Abstract: A method of providing process protocols for physical objects, which pass through several production/processing stations in a production/processing line, is provided. In such a method, machine-readable data for uniquely identifying an object are assigned to the object, a reading means is arranged at a production/processing station, by which machine-readable data can be read, a time stamp is assigned to the data, and a process protocol is generated from the machine-readable data, an assignment of the data to the station and/or to the reading means and the time stamp. Each data set describes a process step of a process, and comprises at least a first attribute, in which a unique identification of a process is stored, a second attribute, in which an identification of the process step is stored, and a third attribute, in which a sequence of the process steps within a process is stored.

Abstract: A method is provided for generating process protocols from process data in an IT system with at least one extraction node, at least one storage node, and at least one transformation node. The process may be stored in a client system of the IT system. An application catalog is run on a server system of the IT system, and application templates are managed using the application catalog, each application template having an installation program and configuration data. The installation program is used to instantiate, configure, and run each application template on the server system as an application. The applications being run are monitored and managed by a runtime component on the server system, and the process protocols are ascertained according to a number of control instructions run on nodes, the configuration data of each application comprising information on which control instructions are run on which nodes.

Abstract: A method is provided for providing process protocols for processes carried out by a number of physical devices. A sensor assigned to a physical device detects measured values. Time stamps are assigned to the detected measured values, and the process protocol is generated from the measured values detected by the sensor, from an assignment of the detected measured values to the sensor and/or to the at least one device, and from the time stamp assigned to the measured values. The process protocol has a number of data sets, and each data set of the process protocol has a first attribute, where a unique identification of a process is stored and by which the process step is assigned to the process, a second attribute, where an identification of the process step is stored, and a third attribute, where a sequence of the process steps within a process is stored.

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.

Abstract: A computer-implemented method of creating a process protocol in a local computer system is provided. The local computer system comprises a processor and a storage device, wherein the process protocol is created from raw data, which is stored in part in a first external computer system and in part in a second external computer system, wherein the raw data in the external computer systems is stored in a number of data tables, wherein the raw data comprises data, which is created during the execution of processes in the first external computer system and in the second external computer system.

Abstract: A method is provided for providing process protocols for processes carried out by a number of physical devices. A sensor assigned to a physical device detects measured values. Time stamps are assigned to the detected measured values, and the process protocol is generated from the measured values detected by the sensor, from an assignment of the detected measured values to the sensor and/or to the at least one device, and from the time stamp assigned to the measured values. The process protocol has a number of data sets, and each data set of the process protocol has a first attribute, where a unique identification of a process is stored and by which the process step is assigned to the process, a second attribute, where an identification of the process step is stored, and a third attribute, where a sequence of the process steps within a process is stored.

Abstract: A method of providing process protocols for physical objects, which pass through several production/processing stations in a production/processing line, is provided. In such a method, machine-readable data for uniquely identifying an object are assigned to the object, a reading means is arranged at a production/processing station, by which machine-readable data can be read, a time stamp is assigned to the data, and a process protocol is generated from the machine-readable data, an assignment of the data to the station and/or to the reading means and the time stamp. Each data set describes a process step of a process, and comprises at least a first attribute, in which a unique identification of a process is stored, a second attribute, in which an identification of the process step is stored, and a third attribute, in which a sequence of the process steps within a process is stored.

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.

Abstract: A computer-implemented method is provided for analysis of process data. The method comprises receiving an APE statement (Advanced Process Algebra Execution), wherein the APE statement defines a query of process instances from the storage means, and wherein the APE statement comprises at least one process operator, and executing the APE statement and reading the process instances according to the APE statement from the storage means, and providing the result of the query for further processing.

Abstract: A computer-implemented method is provided for determining parallel process paths in process data. In a first step, a status hierarchy is generated from process steps stored in a storage means, wherein the process steps are read from the storage means and are added to the status hierarchy, and wherein for each added process step, a predecessor/successor relation is added to at least one further process step to the status hierarchy. In a second step, a process hierarchy of the process instance comprising nodes and edges is deduced from the process steps stored in the status hierarchy and the respective predecessor and/or successor relations.

Abstract: A method is provided for generating process protocols from process data in an IT system with at least one extraction node, at least one storage node, and at least one transformation node. The process may be stored in a client system of the IT system. An application catalog is run on a server system of the IT system, and application templates are managed using the application catalog, each application template having an installation program and configuration data. The installation program is used to instantiate, configure, and run each application template on the server system as an application. The applications being run are monitored and managed by a runtime component on the server system, and the process protocols are ascertained according to a number of control instructions run on nodes, the configuration data of each application comprising information on which control instructions are run on which nodes.

Abstract: A computer-implemented method is provided for providing at least one analytics package to a process mining system, wherein the processor is provided with an event log comprising process data of business processes, the process data comprising at least one process element and the process element comprising at least one process step. The event log is stored according to a predetermined data structure comprising at least a first attribute for storing a unique identifier of the process element, a second attribute for storing an identifier of the process step, and a third attribute for storing an order of the process steps. The processor is further provided with auxiliary data and a data model, and the method comprises creating, based on the data model, at least one analytics package.

Abstract: A computer-implemented method of creating a process protocol in a local computer system is provided. The local computer system comprises a processor and a storage device, wherein the process protocol is created from raw data, which is stored in part in a first external computer system and in part in a second external computer system, wherein the raw data in the external computer systems is stored in a number of data tables, wherein the raw data comprises data, which is created during the execution of processes in the first external computer system and in the second external computer system.

Abstract: A computer-implemented method is provided for determining a net throughput time between process steps of a process instance, wherein a processor is used for determining the net throughput time of the process instance in a calendar, in which a number of time intervals is stored, which are to be considered for the determination of the net throughput times, and the processor performs a matching procedure between the time specifications stored for the process steps and the time intervals stored in the calendar, wherein subsequently to the matching procedure, a net throughput time between two process steps is calculated.

Abstract: A computer-implemented method is provided for analysis of process data. The method comprises receiving an APE statement (Advanced Process Algebra Execution), wherein the APE statement defines a query of process instances from the storage means, and wherein the APE statement comprises at least one process operator, and executing the APE statement and reading the process instances according to the APE statement from the storage means, and providing the result of the query for further processing.

Abstract: A computer-implemented method is provided for storing process data. The method comprises allocating a storage area for the process data in the storage means, loading the process data, from the at least one source system, and storing the process steps according to a predetermined data structure in the allocated storage area of the storage means. The predetermined data structure comprises a first attribute, in which a unique identification of the process instance of the respective process step is stored, a second attribute, in which an identification of the respective process step is stored, and a third attribute, in which the sequence of the process steps within a process instance is stored. The method then sorts the process steps in the allocated storage area, wherein the process steps are first sorted according to the first attribute, and subsequently, according to the third attribute.

Abstract: A computer-implemented method is provided for analysis of process data. The method comprises receiving an APE statement (Advanced Process Algebra Execution), wherein the APE statement defines a query of process instances from the storage means, and wherein the APE statement comprises at least one process operator, and executing the APE statement and reading the process instances according to the APE statement from the storage means, and providing the result of the query for further processing.

Abstract: A computer-implemented method is provided for generating an event log from raw data stored in a source system, wherein a processor is provided with a process sensor and the process sensor derives process data from the raw data, wherein the process data comprises at least one process element which comprises at least one process step. The process sensor further generates unique identifies of process elements, identifiers of process steps which are assigned to the process elements, and an order of the process steps, and stores the generated data as an event log according to a predetermined data structure.

Abstract: A computer-implemented method is provided for providing at least one analytics package to a process mining system, wherein the processor is provided with an event log comprising process data of business processes, the process data comprising at least one process element and the process element comprising at least one process step. The event log is stored according to a predetermined data structure comprising at least a first attribute for storing a unique identifier of the process element, a second attribute for storing an identifier of the process step, and a third attribute for storing an order of the process steps. The processor is further provided with auxiliary data and a data model, and the method comprises creating, based on the data model, at least one analytics package.

Abstract: A computer-implemented method is provided for generating an event log from raw data stored in a source system, wherein a processor is provided with a process sensor and the process sensor derives process data from the raw data, wherein the process data comprises at least one process element which comprises at least one process step. The process sensor further generates unique identifies of process elements, identifiers of process steps which are assigned to the process elements, and an order of the process steps, and stores the generated data as an event log according to a predetermined data structure.