비획득 정보 처리를 위한 대체 기반 실시간 비즈니스 프로세스 모니터링 방법론 개발
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초록
Process monitoring provides a real-time access to critical process attributes generated during process executions. A widely used approach for process monitoring is a rule-based monitoring. It detects specific conditions about attributes causing corresponding results, which is defined in If (condition) Then (status) rule. However, when the rule-based approach is applied to a real-time process monitoring that attributes are recorded sequentially along with execution order of tasks, it shows some limitations like no indicator or late warnings. To improve these limitations,we propose a novel approach for real-time process monitoring by adopting imputation for treating unobserved attributes. Imputation aims at replacing missing or non-sampled attributes with any specific unit with similar characteristics. During the real-time monitoring, there exist unobserved attributes according to the real-time progress of ongoing processes, which can be considered as inevitable missing with monitoring period. In this situation, imputation methods can be used to assume probable progress after the period. Therefore, probable outcomes given the current progress of ongoing process can be predicted in real-time during entire monitoring periods.
Abstract
Process monitoring provides a real-time access to critical process attributes generated during process executions. A widely used approach for process monitoring is a rule-based monitoring. It detects specific conditions about attributes causing corresponding results, which is defined in If (condition) Then (status) rule. However, when the rule-based approach is applied to a real-time process monitoring that attributes are recorded sequentially along with execution order of tasks, it shows some limitations like no indicator or late warnings. To improve these limitations,we propose a novel approach for real-time process monitoring by adopting imputation for treating unobserved attributes. Imputation aims at replacing missing or non-sampled attributes with any specific unit with similar characteristics. During the real-time monitoring, there exist unobserved attributes according to the real-time progress of ongoing processes, which can be considered as inevitable missing with monitoring period. In this situation, imputation methods can be used to assume probable progress after the period. Therefore, probable outcomes given the current progress of ongoing process can be predicted in real-time during entire monitoring periods.
참고문헌 (23)
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