CN112700112B - RPA flow adjustment method and device, electronic equipment and storage medium - Google Patents
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Abstract
The embodiment of the invention discloses an RPA flow adjustment method, an RPA flow adjustment device, electronic equipment and a storage medium, wherein the method comprises the following steps: monitoring a flow index of the current flow; when the flow index meets the regulation condition, at least one candidate flow is matched from a preset flow library based on the characteristic information of the current flow, wherein the preset flow library stores all flows and the characteristic information of all flows; updating the current flow based on the at least one candidate flow. The technical scheme provided by the embodiment of the invention can monitor and adjust a certain type of flow in a targeted manner, and if input data and the like are changed, the automatic adjustment of the flow can be realized, manual operation is not needed, personal errors are reduced, and the efficiency of the flow adjustment is improved.
Description
Technical Field
The embodiment of the invention relates to the technical field of artificial intelligence, in particular to an RPA flow adjustment method, an RPA flow adjustment device, electronic equipment and a storage medium.
Background
Robot flow automation (Robotic process automation, RPA) refers to the automation of service processing with software robots, and is a popular field in the current technology field. The RPA robot captures data using a user interface and simulates a human operating application, and can perform various repetitive tasks including logging in applications, moving files or folders, negating or pasting data information, etc.
Traditional RPA flow design often needs to be well understood on business requirements in the early stage of design, and the processing flow of the business is kept unchanged, and the designed flow can be put into use after testing. If the post business processing flow is changed, experienced staff is required to adjust the automatic flow, the subjectivity is strong, and the matching time is long.
Disclosure of Invention
The invention provides an RPA flow adjustment method, an RPA flow adjustment device, electronic equipment and a storage medium, so as to realize analysis and adjustment of each link of a flow, improve the efficiency and accuracy of flow adjustment, and improve the practicability of the flow.
In a first aspect, an embodiment of the present invention provides a method for adjusting RPA procedures, where the method includes:
monitoring a flow index of the current flow;
when the flow index meets the regulation condition, at least one candidate flow is matched from a preset flow library based on the characteristic information of the current flow, wherein the preset flow library stores all flows and the characteristic information of all flows;
updating the current flow based on the at least one candidate flow.
In a second aspect, an embodiment of the present invention further provides an RPA procedure adjustment device, where the device includes:
The flow index monitoring module is used for monitoring the flow index of the current flow;
the candidate flow determining module is used for matching at least one candidate flow from a preset flow library based on the characteristic information of the current flow when the flow index meets the adjustment condition, wherein the preset flow library stores all flows and the characteristic information of all flows;
and a flow updating module, configured to update the current flow based on the at least one candidate flow.
In a third aspect, an embodiment of the present invention further provides an electronic device, including:
one or more processors;
storage means for storing one or more programs,
the one or more programs, when executed by the one or more processors, cause the one or more processors to implement a method for RPA flow adjustment as described in any one of the embodiments of the present invention.
In a fourth aspect, embodiments of the present invention also provide a storage medium containing computer-executable instructions, which when executed by a computer processor, are configured to perform a method of RPA flow adjustment according to any one of the embodiments of the present invention.
According to the technical scheme, the flow index of the current flow is continuously monitored, the flow index is judged, when the flow index meets the adjusting condition, at least one candidate flow is matched from the preset flow library based on the characteristic information of the current flow, and the current flow is updated based on the at least one candidate flow. The technical scheme provided by the embodiment of the invention can monitor and adjust a certain type of flow in a targeted manner, and if input data and the like are changed, the automatic adjustment of the flow can be realized, manual operation is not needed, personal errors are reduced, and the efficiency of the flow adjustment is improved.
Drawings
In order to more clearly illustrate the technical solution of the exemplary embodiments of the present invention, a brief description is given below of the drawings required for describing the embodiments. It is obvious that the drawings presented are only drawings of some of the embodiments of the invention to be described, and not all the drawings, and that other drawings can be made according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a flow chart of an RPA flow adjustment method according to a first embodiment of the present invention;
fig. 2 is a flow chart of an RPA flow adjustment method in a second embodiment of the present invention;
fig. 3 is a flow chart of an RPA flow adjustment method in the third embodiment of the present invention;
FIG. 4 is an exemplary graph of a fuzzy membership function in accordance with a third embodiment of the present invention;
fig. 5 is a schematic structural diagram of an RPA flow adjustment device according to a fourth embodiment of the present invention;
fig. 6 is a schematic structural diagram of an electronic device in a fifth embodiment of the present invention.
Detailed Description
The invention is described in further detail below with reference to the drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the invention and are not limiting thereof. It should be further noted that, for convenience of description, only some, but not all of the structures related to the present invention are shown in the drawings.
Example 1
Fig. 1 is a flow diagram of an RPA flow sorting method according to an embodiment of the present invention, where the embodiment of the present invention is applicable to a case where an automation flow is correspondingly adjusted when running in a specific type, the method may be performed by an RPA flow adjusting device, and the device may be implemented in a form of software and/or hardware.
As shown in fig. 1, the method according to the embodiment of the present invention includes the following steps:
s110, monitoring a flow index of the current flow.
It should be noted that, the flow in the embodiment of the present invention refers to an RPA flow. The current flow refers to a flow used in a certain type, including but not limited to a robotic automation flow. For example, in a financial scenario, a company performs invoice review through a robotic automation process. The flow index refers to a processing effect that can express that data is processed through a flow in a certain type, and the flow index includes, but is not limited to, overall execution efficiency of the flow, execution efficiency of each link in the flow, overall execution quality of the flow, execution quality of each link in the flow, tasks completed by a robot in the flow, tasks completed manually, and the like. When the flow is started, continuously monitoring the flow index of the current flow so as to judge the effect of processing the data by the flow index.
And S120, when the flow index meets the regulation condition, at least one candidate flow is matched from a preset flow library based on the characteristic information of the current flow.
Wherein, the preset flow library stores each flow and characteristic information of each flow. Optionally, the process library stores different types of processes and characteristic information of the processes, such as invoice approval, wage accounting and the like in the financial class. The adjustment condition refers to an adjustment condition that the current flow cannot achieve the expected data processing effect, and the set adjustment condition includes, but is not limited to, a flow name, a name of a key link in the flow, a name of data processed by the key link in the flow, key step information in the link, and the like. Optionally, the setting the feature information in the present invention includes: a flow identifier of the flow and a link identifier of a key link of the flow. When the flow index meets the regulation condition, the characteristic information of the current flow is matched from the characteristic information of each flow in a preset flow library, and at least one candidate flow is determined. It should be understood that the candidate flows herein may be of the same type as the current flow or of a different type.
Optionally, the matching at least one candidate process from a preset process library based on the feature information of the current process includes: respectively determining the similarity between the characteristic information of the current flow and the characteristic information of each flow in the preset flow library; and sequencing all the processes in the preset process library based on the similarity, and determining at least one process in a preset sequencing range as a candidate process.
The process in the preset process library is various types of processes, when the characteristic information of the current process is matched with the characteristic information of each process in the preset process library, the characteristic information of the current process is matched with the characteristic information of each process in different types, and the similarity is determined, and optionally, the process library comprises various types of processes, so that the number of processes is large, after the similarity between each process and the current process is calculated, the similarity is ranked from large to small, and at least one process which is ranked in the front and is divided into a preset ranking range is determined as a candidate process, so that the candidate process can be obtained quickly. Of course, the sorting method is not limited to the above method, and may be a small to large sorting method.
S130, updating the current flow based on the at least one candidate flow.
The update mode includes, but is not limited to, replacement, adjustment, and the like. After determining at least one candidate flow, the current flow may be updated based on the candidate flows, optionally, when there are multiple candidate flows, the multiple candidate flows are sequentially updated to the current flow, and the multiple candidate flows are compared to determine that one of the candidate flows is preferable to update the current flow.
According to the technical scheme, the flow index of the current flow is continuously monitored, the flow index is judged, when the flow index meets the adjusting condition, at least one candidate flow is matched from the preset flow library based on the characteristic information of the current flow, and the current flow is updated based on the at least one candidate flow. The technical scheme provided by the embodiment of the invention can monitor and adjust a certain type of flow in a targeted manner, and if input data and the like are changed, the automatic adjustment of the flow can be realized, manual operation is not needed, personal errors are reduced, and the efficiency of the flow adjustment is improved.
Example two
Fig. 2 is a schematic flow chart of an RPA flow adjustment method according to an embodiment of the present invention, where the embodiment of the present invention is refinement based on the alternative of the foregoing embodiment, and optional step 110 includes: acquiring link characteristics, execution efficiency and execution quality of each link in the current flow, and determining link scores of each link according to the link characteristics, the execution efficiency and the execution quality; and determining the flow index score of the current flow based on the link scores of the links. When the flow index meets the adjustment condition, the method further comprises: determining at least one abnormal link with a link score lower than a preset link score threshold; determining an abnormality reason of the at least one abnormality link, generating prompt information based on link characteristics, execution efficiency and execution quality of each abnormality link and the abnormality reason, and sending the prompt information to a user terminal. Here, technical terms identical or similar to those of the above-described embodiments will not be repeated.
As shown in fig. 2, the RPA procedure adjustment method according to the embodiment of the present invention includes the following steps:
s210, acquiring link characteristics, execution efficiency and execution quality of each link in the current flow, and determining link scores of each link according to the link characteristics, the execution efficiency and the execution quality; and determining the flow index score of the current flow based on the link scores of the links.
The link score is obtained by performing matrix calculation through link characteristics, execution efficiency and execution quality. The flow includes at least one link, and link characteristics include, but are not limited to, operational steps. The execution efficiency includes, but is not limited to, a historical execution efficiency, an execution efficiency of a current link, and the like, where the historical execution efficiency may be a historical execution efficiency of the current link or a historical execution efficiency of a flow. The execution quality includes, but is not limited to, a historical execution error rate, a current link execution error rate, etc., where the historical execution error rate may be a historical execution error rate of the current link or a historical execution error rate of the flow. The process may be performed by machine, manually, or by both. Therefore, if the links are operated cooperatively by a machine and a person, the operation steps in the link characteristics are divided into the operation steps of the machine and the manual operation steps. Similarly, execution quality and execution efficiency need to be divided based on machine and human. The flow index score is used for evaluating the data processing capability of the current flow, the flow can be divided into different grades, higher, middle and lower grades, each grade comprises a flow index score in a preset score range, when the calculated flow index score falls into which grade preset score range, the grade of the current flow is determined, for example, the higher preset score range is 8-10, the middle preset score is 4-6, the lower preset score is 0-2, a fuzzy theory is applied, different boundary points and different curves are set, and the middle linear intersection point between the three areas of higher, middle and lower grades is a fuzzy part, and the membership degree can be calculated by using a gravity center method or a linear proportion method so as to determine which grade preset score range the flow index score falls into. Thus, when the calculated flow index score falls within which preset score range, the corresponding grade can be known. After the link characteristics, the execution efficiency and the execution quality of each link in the current flow are obtained, determining the link score of each link based on the link characteristics, the execution efficiency and the execution quality of each link. Optionally, the link characteristics, the execution efficiency and the execution quality can be calculated in a matrix mode to obtain the link score. Illustratively, the score of the link characteristic, the score of the execution efficiency and the score of the execution quality of each link are obtained first, and then the link score of each link is obtained by means of a matrix. In the step of obtaining the score of the link characteristic, a threshold value of the operation step may be set first, and optionally, the threshold value ranges from greater than 0 to less than 10, for example, the operation step score corresponding to the number of operation steps less than or equal to 5 is 1, the operation step score corresponding to the number of operation steps greater than 5 and less than or equal to 10 is 5, and the operation step score corresponding to the number of operation steps greater than 5 is 9. Thus, the operation step score can be obtained according to the specific operation steps. It should be noted that the manual operation step score calculation mode may be the same as the operation step score calculation mode of the machine, and of course, different thresholds may also be set, and the link characteristic score may be obtained according to the operation step score block without specific limitation. Similarly, the current link execution error rate and the historical error rate in the execution quality, and the current link execution efficiency and the historical execution efficiency in the execution efficiency are set to respective thresholds, and optionally, the threshold range of each threshold is more than 0 and less than 10. Calculating the execution quality score and the execution efficiency score, calculating the link score based on the obtained link characteristic score, the execution quality score and the execution efficiency score, and calculating the flow index score of the current flow based on the link scores, wherein the calculation modes comprise, but are not limited to, averaging, maximum taking, minimum taking and the like.
And S220, when the flow index meets the regulation condition, at least one candidate flow is matched from a preset flow library based on the characteristic information of the current flow.
S230, updating the current flow based on the at least one candidate flow.
Optionally, the updating the current flow based on the at least one candidate flow includes: respectively covering the current flow based on each candidate flow, and acquiring the flow index score of each candidate flow in the running process; determining the maximum flow index score, and determining a candidate flow corresponding to the maximum flow index score as a target flow when the maximum flow index score is larger than a preset score threshold; and covering the current flow based on the target flow.
The target flow is the type of the current flow, the data processing effect achieved by the data processing is better than that of the current flow, and the current flow can be replaced by the target flow after the preset score threshold value is exceeded. And respectively covering the current flow by at least one candidate flow, carrying out data processing based on each candidate flow to obtain the total flow index score of each candidate flow in the operation process, determining the maximum value in the at least one flow index score, comparing the maximum flow index score with a preset score threshold, determining the flow corresponding to the maximum flow index score as a target flow when the maximum flow index score is larger than the preset score threshold, and covering the current flow by the target flow so as to realize the adjustment of the current flow, wherein when the result of the data processing of the current flow is poor, the current flow can be adjusted in time without manually analyzing the flow links, adjusting the flow, improving the flow adjustment efficiency, and avoiding errors caused by manual operation.
S240, when the flow index meets the regulation condition, determining at least one abnormal link with the link score lower than a preset link score threshold; determining an abnormality reason of the at least one abnormality link, generating prompt information based on link characteristics, execution efficiency and execution quality of each abnormality link and the abnormality reason, and sending the prompt information to a user terminal.
The abnormal links refer to links with the ring node score lower than a preset link score threshold. The user terminal comprises a mobile terminal, a computer, a tablet personal computer and the like. The expression form of the prompt information includes but is not limited to text, image, table and the like. For example, the prompt information is: the upper-level lead auditing flow in the financial invoice reimbursement auditing is abnormal, and the generated reasons tend to fail to identify the authenticity of the invoice, wherein the link characteristic score of the link is 5, the execution efficiency score is 2 and the execution quality score is 2. Optionally, an abnormal link library is preset, the abnormal link library includes different types of flows, and a step of possibly generating an abnormality and a reason for generating the abnormality in each link in each flow, when determining that the link score of a certain link is lower than the preset link score, the step of generating the abnormality of the link is obtained, and according to the corresponding type found in the abnormal link library, the corresponding flow and the corresponding link, the reason for generating the abnormality in the step is determined. And generating prompt information based on link characteristics, execution efficiency, execution quality and abnormality reasons of each abnormal link, and sending the prompt information to the user terminal. Optionally, the prompt message further includes a step of exception generation. Optionally, the level of the prompt information may be determined according to the total number of links and the number of abnormal links in the current flow, and when the proportion of the number of abnormal links in the total number of links in the current flow is greater than a first preset value, the prompt information of the first level is sent to the user, which indicates that a larger error may occur in the processing data of the flow, and the process is not suitable for the data processing of the type and needs to be checked and adjusted in an emergency. When the proportion of the number of abnormal links in the current flow is smaller than or equal to a first preset value, a second-level prompt message is sent to the user, the current flow is abnormal, the influence on data transmission is small, and the user can be left with a long time to adjust the flow.
Optionally, updating the current flow based on the at least one candidate flow includes: based on the characteristic information of each abnormal link, matching the updated link of each abnormal link from the at least one candidate flow; updating the abnormal links in the current flow based on the update links correspondingly to form an update flow; and when the flow index score of the updated flow meets a preset score threshold, covering the current flow based on the updated flow.
The characteristic information of the abnormal link includes, but is not limited to, a link name, key steps in the link, and the like, the characteristic information of each link in the candidate flow is determined to be matched based on the characteristic information of the abnormal link, an update link matched with the abnormal link is determined, the update link is replaced with the abnormal link in the current flow, an update flow is formed, the update flow is operated to perform data processing, and for example, when the flow index score of the update flow meets a preset score threshold, the flow index score of the update flow is larger than the preset score threshold. The current flow is covered based on the updated flow, so that the current flow is adjusted, and the current flow can be locally adjusted by the adjustment mode, so that the calculated amount is reduced, and the time cost is reduced.
According to the technical scheme provided by the embodiment of the invention, the link characteristics, the execution efficiency and the execution quality of each link of the current flow are obtained, the link score of each link is determined according to the link characteristics, the execution efficiency and the execution quality, the flow index score of the current flow is determined based on the link score of each link, when the current flow index score is smaller than the preset score threshold value, at least one candidate flow is matched from the preset flow library based on the characteristic information of the current flow, the current flow is respectively covered by each candidate flow, the flow index score of each candidate flow in the operation process is obtained, the maximum flow index score is determined, when the maximum flow index score is larger than the preset score threshold value, the candidate flow corresponding to the maximum flow index score is determined as the target flow, the current flow is covered by the target flow, or the abnormal reasons of at least one abnormal link with the determined link score lower than the preset link score threshold value are also determined, and the link characteristics, the execution efficiency and the execution quality of each abnormal link are generated and the abnormal reason prompt information is sent to the user terminal. The technical scheme of the embodiment of the invention can realize automatic adjustment of the whole flow and improve the efficiency and accuracy of flow adjustment. The method can also realize that various information of the abnormal link is sent to the user terminal in a prompt message mode, and the user adjusts the abnormal link according to the prompt message, so that the user can locally adjust according to actual conditions, and the flow adjustment efficiency is improved.
Example III
Fig. 3 is a flow chart of an RPA flow adjustment method according to an embodiment of the present invention. The embodiment of the present invention is a preferred embodiment of alternatives to the above-described embodiment. Firstly, presetting abnormity and abnormity reasons of part or all links in different types of processes, for example, links of a street reimbursement bill and uploading an invoice image in a financial invoice auditing process, wherein the abnormal uploading of the invoice image is unclear, the abnormity reasons and the invoice type are uncertain. The number of operation steps and the corresponding operation step score of the operation steps in the link characteristic are preset, for example, the operation step score corresponding to the operation step number being less than or equal to 5 is 1, the operation step score corresponding to the operation step number being more than 5 and less than or equal to 10 is 5, and the operation step score corresponding to the operation step number being more than 5 is 9. Of course, the links may include machine operation steps and manual operation steps, and the determination of the operation step score may be calculated in the manner described above. The execution efficiency comprises the historical execution efficiency of the current link and the execution efficiency of the current link, the average step execution time length of the machine operation is less than 0.55 seconds, the machine historical execution efficiency score is 8, the execution time length is more than or equal to 0.55 seconds and less than 15 seconds, the machine historical execution efficiency score is 6, the execution time length is more than 15 seconds, and the machine historical execution efficiency score is 4. The same principle is that the average step execution time of the manual operation is set to be less than 1 minute, the manual historical execution efficiency score is 8, the average step execution time of the manual operation is greater than or equal to 1 minute and less than 10 minutes, the manual historical execution efficiency score is 6, the average step execution time of the manual operation is greater than or equal to 10 minutes and less than 1 hour, the manual historical execution efficiency score is 4, the average step execution time of the manual operation is greater than 1 hour, and the manual historical execution efficiency score is 2. The man-made and machine average step execution scores of the current link are set according to the same principle, and are not repeated here. The execution quality comprises the historical execution error rate of the current link and the current execution error rate of the current link, the historical execution error rate comprises machine operation and manual operation, the machine or the manual operation comprises data problems, environmental problems, processing timeout problems, other problems and the like, and different scores are set according to each problem.
When analyzing the flow, the scores of the various items are calculated by a rule engine mode, and optionally, the flow is adjusted by an interface configuration mode. And acquiring link characteristics through configuration files, and acquiring execution efficiency and execution quality through flow execution data. Then, setting a Java class method corresponding to each rule factor node for writing the called rule template and the fact data, wherein each rule factor node has a plurality of adjusting conditions, such as: the execution efficiency has 3 adjustment conditions, each condition has 1 score, the rule engine determines that the score of the rule factor node can be obtained according to 1 adjustment condition, and the 3 conditions are respectively: the method has the advantages that the execution efficiency of manual intervention is realized, the execution efficiency of no manual intervention is less than 0.1 (unit: second/operation step number), and the execution efficiency of no manual intervention is more than or equal to 0.1 (unit: second/operation step number); each adjustment condition corresponds to a plurality of regular expressions, the regular expressions being composed of: rule entry + operator + score, for example, the execution efficiency without human intervention and with a value less than 0.1 (unit: seconds/number of operating steps) is composed of 2 rule expressions: 1) No manual intervention (manual intervention= 0); 2) The execution time of the links divided by the number of operation steps is less than 0.1 (execution time of the links/number of operation steps < 0.1).
And calculating a two-dimensional matrix from the historical execution error rate and the current execution error rate to obtain an execution quality score, obtaining an execution efficiency score by the same principle, and obtaining a link score by calculating a link characteristic score, the execution efficiency score and the execution quality score through a three-dimensional matrix. For example, the corresponding scores of link characteristics, execution efficiency and execution quality are 7.75, 2.0 and 1.75 respectively. The link scores are obtained through a three-dimensional matrix to obtain 5.6, and after the link scores of all links are obtained in sequence, the average value of all the link scores is obtained to obtain the flow index score. When calculating three dimensions including link characteristics, execution efficiency and execution quality, each dimension has three conditions of high, medium and low, and the node values of the link characteristics, the execution efficiency and the execution quality corresponding to membership functions are as follows: 0. 2, 4, 6, 8, 10. The score is low when the score is in the interval of 0-2, the score is in the interval of 4-6, the score is high when the score is in the interval of 8-10, and the higher the analysis value is, the better the link data processing effect is. The corresponding piecewise function is:
wherein x is 1 Is the parameter setting of the segment interval, and indicates that the node value of the corresponding membership function is: 0. 2, 4, 6, 8, 10.x is a fractional value in one of three dimensions, y 1 Is the ratio of the values of the first dimension configuration high, y' 1 Is the ratio of the values of the low value of the first dimension configuration.
The method comprises the steps of calculating historical execution efficiency (machine operation and/or artificial operation) in the execution efficiency, current execution efficiency (machine operation and/or artificial operation) of a current link to obtain historical execution quality (machine operation and/or artificial operation) in the execution efficiency and the execution quality and current execution quality (machine operation and/or artificial operation) of the current link to obtain the execution quality, applying fuzzy theory in calculation, dividing the calculation into { low, medium and high } three stages, setting different boundary points and different curves, wherein a middle linear intersection point is a fuzzy part, and calculating membership degree by using a gravity center method or a linear proportion method. The fuzzy membership functions are shown in FIG. 4, e.g., x=3, between 2 and 4, where y1 and y' 1 Are all 0.5, when x=3.5, the distance between x and 4 is smaller than the distance between x and 2, where y1=0.75, y' 1 =0.25. For example, the scores corresponding to the link characteristics, the execution efficiency and the execution quality are respectively 7.75, 2.0 and 1.75, the scores corresponding to the link characteristics and the execution efficiency are calculated from three matrixes according to the piecewise function, and the execution quality score is calculated through the three-dimensional matrix specifically as follows:
H 1 ＝(y′ 1 *10+y 1 *9)*y′ 2 +(y′ 1 *8+y 1 *7)y 2 ＝((0.5*7.75-3)*10+(-0.5*7.75+4)*9)*0+((0.5*7.75-3)*8+(-0.5*7.75+4)*7)*1＝0.875*8+0.125*7＝7.875
H 2 ＝(y′ 1 *8+y 1 *7)*y′ 2 +(y′ 1 *7+y 1 *5)y 2 ＝((0.5*7.75-3)*8+(-0.5*7.75+4)*7)*0+((0.5*7.75-3)*7+(-0.5*7.75+4)*5)*1＝0.875*7+0.125*5＝6.75
H 3 ＝(y′ 1 *8+y 1 *7)*y′ 2 +(y′ 1 *7+y 1 *5)y 2 ＝((0.5*7.75-3)*7+(-0.5*7.75+4)*5)*0+((0.5*7.75-3)*6+(-0.5*7.75+4)*3)*1＝0.875*6+0.125*3＝5.625
Wherein: y is 1 : the first dimension configures the high value ratio, y' 1 : the first dimension configures the ratio of low values, y 2 : the second dimension is configured with high value ratio, y' 2 : the second dimension configures a low ratio of values. The three values of high, middle and low execution quality are obtained to be H 1 ＝＝7.875、H 2 ＝＝6.75、H 3 From its membership function, we know that y1=1, y 'when x=1.75' 1 And (0), only taking the third value of 5.625, and accurately obtaining the execution quality score to the value of 5.6, obtaining the link score through the three-dimensional matrix according to the link characteristics, the execution quality and the execution efficiency, further obtaining the flow index score, and adjusting the flow when the flow index score is lower than a preset score threshold value.
And searching matched processes or links in a process library through the process characteristic information, and finding out the first 5 links or processes with the highest matching degree of the same type and the highest matching degree of different types for selection by a machine (only the highest matching degree is needed) or a user. Wherein the calculation formula when matching is: y=x 1 H 1 +X 2 H 2 . Wherein X is 1 ＝1，X 2 Ring fraction/10, h 1 +H 2 =1. Wherein: x is X 1 : a fixed value of the same type 1; h 1 : weights of the same type; x is X 2 : different types of analysis result values/10; h 2 : different types of weights; y: and calculating the total similarity of the processes. Thus, the larger the calculated Y value is, the optimal result we want to find. After searching, the first 5 columns with the largest Y value are listed for selection. Wherein H is 1 And H 2 Can be configured according to actual conditions.
According to the technical scheme, link scores are obtained through obtaining link characteristics, execution quality and execution efficiency, and flow index scores are obtained through calculation based on the link scores, when the flow index scores are smaller than a preset score threshold, similarity matching is conducted through feature information in a flow library, the first five flows with high matching degree are covered on the current flow, and a proper flow is finally obtained through calculation. The RPA flow adjusting method provided by the embodiment of the invention can analyze and judge the rationality and the effectiveness of the flow before the execution after the flow is designed or during and after the execution. If the flow is unreasonable, proper adjustment is needed, and the method of the embodiment of the invention can realize automatic adjustment without searching the root of the flow problem by manual operation, thereby accelerating the speed of flow adjustment, avoiding manual participation in the adjustment flow and reducing errors caused by manual operation.
Example IV
Fig. 5 is a schematic structural diagram of an RPA flow adjustment device according to an embodiment of the present invention, where the RPA flow adjustment device according to the embodiment of the present invention may execute the RPA flow adjustment method according to any embodiment of the present invention, and has functional modules and beneficial effects corresponding to the execution method. As shown in fig. 5, the RPA flow adjustment device according to the embodiment of the present invention includes: a flow index monitoring module 510, a candidate flow determination module 520, and a flow update module 530, wherein:
a flow index monitoring module 510, configured to monitor a flow index of a current flow;
the candidate flow determining module 520 is configured to match at least one candidate flow from a preset flow library based on the characteristic information of the current flow when the flow index meets an adjustment condition, where the preset flow library stores each flow and the characteristic information of each flow;
a flow update module 530, configured to update the current flow based on the at least one candidate flow.
Further, the flow index monitoring module 510 includes:
the flow index score determining submodule is used for acquiring link characteristics, execution efficiency and execution quality of each link in the current flow and determining the link score of each link according to the link characteristics, the execution efficiency and the execution quality; determining a flow index score of the current flow based on the link scores of the links; the link score is obtained by performing matrix calculation through link characteristics, execution efficiency and execution quality.
Further, the feature information includes: a flow identifier of the flow and a link identifier of a key link of the flow.
Further, the candidate flow determination module 520 includes:
the similarity determination submodule is used for respectively determining the similarity between the characteristic information of the current flow and the characteristic information of each flow in the preset flow library;
and the candidate flow determination submodule is used for sequencing all flows in the preset flow library based on the similarity and determining at least one flow in a preset sequencing range as a candidate flow.
Further, the flow update module 530 includes:
the flow index score determining and acquiring submodule is used for respectively covering the current flow based on each candidate flow and acquiring the flow index score of each candidate flow in the operation process;
the target flow determining sub-module is used for determining the maximum flow index score, and determining the candidate flow corresponding to the maximum flow index score as the target flow when the maximum flow index score is larger than a preset score threshold;
and the first current flow determining submodule is used for covering the current flow based on the target flow.
Further, the device further comprises:
the prompt information sending module is used for determining at least one abnormal link with the link score lower than a preset link score threshold value; determining an abnormality reason of the at least one abnormality link, generating prompt information based on link characteristics, execution efficiency and execution quality of each abnormality link and the abnormality reason, and sending the prompt information to a user terminal.
Further, the flow update module 530 includes:
an update link matching sub-module, configured to match update links of each abnormal link from the at least one candidate flow based on feature information of each abnormal link;
an update flow forming sub-module, configured to update an abnormal link in the current flow based on the update link correspondence, and form an update flow;
and the second current flow determining submodule is used for covering the current flow based on the updating flow when the flow index of the updating flow meets a preset score threshold value.
According to the technical scheme, the flow index of the current flow is continuously monitored, the flow index is judged, when the flow index meets the adjusting condition, at least one candidate flow is matched from the preset flow library based on the characteristic information of the current flow, and the current flow is updated based on the at least one candidate flow. The technical scheme provided by the embodiment of the invention can monitor and adjust a certain type of flow in a targeted manner, and if input data and the like are changed, the automatic adjustment of the flow can be realized, manual operation is not needed, personal errors are reduced, and the efficiency of the flow adjustment is improved.
It should be noted that, the units and modules included in the above system are only divided according to the functional logic, but not limited to the above division, so long as the corresponding functions can be implemented; in addition, the specific names of the functional units are also only for distinguishing from each other, and are not used to limit the protection scope of the embodiments of the present invention.
Example five
Fig. 6 is a schematic structural diagram of an electronic device according to an embodiment of the present invention. Fig. 6 shows a block diagram of an exemplary device 60 suitable for use in implementing the embodiments of the present invention. The device 60 shown in fig. 6 is only an example and should not be construed as limiting the functionality and scope of use of embodiments of the invention.
As shown in fig. 6, the device 60 is in the form of a general purpose computing device. The components of device 60 may include, but are not limited to: one or more processors or processing units 601, a system memory 602, and a bus 603 that connects the different system components (including the system memory 602 and the processing units 601).
Bus 603 represents one or more of several types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, a processor, and a local bus using any of a variety of bus architectures. By way of example, and not limitation, such architectures include Industry Standard Architecture (ISA) bus, micro channel architecture (MAC) bus, enhanced ISA bus, video Electronics Standards Association (VESA) local bus, and Peripheral Component Interconnect (PCI) bus.
Device 60 typically includes a variety of computer system readable media. Such media can be any available media that is accessible by device 60 and includes both volatile and nonvolatile media, removable and non-removable media.
The system memory 602 may include computer system readable media in the form of volatile memory such as Random Access Memory (RAM) 604 and/or cache memory 605. The device 60 may further include other removable/non-removable, volatile/nonvolatile computer system storage media. By way of example only, storage system 606 may be used to read from and write to non-removable, nonvolatile magnetic media (not shown in FIG. 6, commonly referred to as a "hard disk drive"). Although not shown in fig. 6, a magnetic disk drive for reading from and writing to a removable non-volatile magnetic disk (e.g., a "floppy disk"), and an optical disk drive for reading from or writing to a removable non-volatile optical disk (e.g., a CD-ROM, DVD-ROM, or other optical media) may be provided. In such cases, each drive may be coupled to bus 603 through one or more data medium interfaces. Memory 602 may include at least one program product having a set (e.g., at least one) of program modules configured to carry out the functions of embodiments of the invention.
A program/utility 608 having a set (at least one) of program modules 607 may be stored in, for example, memory 602, such program modules 607 including, but not limited to, an operating system, one or more application programs, other program modules, and program data, each or some combination of which may include an implementation of a network environment. Program modules 607 generally perform the functions and/or methods of the described embodiments of the invention.
The device 60 may also communicate with one or more external devices 609 (e.g., keyboard, pointing device, display 610, etc.), one or more devices that enable a user to interact with the device 60, and/or any device (e.g., network card, modem, etc.) that enables the device 60 to communicate with one or more other computing devices. Such communication may occur through an input/output (I/O) interface 611. Also, device 60 may communicate with one or more networks such as a Local Area Network (LAN), a Wide Area Network (WAN) and/or a public network, such as the Internet, through network adapter 612. As shown, the network adapter 612 communicates with other modules of the device 60 over the bus 603. It should be appreciated that although not shown in fig. 6, other hardware and/or software modules may be used in connection with device 60, including, but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, data backup storage systems, and the like.
The processing unit 601 executes various functional applications and data processing by running a program stored in the system memory 602, for example, implementing the RPA flow adjustment method provided by the embodiment of the present invention.
Example six
Embodiments of the present invention also provide a storage medium containing computer-executable instructions for performing an RPA procedure adjustment method when executed by a computer processor.
The computer storage media of embodiments of the invention may take the form of any combination of one or more computer-readable media. The computer readable medium may be a computer readable signal medium or a computer readable storage medium. The computer readable storage medium can be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or a combination of any of the foregoing. More specific examples (a non-exhaustive list) of the computer-readable storage medium would include the following: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.
The computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, either in baseband or as part of a carrier wave. Such a propagated data signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination of the foregoing. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.
Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.
Computer program code for carrying out operations for embodiments of the present invention may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, smalltalk, C ++ and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computer (for example, through the Internet using an Internet service provider).
Note that the above is only a preferred embodiment of the present invention and the technical principle applied. It will be understood by those skilled in the art that the present invention is not limited to the particular embodiments described herein, but is capable of various obvious changes, rearrangements and substitutions as will now become apparent to those skilled in the art without departing from the scope of the invention. Therefore, while the invention has been described in connection with the above embodiments, the invention is not limited to the embodiments, but may be embodied in many other equivalent forms without departing from the spirit or scope of the invention, which is set forth in the following claims.
Claims (9)
1. An RPA procedure adjustment method, comprising:
monitoring a flow index of the current flow;
when the flow index meets the regulation condition, at least one candidate flow is matched from a preset flow library based on the characteristic information of the current flow, wherein the preset flow library stores all flows and the characteristic information of all flows;
updating the current flow based on the at least one candidate flow;
the monitoring the flow index of the current flow comprises the following steps:
acquiring link characteristics, execution efficiency and execution quality of each link in the current flow, determining the link score of each link according to the link characteristic score, the execution efficiency score and the execution quality score in the mode of a rule engine;
Determining a flow index score of the current flow based on the link scores of the links;
the link score is obtained by performing matrix calculation through link characteristics, execution efficiency and execution quality.
2. The method of claim 1, wherein the characteristic information comprises: a flow identifier of the flow and a link identifier of a key link of the flow.
3. The method of claim 1, wherein the matching at least one candidate flow from a preset flow library based on the characteristic information of the current flow comprises:
respectively determining the similarity between the characteristic information of the current flow and the characteristic information of each flow in the preset flow library;
and sequencing all the processes in the preset process library based on the similarity, and determining at least one process in a preset sequencing range as a candidate process.
4. The method of claim 1, wherein the updating the current flow based on the at least one candidate flow comprises:
respectively covering the current flow based on each candidate flow, and acquiring the flow index score of each candidate flow in the running process;
Determining the maximum flow index score, and determining a candidate flow corresponding to the maximum flow index score as a target flow when the maximum flow index score is larger than a preset score threshold;
and covering the current flow based on the target flow.
5. The method of claim 1, wherein when the flow index meets an adjustment condition, the method further comprises:
determining at least one abnormal link with a link score lower than a preset link score threshold;
determining an abnormality reason of the at least one abnormality link, generating prompt information based on link characteristics, execution efficiency and execution quality of each abnormality link and the abnormality reason, and sending the prompt information to a user terminal.
6. The method of claim 5, wherein the updating the current flow based on the at least one candidate flow comprises:
based on the characteristic information of each abnormal link, matching the updated link of each abnormal link from the at least one candidate flow;
updating the abnormal links in the current flow based on the update links correspondingly to form an update flow;
and when the flow index score of the updated flow meets a preset score threshold, covering the current flow based on the updated flow.
7. An RPA procedure adjustment device, comprising:
the flow index monitoring module is used for monitoring the flow index of the current flow;
the candidate flow determining module is used for matching at least one candidate flow from a preset flow library based on the characteristic information of the current flow when the flow index meets the adjustment condition, wherein the preset flow library stores all flows and the characteristic information of all flows;
a flow updating module, configured to update the current flow based on the at least one candidate flow;
the flow index monitoring module is specifically configured to obtain link characteristics, execution efficiency and execution quality of each link in the current flow, determine link scores of each link according to a mode characteristic score, an execution efficiency score and an execution quality score of a rule engine, and determine link scores of each link according to the link characteristic score, the execution efficiency score and the execution quality score;
determining a flow index score of the current flow based on the link scores of the links;
the link score is obtained by performing matrix calculation through link characteristics, execution efficiency and execution quality.
8. An electronic device, the device comprising:
One or more processors;
storage means for storing one or more programs,
when executed by the one or more processors, causes the one or more processors to implement the RPA procedure adjustment method of any one of claims 1-6.
9. A storage medium containing computer executable instructions for performing the RPA procedure adjustment method according to any one of claims 1-6 when executed by a computer processor.
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