improve the pertinence of the audit. By setting different thresholds, the system can trigger a secondary audit when necessary, avoid unnecessary audit operations, optimize the audit process, and improve audit efficiency. Whether it is a secondary audit based on the first replacement data or the second replacement data, it can ensure that the vehicle use process meets all requirements and standards, thereby ensuring the safety and compliance of vehicle use. By reasonably controlling the triggering conditions of the secondary audit, the system reduces unnecessary audit work, reduces audit costs, and improves overall economic benefits. In summary, this working principle improves the accuracy of the audit, optimizes the audit process, ensures the safety and compliance of the vehicle use process, and reduces the audit cost by flexibly responding to different audit information update rates.

[0091] In one embodiment of the present invention, the S41 includes:

[0092] Acquire audit error information according to the secondary determination result, and issue an operational abnormality warning according to the audit error information;

[0093] Calculate the audit accuracy rate by reviewing the error information and combining it with the secondary judgment results;

[0094] The calculation formula for the audit accuracy rate is:

[0095]

[0096] in, To check the accuracy, To review the amount of abnormal information, is the abnormal information correction amount, The amount of vehicle information collected is is the original amount of vehicle information, To correct the data ratio.

[0097] in, .in, The amount of error information in the secondary judgment result.

[0098] The audit accuracy rate is compared with a preset accuracy rate threshold to obtain a comparison result, and a determination is made based on the comparison result whether to conduct a re-audit to obtain three determination results.

[0099] The working principle of the above technical solution is: obtain audit error information according to the secondary judgment result, and issue an abnormal operation warning according to the audit error information; calculate the audit accuracy rate by combining the audit error information with the secondary judgment result; compare the audit accuracy rate with the preset accuracy rate threshold to obtain a comparison result, and determine whether to re-audit according to the comparison result to obtain a third judgment result. When the audit accuracy rate is greater than or equal to the preset accuracy rate threshold, the audit is terminated; when the audit accuracy rate is less than the preset accuracy rate threshold, the current rental information of the corresponding vehicle is re-audited to obtain a re-audit result.

[0100] The technical effect of the above technical solution is: obtaining audit error information according to the secondary determination result, and making an abnormal operation warning based on it, which can help the operation team to timely discover and deal with potential problems, reduce the operational risks caused by audit errors, and thus improve the overall operational efficiency and safety. By combining the audit error information and the secondary determination result to calculate the audit accuracy rate, the quality and efficiency of the audit process can be more accurately evaluated. This indicator can intuitively reflect the accuracy of the audit work and provide valuable reference data for the operation team. The audit accuracy rate is compared with the preset accuracy rate threshold, and whether to conduct a re-audit is automatically determined based on the comparison result, realizing intelligent decision-making and automated management. This can not only reduce the need for manual intervention, but also improve the efficiency and accuracy of decision-making. When the audit accuracy rate is lower than the preset threshold, the system will re-audit the current rental information of the corresponding vehicle. This mechanism ensures the reliability of the audit process, avoids potential problems caused by audit errors, and ensures the stability and safety of operations. Through the continuous audit and re-audit process, the operation team can continuously collect feedback data, analyze the causes of audit errors, and optimize the audit process accordingly. This can not only improve the efficiency and quality of audit work, but also provide strong support for the sustainable development of the enterprise. In summary, by real-time monitoring of the audit process, accurate calculation of the audit accuracy, intelligent decision-making and automated management, and continuous optimization of the audit process, the operational efficiency and security have been significantly improved, the reliability of the audit process has been enhanced, and a strong guarantee has been provided for the stable development of the company.

[0101] In one embodiment of the present invention, the step of obtaining audit error information according to the secondary determination result and performing an operational abnormality warning according to the audit error information includes:

[0102] When the audit error information is obtained, the audit error information is marked to obtain error marking information;

[0103] An error warning is generated through the error marking information, and the warning is released after the error information is modified.

[0104] The working principle of the above technical solution is as follows: when the system detects error information that occurs during the audit process, it will automatically capture the error information and mark it. The purpose of marking is to clarify the specific content, nature and severity of the error, so as to facilitate subsequent processing and early warning. Based on the marked error information, the system will generate corresponding error warnings. The generation of warnings may involve the classification of error information, priority determination and setting of warning levels. Classification can help the operation team quickly identify the type of error, priority determination can determine the order of handling errors, and the setting of warning levels reflects the severity of the error and the scope of impact on operations. The generated error warning will continue to exist until the corresponding error information is modified. In this process, the warning can serve as a reference and reminder for the operation team to deal with the error in a timely manner. Once the error information is corrected, the system will determine whether the warning has been lifted based on the updated information. If the error has been corrected, the warning will be automatically lifted.

[0105] The technical effect of the above technical solution is: by automatically capturing, labeling and warning error information, the operation team can discover and handle problems more efficiently, reducing the time for manual search and confirmation of errors. The early warning mechanism helps to timely discover anomalies and potential risks in operations, so as to take corresponding measures to avoid or reduce losses and ensure the safety of operations. Through error warnings, the operation team can more clearly understand the links and causes of errors, and then optimize related work processes and specifications to reduce the recurrence of similar errors. The early warning mechanism can prompt team members to respond and handle errors quickly, and improve the team's collaborative efficiency and response speed. By collecting and analyzing error information, the operation team can obtain more data support on the operation status and provide more accurate and comprehensive information for subsequent decision-making.

[0106] In one embodiment of the present invention, the system comprises:

[0107] An audit grouping module is used to obtain a vehicle use process according to the current rental information of the vehicle, split the vehicle use process into multiple process type blocks, extract the same type of process type blocks of all vehicles, obtain an audit group, and obtain each audit package of the vehicle;

[0108] The cycle sorting module is used to obtain the remaining life cycle of vehicle orders, sort the remaining life cycle of the current audit packages of all vehicles, obtain the cycle sorting, and audit each audit group through RPA according to the cycle sorting order to obtain the preliminary audit results;

[0109] An update determination module is used to obtain audit exception information and combine it with vehicle information update data, calculate the audit information update rate, perform insertion determination and re-audit determination on the vehicle update data according to the audit information update rate, and obtain a secondary determination result;

[0110] The re-audit determination module is used to issue an abnormal operation warning and calculate the audit accuracy rate based on the secondary determination results, determine whether to conduct a re-audit, and obtain the tertiary determination results.

[0111] The working principle of the above technical solution is: based on the current rental information of the vehicle, the system identifies and obtains the vehicle usage process.

[0112] The use process is divided into multiple different process type blocks, which represent different links of vehicle use, such as vehicle inspection, rental preparation, return processing, etc. The system extracts the same type of process type blocks in all vehicles to form audit groups. Each audit group contains a group of process blocks of the same type, which is convenient for centralized audit and management. At the same time, the system generates one or more audit packages for each vehicle, which contain all relevant information that needs to be audited in the vehicle use process. The system obtains the remaining life cycle of each vehicle order, that is, the time from the current state of the vehicle to the next audit or expiration. The remaining life cycle of the current audit packages of all vehicles is sorted to generate a cycle sorting list. The system uses RPA (Robotic Process Automation) technology to audit each audit group in the order of cycle sorting. RPA technology can simulate human operations and automatically perform repetitive tasks. The system obtains audit exception information during the preliminary audit process and updates it in combination with vehicle information. The audit information update rate is calculated, that is, the proportion of abnormal information that needs to be updated, which helps to evaluate the audit quality and the effectiveness of the process. Based on the audit information update rate, the system makes an insertion judgment on the vehicle update data and decides whether the new information needs to be inserted into the vehicle record. At the same time, the system will conduct a re-review based on the update rate. If the update rate is high, a secondary review process may be triggered. The system will issue an abnormal operation warning based on the secondary judgment result. If a possible problem is detected, the relevant personnel will be notified in time to handle it. At the same time, the system calculates the review accuracy rate, that is, the proportion of vehicles that successfully passed the review, which reflects the effectiveness of the review process. Based on the review accuracy rate, the system determines whether a re-review is required. If the review accuracy rate is low, a more stringent re-review process may be triggered.

[0113] The technical effect of the above technical solution is: by splitting the process, the system can manage the use process of each vehicle in a more detailed manner to ensure that each link complies with the regulations. The formation of the audit group improves the audit efficiency, because the same type of process can be processed in batches, reducing duplication of work. The audit package provides comprehensive and structured information for auditors, making the audit process more standardized and efficient. Through sorting, the system prioritizes vehicles with a shorter remaining life cycle to ensure that the vehicles always remain in compliance. The use of RPA technology has greatly improved the audit efficiency, reduced manual operations, reduced the error rate, and allowed more audit tasks to be processed in a shorter time. By processing abnormal information, the system can promptly discover and correct non-compliant situations to ensure the compliance of vehicle use. The calculation of the audit information update rate provides feedback on the audit quality and helps to continuously improve the audit process. Determine whether the timeliness of information affects the audit. Insertion judgment and re-audit judgment ensure the accuracy and completeness of the data and improve the reliability of the entire audit process. Operation abnormality warning can promptly discover potential problems, reduce the occurrence of safety accidents, and ensure the safety of vehicles and passengers. The calculation of the audit accuracy rate provides an evaluation of the effectiveness of the audit process, which helps to discover and improve deficiencies in the process. Re-audit judgment ensures the accuracy and reliability of the audit results and improves the quality of the entire audit process.

[0114] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. An efficient operation audit method based on RPA, characterized in that: The method comprises: S11. Obtain a vehicle use process according to the current rental information of the vehicle, split the vehicle use process into multiple process type blocks, extract the process type blocks of the same type for all vehicles, obtain an audit group, and obtain each audit package of the vehicle; Pack all process type blocks of each order of each vehicle into a review package for the corresponding vehicle order; S21. Obtain the remaining life cycle of the vehicle order, sort the remaining life cycle of the current audit packages of all vehicles, obtain the cycle sorting, and audit each audit group through RPA according to the cycle sorting order to obtain the preliminary audit results; Wherein, the S21 includes: For each vehicle's current audit package, the remaining life cycle is generated according to the rental time, and the remaining life cycles of all vehicles are sorted from short to long to obtain the cycle sorting; Audit multiple process type blocks of each audit group according to the order of period sorting to obtain preliminary audit results; S31, obtain the audit abnormality information and combine it with the vehicle information update data, calculate the audit information update rate, perform insertion determination and re-audit determination on the vehicle update data according to the audit information update rate, and obtain a secondary determination result; During the audit process, obtaining audit exception information and obtaining vehicle information update data corresponding to the audit exception information; When the update rate of the audit information reaches 50%, it is determined to insert the vehicle update data into the original vehicle audit information to obtain the first replacement data, generate the vehicle use process according to the first replacement data, conduct a secondary audit, and obtain the first audit result; When the update rate of the audit information reaches 80%, it is determined to replace the vehicle update data with the original vehicle audit information, obtain the second replacement data, generate the vehicle use process according to the second replacement data, conduct a second audit, and obtain the second audit result; When the update rate of the audit information does not reach 50%, it is determined to continue to obtain updated vehicle information without conducting a secondary audit and obtaining a preliminary audit result; The system directly outputs the preliminary review results; S41. Perform an abnormal operation warning and audit accuracy calculation based on the secondary determination result, determine whether to conduct a re-audit, and obtain a tertiary determination result.

2. According to the RPA-based efficient operation audit method of claim 1, it is characterized in that: The S11 includes: Obtain the current rental information of each vehicle, and generate a process sheet for the current rental information according to preset process rules through RPA to obtain the vehicle usage process; The vehicle use process is divided into a plurality of process type blocks according to preset vehicle process types, the process type blocks are audited and grouped to obtain audit groups, and the audit packages of the workshop orders are obtained according to the process type blocks.

3. According to claim 2, an efficient operation audit method based on RPA is characterized in that: The audit grouping of the process type blocks to obtain the audit group, and obtaining the audit package of the workshop order according to the process type blocks, includes: Extract the corresponding process type block of the vehicle use process of each vehicle's current rental information according to the vehicle process type, and obtain the review group of the vehicle process type; Each vehicle has multiple historical audit packages and one current audit package. Each audit package of each vehicle is supervised in a targeted manner and the supervision results are stored.

4. According to the RPA-based efficient operation audit method of claim 1, it is characterized in that: The S31 includes: Calculate the audit information update rate by combining the audit exception information with the vehicle information update data; The vehicle update data is inserted and judged by the review information update rate to obtain a judgment result, and a judgment is made on whether to review again based on the judgment result to obtain a secondary judgment result.

5. According to the RPA-based efficient operation audit method of claim 1, it is characterized in that: The S41 includes: Acquire audit error information according to the secondary determination result, and issue an operational abnormality warning according to the audit error information; Calculate the audit accuracy rate by combining the audit error information with the secondary judgment results; The audit accuracy rate is compared with a preset accuracy rate threshold to obtain a comparison result, and a determination is made based on the comparison result whether to conduct a re-audit to obtain three determination results.

6. According to claim 5, an efficient operation audit method based on RPA is characterized in that: The obtaining of audit error information according to the secondary determination result and performing an operational abnormality warning according to the audit error information include: When the audit error information is obtained, the audit error information is marked to obtain error marking information; An error warning is generated through the error marking information, and the warning is released after the error information is modified.

7. An efficient operation audit system based on RPA, characterized in that: The system comprises: An audit grouping module is used to obtain a vehicle use process according to the current rental information of the vehicle, split the vehicle use process into multiple process type blocks, extract the same type of process type blocks of all vehicles, obtain an audit group, and obtain each audit package of the vehicle; Pack all process type blocks of each order of each vehicle into a review package for the corresponding vehicle order; The cycle sorting module is used to obtain the remaining life cycle of vehicle orders, sort the remaining life cycle of the current audit packages of all vehicles, obtain the cycle sorting, and audit each audit group through RPA according to the cycle sorting order to obtain the preliminary audit results; An update determination module is used to obtain audit exception information and combine it with vehicle information update data, calculate the audit information update rate, perform insertion determination and re-audit determination on the vehicle update data according to the audit information update rate, and obtain a secondary determination result; During the audit process, obtaining audit exception information and obtaining vehicle information update data corresponding to the audit exception information; When the update rate of the audit information reaches 50%, it is determined to insert the vehicle update data into the original vehicle audit information to obtain the first replacement data, generate the vehicle use process according to the first replacement data, conduct a secondary audit, and obtain the first audit result; When the update rate of the audit information reaches 80%, it is determined to replace the vehicle update data with the original vehicle audit information, obtain the second replacement data, generate the vehicle use process according to the second replacement data, conduct a second audit, and obtain the second audit result; When the update rate of the audit information does not reach 50%, it is determined to continue to obtain updated vehicle information without conducting a secondary audit and obtaining a preliminary audit result; The system directly outputs the preliminary review results; The re-audit determination module is used to issue an abnormal operation warning and calculate the audit accuracy rate based on the secondary determination results, determine whether to conduct a re-audit, and obtain the tertiary determination results.

Images