# US 11,307,557 B2 · Method for eliminating process anomalies

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- Number: US 11,307,557 B2
- Document ID: US11307557B2
- Status: Granted
- Kind: B2
- Application number: 17/018,296
- Filed: 2020-09-11
- Published: 2021-02-11
- Granted: 2022-04-19
- Earliest claimed: 2018-03-12
- Assignees: Celonis SE
- Applicants: Celonis SE
- Inventors: Alexander Rinke; Martin Klenk
- Web page: https://patentgrep.com/patent/US11307557B2

## CPC

- G05B 19/406: characterised by monitoring or safety (G05B19/19 takes precedence)
- G06F 11/0793: {Remedial or corrective actions (recovery from an exception in an instruction pipeline G06F9/3861; by retry G06F11/1402; for recovering from a failure of a protocol instance or entity H04L69/40)}
- G06F 11/302: {where the computing system component is a software system}
- G06F 11/3447: {Performance evaluation by modeling}
- G06F 11/3476: {Data logging (G06F11/14, G06F11/2205 take precedence)}
- G06Q 10/0639: Performance analysis of employees; Performance analysis of enterprise or organisation operations
- G05B 2219/32179: Quality control, monitor production tool with multiple sensors
- G05B: CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS (systems for controlling or regulating non-electric variables G05D; systems for regulating electric or magnetic variables G05F; control devices or systems insofar as characterised by mechanical features only G05G)
- G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N)
- G06Q: INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR

## Abstract

A method for monitoring process instances that are being executed and for eliminating process anomalies in the process instances is provided. In a monitoring step, a sensor, using a sensor definition, monitors a process log with respect to a process anomaly described in the sensor definition, and detects process instances or processes that have the process anomaly described in the sensor definition. In a correction step, for a process instance detected in the monitoring step, the process anomaly is eliminated at the runtime of the process instance.

## Claims

### Claim 1

A computer-implemented method for monitoring process instances that are being executed and for eliminating process anomalies in said process instances, wherein each process instance comprises a number of process steps, wherein process data for the process steps already executed are stored in at least one process log, wherein the process data for each process step comprise at least
an identifier of the process step,
an identifier with which the process step can be uniquely assigned to a process instance, and
an order of the process step within the process instance,
wherein a process anomaly is described with at least one sensor definition, wherein a process anomaly is associated with a set of generic actions to eliminate the process anomaly, the generic actions each defining a specified action for correcting an anomalous process instance, wherein the generic actions are defined uniformly, and wherein
(a) in a monitoring step a sensor, using the sensor definition, monitors the process log with respect to the process anomaly described in the sensor definition and detects process instances or processes comprising a plurality of process instances, that have the process anomaly described in the sensor definition, and
(b) in a correction step, for a process instance detected in the monitoring step, the process anomaly is eliminated at the runtime of said process instance, wherein
at least one generic action is selected from the set of generic actions assigned to the process anomaly,
based on the selected generic action, a process intervention instance specific to the detected process is created and source-system-specific instructions are generated, and
the process intervention instance is executed to eliminate the process anomaly of the detected process instance.

### Claim 2 (depends on 1)

The method of claim 1, wherein for each process step the process data are stored in the process log during the execution of the process step or at the end of the process step.

### Claim 3 (depends on 1)

The method of claim 1, wherein the sensor definition contains data and/or instructions with which, in the monitoring step, process instances and/or processes are selected from the process log that fulfil a predetermined selection criterion.

### Claim 4 (depends on 3)

The method of claim 3, wherein the selection criterion can be
at least one static or dynamic parameter,
at least one predetermined pattern, and/or
at least one parameter that can be defined by pattern recognition,
wherein, in the case of a deviation or non-deviation from the selection criterion, the selection criterion is fulfilled and a deviation or non-deviation from the selection criterion is indicative of a process anomaly.

### Claim 5 (depends on 1)

The method of claim 1, wherein a process instance has a number of sub-process instances, wherein the process steps of the sub-process instances can be executed in different source systems, and wherein the process data for the already executed process steps of the sub-process instances are combined in the at least one process log.

### Claim 6 (depends on 1)

The method of claim 1, wherein the sensor definition includes information regarding the times at which the monitoring step is performed.

### Claim 7 (depends on 1)

The method of claim 1, wherein the process log is filtered according to predetermined filter criteria before the monitoring step, and wherein the filtered process log is the basis for the monitoring step.

### Claim 8 (depends on 1)

The method of claim 1, wherein the process data stored in the process log can be linked with further auxiliary data describing the particular process instance and/or the particular process step, wherein, when the process intervention instance is generated, it is parameterized with the auxiliary data.

### Claim 9 (depends on 8)

The method of claim 8, wherein the process intervention instance has a number of non-invasive actions and/or a number of invasive actions, wherein
the non-invasive actions are executed outside the source system in which the particular process instance is executed, and
the invasive actions are executed in the source system in which the particular process instance is executed.

### Claim 10 (depends on 9)

The method of claim 9, wherein with an invasive action the course of the particular process instance in the source system is changed and/or controlled.

### Claim 11 (depends on 9)

The method of claim 9, wherein the non-invasive actions and/or the invasive actions are converted into executable instructions for the particular source system.

### Claim 12 (depends on 1)

The method of claim 1, wherein the selection of the at least one generic action from the set of generic actions associated with the process anomaly may be performed in such a way that, for a number of actions or combinations of actions contained in the set of generic actions, a simulation is performed in which it is determined which action or combination of actions applied to the process instance leads best to a predetermined result, wherein this action or combination of actions is selected.

### Claim 13 (depends on 7)

The method of claim 7, wherein the filter criterion is formed by at least one attribute of the process log and the characteristics that this attribute can assume, the characteristics being assigned to a user, wherein, by assigning the characteristics of the attribute to the user, the process anomalies occurring in the filtered process log are also assigned to this user.

### Claim 14 (depends on 1)

The method of claim 1, wherein the process log is stored in a main memory of a computer system, preferably in such a way that successive process steps of a process instance are stored in adjacent memory cells.

### Claim 15 (depends on 6)

The method of claim 6, wherein the monitoring step is performed by an anomaly detection engine and the correction step is performed by an anomaly correction engine, wherein
the anomaly detection engine controls the execution of the sensor, the execution of the sensor being triggered according to the time points specified in the sensor definition, and
the anomaly detection engine passes information about the process instances detected by the sensor to the anomaly correction engine.