Abstract: A method includes receiving, at computing system, sensor data from a machine, preparing the sensor data for use by data mining algorithms, generating an analysis table based on the prepared sensor data, the analysis table including information and data for a plurality of instances for the machine, and using the information and data included in the analysis table to predict a failure of the machine.

Abstract: An enabled task accessed by a user within a workflow is identified. The workflow is expressed as a Petri net and includes enabled tasks and non-enabled tasks. A non-enabled task selected by a user is identified, and a suitable state that enables the non-enabled state is determined based on the identified enabled task. A simulated workflow for the selected non-enabled task is generated based on the determined suitable state. The simulated workflow is expressed as a Petri net. The user is enabled to navigate through the simulated workflow.

Abstract: Various embodiments of systems and methods for process model extraction and weak-spot analysis from plain event logs are described herein. In an aspect, the method involves obtaining an event log that includes events grouped by process instances. Based on analyzing the event log a process graph is generated. In another aspect, one or more visual representations of the generated process graph, indicating the weak-spots, are generated. At least one of the one or more visual representations of the process model is rendered in response to receiving a selection of the at least one visual representation. In yet another aspect, the weak-spots are transformed into a data structure and provided as input to a rule mining algorithm for generating a set of rules defining the weak-spots. The set of rules received from the rule mining algorithm are rendered on a graphical user interface (GUI).

Abstract: Various embodiments of systems and methods for adapting a reference workflow, according to changing data-contexts, during execution are described herein. The method involves detecting an entry to an adaptive segment in the reference workflow and invoking data context variables associated with the adaptive segment. Further the method includes invoking a set of ordered adaptation rules comprising a set of constraints on the data context variables. In an aspect, the method includes evaluating the rule-set using the one or more data context variables associated with the workflow. Based on the evaluation, a list of adaptation patterns is generated and provided as input to a pattern selector. In another aspect, adaptation patterns from the list of adaptation patterns are recursively called by the pattern selector. The called adaptation patterns are then executed as sub-processes within the adaptive segment.

Abstract: An enabled task accessed by a user within a workflow is identified. The workflow is expressed as a Petri net and includes enabled tasks and non-enabled tasks. A non-enabled task selected by a user is identified, and a suitable state that enables the non-enabled state is determined based on the identified enabled task. A simulated workflow for the selected non-enabled task is generated based on the determined suitable state. The simulated workflow is expressed as a Petri net. The user is enabled to navigate through the simulated workflow.