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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/21971

Title: Using event logs to model interarrival times in business process simulation
Authors: Martin, Niels
Depaire, Benoît
Caris, An
Issue Date: 2016
Publisher: Springer
Citation: Reichert, M.; Reijers, H.A. (Ed.). Business Process Management Workshops, p. 255-267
Series/Report: Lecture Notes in Business Information Processing
Series/Report no.: 256
Abstract: The construction of a business process simulation (BPS) model requires significant modeling efforts. This paper focuses on modeling the interarrival time (IAT) of entities, i.e. the time between the arrival of consecutive entities. Accurately modeling entity arrival is crucial as it influences process performance metrics such as the average waiting time. In this respect, the analysis of event logs can be useful. Given the limited process mining support for this BPS modeling task, the contribution of this paper is twofold. Firstly, an IAT input model taxonomy for process mining is introduced, describing event log use depending on process and event log characteristics. Secondly, ARPRA is introduced and operationalized for gamma distributed IATs. This novel approach to mine an IAT input model is the first to explicitly integrate the notion of queues. ARPRA is shown to significantly outperform a benchmark approach which ignores queue formation.
Notes: Martin, N (reprint author), Hasselt Univ, Agoralaan Bldg D, B-3590 Diepenbeek, Belgium. niels.martin@uhasselt.be; benoit.depaire@uhasselt.be; an.caris@uhasselt.be
URI: http://hdl.handle.net/1942/21971
DOI: 10.1007/978-3-319-42887-1_21
ISI #: 000387749900023
ISBN: 9783319428864
ISSN: 1865-1348
Category: C1
Type: Proceedings Paper
Validation: ecoom, 2017
Appears in Collections: Research publications

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