WO2021024122A1 - Métodos para el monitoreo de asistentes automatizados - Google Patents
Métodos para el monitoreo de asistentes automatizados Download PDFInfo
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- WO2021024122A1 WO2021024122A1 PCT/IB2020/057237 IB2020057237W WO2021024122A1 WO 2021024122 A1 WO2021024122 A1 WO 2021024122A1 IB 2020057237 W IB2020057237 W IB 2020057237W WO 2021024122 A1 WO2021024122 A1 WO 2021024122A1
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- WIPO (PCT)
- Prior art keywords
- robot
- robots
- time
- user interface
- alert
- Prior art date
Links
- 238000000034 method Methods 0.000 title claims abstract description 48
- 238000012544 monitoring process Methods 0.000 title claims abstract description 13
- 206010000117 Abnormal behaviour Diseases 0.000 claims abstract description 13
- 230000000694 effects Effects 0.000 claims description 27
- 238000003860 storage Methods 0.000 claims description 11
- 238000004519 manufacturing process Methods 0.000 claims description 7
- 238000012423 maintenance Methods 0.000 claims description 6
- 238000004801 process automation Methods 0.000 abstract description 5
- 230000000007 visual effect Effects 0.000 description 14
- 230000008569 process Effects 0.000 description 12
- 238000010200 validation analysis Methods 0.000 description 11
- 238000004590 computer program Methods 0.000 description 5
- 230000015654 memory Effects 0.000 description 4
- 239000003795 chemical substances by application Substances 0.000 description 3
- 238000005259 measurement Methods 0.000 description 3
- 230000003252 repetitive effect Effects 0.000 description 3
- 230000006399 behavior Effects 0.000 description 2
- 238000001514 detection method Methods 0.000 description 2
- 238000013179 statistical model Methods 0.000 description 2
- 238000012795 verification Methods 0.000 description 2
- 238000004458 analytical method Methods 0.000 description 1
- 238000013473 artificial intelligence Methods 0.000 description 1
- 238000003339 best practice Methods 0.000 description 1
- 230000000903 blocking effect Effects 0.000 description 1
- 238000004364 calculation method Methods 0.000 description 1
- 230000015556 catabolic process Effects 0.000 description 1
- 238000004883 computer application Methods 0.000 description 1
- 238000013499 data model Methods 0.000 description 1
- 238000013500 data storage Methods 0.000 description 1
- 230000007812 deficiency Effects 0.000 description 1
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- 238000004513 sizing Methods 0.000 description 1
- 239000013589 supplement Substances 0.000 description 1
Classifications
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J9/00—Programme-controlled manipulators
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B13/00—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
- G05B13/02—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F11/00—Error detection; Error correction; Monitoring
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F11/00—Error detection; Error correction; Monitoring
- G06F11/30—Monitoring
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F9/00—Arrangements for program control, e.g. control units
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F9/00—Arrangements for program control, e.g. control units
- G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
- G06F9/46—Multiprogramming arrangements
- G06F9/48—Program initiating; Program switching, e.g. by interrupt
Definitions
- the present invention is directed to the technical field of desktop monitoring and automated processes by Robotics Desk Automation and Processes.
- Robotic automation is the application of software to automate tasks and processes that humans would otherwise perform.
- Software robots can fully automate essential business transactions through Robotic Process Automation (ARP) or optimize the way people work with Robotic Desktop Automation (ARE).
- ARP Robotic Process Automation
- ARE Robotic Desktop Automation
- the goal of robotic automation is to improve customer experience and operational excellence through increased efficiency, performance, and agility in day-to-day activities across the enterprise.
- ARE is an automation solution that assists an agent in handling simple repetitive tasks, in which the agent plays a facilitating role in the way in which automation is started and finished, depending on its work flow.
- ARP provides automation solutions that do not require the intervention of an agent to develop and are fully self-sustaining.
- the ARP allows to automate processes, reducing human intervention in the execution of computer applications by means of digital robots that are quickly coupled to the applications that are used in companies for repetitive and routine activities, gaining speed, reductions in operating costs and improving the quality and precision of operations and their results.
- These ARP and ARE digital robots are a set of coded commands that inform a computer system of the tasks it must carry out and automate.
- US2017173784 refers to the monitoring, administration and tracking of robots through the use of a robotic console module, whereby an administrator can have access to a holistic view of a plurality of robots running in various workstations of the clients. The administrator also has the ability to start and stop robots and see alerts for robots that are running.
- the method consists of receiving from an ARP system information related to the digital robot that runs in the ARP system to carry out an assigned task, including information on incidents of an anomaly in the RPA system, which occurred while the robot would execute the assigned task, map the incident data according to a common data model, determine a solution to the anomaly based on an analysis carried out through a model trained with artificial intelligence of the mapped incident data and execute the determined resolution.
- FR3038406 refers to a system for monitoring the performance of IT infrastructures, when an application is used, in order to anticipate necessary adjustments in the infrastructure to accelerate the response to incidents that lead to the degradation or interruption of services delivered by the application, which comprises: measurement means for tracking measurement information (may be the time during which a program has been executed); storage means for storing the measurement information; second storage means for memorizing the answers to the problems detected by the monitoring system; a rule machine; service level objective indicators; escalation rules; acceptable limits; memorized best practices; memorized activity periods; in order to establish correlations between this information to anticipate the evolution of resource consumption and thus be able to define proposals for the sizing of the infrastructure.
- EP3451232 refers to an anomaly detection module that can include a time series analyzer that classifies current time series data into at least a plurality of classifications, based on historical data and can build a representative statistical model of current time series data based on at least one of the plurality of classifications.
- An anomaly detector monitors current time series data and identifies statistical outliers, based on the statistical model, and can determine an outlier score by tracking a history of outliers. This document also mentions that outliers are used to report anomalies and / or remediation actions.
- the inventors of the present application have identified in the technical field the need for new computer-implemented methods useful for monitoring and identifying failures in robots in a Robotic Process Automation and Robotic Desk Automation system, which allow the detection of incidents in the processes and automated desktops based on the times of use and the transactions carried out, applicable to robots that are executed both on demand and during regular hours, in order to be able to take corrective measures and thus ensure the correct functioning of the robots digital in time.
- the inventors provide a computer-implemented method that addresses some of these deficiencies.
- the method described here comprises collecting historical information about the robots' uptime and / or the number of transactions carried out; receive information in real time about the activity and inactivity time of the robots and / or the number of transactions carried out by the robots; Based on the information received, determine which robots show abnormal behavior in activity and inactivity times and / or in the number of transactions carried out with respect to historical information; and generate alerts in a user interface for those robots that present abnormal behavior.
- FIG. 1 shows a general schematic of the automated process and desktop monitoring framework in which the method of the present invention is implemented.
- FIG. 2 shows a general robot status validation flow chart for alert generation using a preferred embodiment of the method of the present invention.
- FIG. 3 illustrates a flow chart of a preferred embodiment of the method of the present invention in which the validation of the robots is performed according to their run time. inactivity.
- FIG. 4 illustrates a flow chart of a preferred embodiment of the method of the present invention in which the validation of the robots that are executed in regular hours is performed according to the activity history.
- FIG. 5 illustrates a flow diagram of a preferred embodiment of the method of the present invention where the validation of the robots that are executed on demand is performed.
- FIG. 6 shows a flow chart of a preferred embodiment of the method of the present invention, where the validation of the status of the robots is carried out from the history of the activity of the roles of said robots.
- FIG. 7 illustrates a preferred embodiment of the user interface where the robot controller can view the status of the robots and a summary of all robots and machines.
- FIG. 8 illustrates a preferred embodiment of the user interface where the robot controller can view a summary of the transactions carried out by the robots in each region.
- FIG. 9 illustrates a preferred embodiment of the user interface where the robot controller can view information related to the effectiveness and reasonableness of the figures for each of the Iso robots.
- FIG. 10 illustrates a preferred embodiment of the user interface where the robot controller can view the percentage of successful and failed transactions by region and per day carried out by digital robots.
- the present invention is directed with a computer-implemented method for monitoring robots in a Robotic Process Automation (ARP) and Robotic Desk Automation (ARE) system.
- ARP Robotic Process Automation
- ARE Robotic Desk Automation
- the method can be implemented in systems that comprise one or more processors, computer-readable storage media coupled to the one or more processors, these storage devices having stored instructions that when executed by the one or more processors make the one or more processors execute the different stages of the method that include: collecting historical information on the activity / inactivity time of the robots and / or the number of transactions carried out; receive information in real time about the activity / inactivity time of the robots and / or the number of transactions carried out by the robots; Based on the information received, determine which robots show abnormal behavior in activity / inactivity times and / or in the number of transactions carried out with respect to historical information; and generate alerts in a user interface for those robots that present abnormal behavior.
- the implementation of the method is supported in a database (2) which can preferably be a SQL server, in which the robots (1) or assistants to be monitored are registered .
- the robots and the database can be connected via a network.
- Robots automatically enter data into the database. These data are preferably related to the execution time of the desktops and processes automated by the robots, even more preferably with the start or execution time of the processes and with the end time of the executed processes. Likewise, the data can be related to the number of transactions made by the robots.
- the data that is registered in the database is processed, in order to determine anomalies in the activity and / or in the number of transactions carried out by the robots through logical rules that generate alerts in a user interface (3), allowing a robot controller to display the status of all robots being monitored.
- a first rule consists of determining from the information received from the digital robots, which robots are not in a maintenance state and / or in a pre-production state and for those that have any of these states, not to generate any alert , keeping the state as initial, as exemplified in FIG. 2.
- a robot when a robot is in the pre-production stage, it is possible to generate a color alert on the user interface that can preferably be orange.
- a maintenance state it can be generate a color alert in the user interface that can preferably be white.
- the wizards controller can in the user interface assign any of these states to the digital robots being monitored.
- Another possible rule comprises validating the status of the robot according to idle time, as exemplified in FIG. 3.
- this rule can be applied after determining which wizards are in maintenance and / or pre-production status and discarding them.
- the first measure it is determined, of the robots that are not in maintenance and / or pre-production, which are inactive and whether or not they have started activity on the day. If they have started activity, the time they have been inactive is compared to a predetermined threshold value. If the idle time is greater than the preset threshold, an alert is generated in the user interface, which is preferably a visual alert of one color, which is even more preferably red.
- an alert is generated in the user interface, which is preferably a visual color alert, which is even more preferably green.
- an alert is generated in the interface, which preferably is a visual color alert, which is, even more preferably, blue.
- a further validation may be carried out which involves checking the wizard's activity based on the historical activity data, as illustrated in FIG. 4.
- This additional validation is carried out for robots or assistants that are not executed on demand, that is, they are not activated by a user; they run on a regular schedule.
- the process is not on demand but there is information that indicates that activity started on the day (for example, it is evidenced that at least one transaction ended) even though its current status is inactive, the number of transactions carried out by the robot in the day with the average number of daily transactions made by the robot.
- an alert is generated in the user interface that preferably can be a visual color alert, which is, even more preferably , blue. If, on the other hand, the number of transactions carried out by the robot on the day is less than the average number of daily transactions carried out by the robot, it is verified if the time in which the robot has been inactive on the day is less than or equal to the historical average idle time of the robot. In case the robot's idle time in the day is less than or equal to the historical average idle time of the robot, an alert is generated in the user interface that preferably can be a visual color alert, which is, even more preferably green. On the contrary, if the idle time of the robot in the day is greater At the historical average idle time of the robot, an alert is generated in the user interface which can preferably be a visual alert in color, which is, even more preferably red.
- an alert is generated which can preferably be a visual color alert, which is, even more preferably red, to the user interface. If the verification is positive, a color alert, which is, even more preferably blue, can be sent to the user interface.
- an alert is generated in the user interface that preferably can be a visual alert in color, which is, even more preferably, red. If the number of transactions made by the robot on the day is greater than the average number of daily transactions made by the robot, an alert is generated in the user interface that preferably can be a visual color alert, which is, even more preferably , blue.
- robots that run on a regular schedule are preferably validated from the rules exemplified in FIG. 4.
- Robots that run on demand are preferably validated from the rules exemplified in FIG. 5.
- the validation of both types of robots can be carried out simultaneously or independently.
- a validation of the internal machines that run the robots that are active can be performed, in order to determine if any are off, as illustrated in FIG. 6.
- this validation is done to the robots that operate both on demand and in regular hours and that have been verified using the rules previously described.
- First of all it is verified that the robots are not turned off.
- For robots that are not turned off it is verified that all robot roles are being executed. If all the roles are running, it is checked if there are idle machines, and if there are, an alert for inactivity of one or more machines is generated to the user interface. If all the robot roles are not running, the activity history of the robot roles is checked. If the behavior of the roles is not normal according to the history, an alert is generated in the user interface that preferably can be a visual color alert, which is, even more preferably, red, and an alert for inactivity of one or more machines.
- the number of transactions carried out by a robot in one hour is compared with the average and that their status is completed satisfactorily and not with errors .
- the validation of the machines is carried out taking into account that a single machine can execute more than one role in different periods of time and that different machines can execute different roles simultaneously.
- the user interface can graphically display the number of automated operations that are carried out in certain historical periods of time (last 30 days, last 12 months, etc.) by a single robot, per region. Likewise, it is possible to graphically display the number of operations performed by all the robots in each region on the user interface. Likewise, it is possible to graphically display in the user interface the percentage of successful transactions versus failed transactions, by region, as exemplified in FIG. 10. For each of the robots, depending on the number of successful and failed transactions, the total number of transactions and the average number of executions in a historical period of time, it is possible to calculate a “reasonableness” value, dividing the total number of transactions per day in the average of the executions in a certain period of time.
- a colored alert When the reasonableness value is greater than or equal to 90%, a colored alert will be displayed on the user interface, which is preferably green; When the value of reasonableness is greater than or equal to 85% and less than 90%, a colored alert will be displayed on the user interface, preferably yellow; and when the reasonableness value is less than 85%, a colored alert will be displayed on the user interface, which is preferably red, as exemplified in FIG. 9.
- These parameters are mentioned as an example, since it is possible to carry out the calculation of any parameter (based on the information available in the database) to measure the performance of the robots, to later send them and display them in a user interface to provide information to the robot controller about their operation, as exemplified in figures 7 to 10.
- the present invention is directed to the computer-readable storage medium, coupled to one or more processors, that has stored instructions that when executed by the one or more processors, cause the one or more processors execute any of the operations or rules described above.
- the invention in a third aspect, relates to a system comprising one or more processors, and a computer-readable storage medium, coupled to the one or more processors, which has stored instructions that when executed by the one or more more processors, cause the one or more processors to execute any of the operations or rules described above.
- the described method can be implemented in digital electronic circuits, or in computer hardware, firmware, software, or combinations thereof.
- the apparatus may be implemented in a computer program product tangibly embodied in an information carrier, for example, in a machine-readable storage device for execution by a programmable processor; and the steps of the method can be performed by a programmable processor that executes an instruction program to perform the functions of the described implementations by operating on the input data and generating the output.
- the features described can be advantageously implemented in one or more computer programs that are executable in a programmable system that includes at least one programmable processor coupled to receive data and instructions from and to transmit data and instructions to a data storage system, at least one input device, and at least one output device.
- a computer program is a set of instructions that can be used, directly or indirectly, on a computer to perform a certain activity or achieve a certain result.
- a computer program can be written in any form of programming language, including compiled or interpreted languages, and can be implemented in any form, including as a standalone program or as a module, component, subroutine, or other unit suitable for use. in a computing environment.
- processors suitable for executing an instruction program include, by way of example, general and special purpose microprocessors, and the single processor or one of multiple processors of any type of computer.
- a processor will receive instructions and data from read-only memory or random access memory, or both.
- the essential elements of a computer are a processor to execute instructions and one or more memories to store instructions and data.
- a computer will also include, or be operably coupled to communicate with, one or more mass storage devices for storing data files; Such devices include magnetic drives, such as internal hard drives and removable drives; magneto-optical discs; and optical discs.
- Storage devices suitable for tangibly incorporating instructions and data from computer programs include all forms of non-volatile memory, including by way of example semiconductor memory devices such as EPROM, EEPROM, and flash memory devices; magnetic drives such as internal hard drives and removable drives; magneto-optical discs; and CD-ROM and DVD-ROM discs.
- semiconductor memory devices such as EPROM, EEPROM, and flash memory devices
- magnetic drives such as internal hard drives and removable drives
- magneto-optical discs and CD-ROM and DVD-ROM discs.
- Processor and memory can be supplemented or incorporated into ASICs (Application Specific Integrated Circuits).
- the methods can be implemented in a computer that has a display device such as a CRT monitor (ray tube cathodic) or LCD (liquid crystal display) to display information to the user and a keyboard and pointing device, such as a mouse or trackball, by which the user can provide information to the computer.
- a display device such as a CRT monitor (ray tube cathodic) or LCD (liquid crystal display) to display information to the user and a keyboard and pointing device, such as a mouse or trackball, by which the user can provide information to the computer.
- a keyboard and pointing device such as a mouse or trackball
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- Health & Medical Sciences (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Evolutionary Computation (AREA)
- Medical Informatics (AREA)
- Automation & Control Theory (AREA)
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- Testing And Monitoring For Control Systems (AREA)
Abstract
Description
Claims
Applications Claiming Priority (2)
Application Number | Priority Date | Filing Date | Title |
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CONC2019/0008485 | 2019-08-02 | ||
CONC2019/0008485A CO2019008485A1 (es) | 2019-08-02 | 2019-08-02 | Métodos para el monitoreo de asistentes automatizados |
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WO2021024122A1 true WO2021024122A1 (es) | 2021-02-11 |
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PCT/IB2020/057237 WO2021024122A1 (es) | 2019-08-02 | 2020-07-31 | Métodos para el monitoreo de asistentes automatizados |
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WO (1) | WO2021024122A1 (es) |
Citations (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
WO2015006246A1 (en) * | 2013-07-06 | 2015-01-15 | Cyara Solutions Corp. | System and method for automated chat testing |
US10307906B2 (en) * | 2015-12-22 | 2019-06-04 | Tata Consultancy Services Limited | System and method for providing a proactive process automation among a plurality of software robotic agents in a network |
-
2019
- 2019-08-02 CO CONC2019/0008485A patent/CO2019008485A1/es unknown
-
2020
- 2020-07-31 WO PCT/IB2020/057237 patent/WO2021024122A1/es active Application Filing
Patent Citations (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
WO2015006246A1 (en) * | 2013-07-06 | 2015-01-15 | Cyara Solutions Corp. | System and method for automated chat testing |
US10307906B2 (en) * | 2015-12-22 | 2019-06-04 | Tata Consultancy Services Limited | System and method for providing a proactive process automation among a plurality of software robotic agents in a network |
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