Authors:
Niels Martin
1
;
Benoît Depaire
2
and
An Caris
2
Affiliations:
1
Hasselt University, Belgium
;
2
Hasselt University and Research Foundation Flanders (FWO), Belgium
Keyword(s):
Business Process Simulation, Event Log Knowledge, Process Mining, Simulation Model Construction Inputs, Conceptual Framework.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Business Process Management
;
Conceptual Modeling
;
Discrete-Event Simulation
;
e-Business
;
Enterprise Engineering
;
Enterprise Information Systems
;
Formal Methods
;
Knowledge Management and Information Sharing
;
Knowledge-Based Systems
;
Simulation and Modeling
;
Symbolic Systems
Abstract:
Business process simulation models are typically built using model construction inputs such as documentation, interviews and observations. Due to issues with these information sources, efforts to further improve the realism of simulation models are valuable. Within this context, the present paper focuses on the use of process execution data in simulation model construction. More specifically, the behaviour of contemporary business processes is increasingly registered in event logs by process-aware information systems. Knowledge can be extracted from these log files using process mining techniques. This paper advocates the addition of event log knowledge as a model construction input, complementary to traditional information sources. A conceptual framework for simulation model construction is presented and the integration of event log knowledge during the modeling of particular simulation model building blocks is outlined. The use of event log knowledge is demonstrated in a simulation
of the operations of a roadside assistance company.
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