Real-Time Repair of Business Processes Based on Alternative Operations in Case of Uncertainty

Owing to the continual evolution of business processes, differences often occur between observable behavior in the event log and the actual operation of the given process model. Whether an iterative and observable deviation occurs between the event log and the process model is in general uncertain. Existing repair techniques add only observable deviations in a fixed manner, which makes it difficult to consider the fitness and the precision of the results simultaneously. To solve this limitation, this study proposes a method of repair that can improve precision as much as possible without affecting the fitness of the results as well as the number of repair-related activities. Patterns of behavior that cannot be replayed are determined by refined reachable activity structures and conformance checks of behavioral relationships. They are optimized by constructing repair or configuration operations. The two operations can be switched based on the identification of iterative observable deviation in the given pattern of behavior during repair. To assess this, datasets from simulated and empirically acquired business processes were used. The proposed method improved the precision of six datasets by 12% on average. Deviations were repeatedly generated by the cycle, because of which the average precision improved by 21% on three datasets with loops.