초록 ▼

A system and method is disclosed for generating process simulation parameters. The method discloses: identifying an execution process; partitioning the process in accordance with a partitioning rule; and generating simulation parameters for each partition. The system discloses various means for effe

A system and method is disclosed for generating process simulation parameters. The method discloses: identifying an execution process; partitioning the process in accordance with a partitioning rule; and generating simulation parameters for each partition. The system discloses various means for effecting the method.

대표청구항 ▼

What is claimed is: 1. A method for process simulation, comprising: identifying a process model that models steps of a process; obtaining process execution data, including process instances that are representative of corresponding past executions of the process; partitioning different ones of the p

What is claimed is: 1. A method for process simulation, comprising: identifying a process model that models steps of a process; obtaining process execution data, including process instances that are representative of corresponding past executions of the process; partitioning different ones of the process instances into different partitions in accordance with a partitioning rule; generating simulation parameters for different partitions resulting from said partitioning; modeling the process by generating separate simulation models for the different partitions based on the simulation parameters for said different partitions; and storing the separate simulation models onto a computer-readable medium. 2. The method of claim 1, further comprising: receiving the partitioning rule from a participating user. 3. The method of claim 1, further comprising: receiving the partitioning rule from a clustering module that produces clusters of the process instances. 4. The method of claim 1, further comprising: generating the simulation parameters using a curve fitting tool. 5. A method for process simulation, comprising: identifying a process; partitioning different instances of execution of the process into different partitions in accordance with a partitioning rule; generating simulation parameters for each partition; simulating the process using the simulation parameters; and storing the simulation parameters onto a computer-readable medium. 6. A method for process simulation, comprising: receiving execution process data; receiving partitioning rule data for the execution process; labeling different instances of the execution process with partitioning information in accordance with the partitioning rules; generating simulation parameters for each partition using a curve fitting tool; and simulating the process by using the simulation parameters in a process simulation model engine. 7. An apparatus, comprising: a computer-readable medium storing computer-executable instructions for process simulation, said instructions comprising: identifying a process model that models steps of a process; obtaining process execution data, including process instances that are representative of corresponding past executions of the process; partitioning different ones of the process instances into different partitions in accordance with a partitioning rule; generating simulation parameters for different partitions resulting from said partitioning; modeling the process by generating separate simulation models for the different partitions based on the simulation parameters for said different partitions; and storing the separate simulation models onto a computer-readable medium. 8. The apparatus of claim 7, said instructions further comprising: receiving the partitioning rule from a clustering module. 9. The apparatus of claim 7, said instructions further comprising: generating the simulation parameters using a curve fitting tool. 10. A system for process simulation, comprising a: means for identifying a process model that models steps of a process; means for obtaining process execution data, including process instances that are representative of corresponding past executions of the process; means for partitioning different ones of the process instances into different partitions in accordance with a partitioning rule; means for generating simulation parameters for different partitions resulting from said partitioning; means for modeling the process by generating separate simulation models for the different partitions based on the simulation parameters for said different partitions; and means for storing the separate simulation models onto a computer-readable medium. 11. The system of claim 10, further comprising: means for receiving the partitioning rule from a clustering module. 12. The system of claim 10, further comprising: means for generating the simulation parameters using a curve fitting tool. 13. The method of claim 1, wherein the simulation parameters comprise an indication of how often new process instances are created. 14. The method of claim 1, wherein the simulation parameters comprise a probability that the process will follow a certain flow path. 15. The method of claim 1, wherein the process comprises a customer service process. 16. The method of claim 1, wherein at least one of the partitions is generated by obtaining a user-specified partitioning attribute and then identifying a partitioning threshold with respect to said attribute. 17. The method of claim 3, further comprising: merging the clusters produced by the clustering module. 18. The method of claim 5, wherein the partitioning rule is obtained by clustering past instances of executions of the process based on process attributes of said past instances of executions of the process. 19. The method of claim 5, wherein the simulation parameters comprise an indication of how often new process instances are created. 20. The method of claim 5, wherein the simulation parameters comprise a probability that the process will follow a certain flow path. 21. The method of claim 5, wherein the process comprises a customer service process. 22. The apparatus of claim 7, wherein the simulation parameters comprise a probability that the process will follow a certain flow path. 23. The apparatus of claim 7, wherein the process comprises a customer service process. 24. The apparatus of claim 7, wherein the partitioning rule is obtained by clustering past instances of executions of the process based on similarities of process attributes of said past instances of executions of the process.