Abstract
Detecting and measuring resource queues is central to business process optimization. Queue mining techniques allow for the identification of bottlenecks and other process inefficiencies, based on event data. This work focuses on the discovery of resource queues. In particular, we investigate the impact of available information in an event log on the ability to accurately discover queue lengths, i.e. the number of cases waiting for an activity. Full queueing information, i.e. timestamps of enqueueing and exiting the queue, makes queue discovery trivial. However, often we see only the completions of activities. Therefore, we focus our analysis on logs with partial information, such as missing enqueueing times or missing both enqueueing and service start times. The proposed discovery algorithms handle concurrency and make use of statistical methods for discovering queues under this uncertainty. We evaluate the techniques using real-life event logs. A thorough analysis of the empirical results provides insights into the influence of information levels in the log on the accuracy of the measurements.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
van der Aalst, W.M.P.: Process Mining: Discovery, Conformance and Enhancement of Business Processes. Springer, Heidelberg (2011)
Senderovich, A., Weidlich, M., Gal, A., Mandelbaum, A.: Queue mining for delay prediction in multi-class service processes. Technical report (2014)
Nakatumba, J.: Resource-aware business process management: analysis and support. Ph.D. thesis, Eindhoven University of Technology (2013)
Rogge-Solti, A., Mans, R.S., van der Aalst, W.M.P., Weske, M.: Repairing event logs using timed process models. In: Demey, Y.T., Panetto, H. (eds.) OTM 2013 Workshops 2013. LNCS, vol. 8186, pp. 705–708. Springer, Heidelberg (2013)
Leemans, S.J.J., Fahland, D., van der Aalst, W.M.P.: Discovering block-structured process models from event logs - a constructive approach. In: Colom, J.-M., Desel, J. (eds.) PETRI NETS 2013. LNCS, vol. 7927, pp. 311–329. Springer, Heidelberg (2013)
Buijs, J., van Dongen, B., van der Aalst, W.M.P.: A genetic algorithm for discovering process trees. In: IEEE Congress on Evolutionary Computation, pp. 1–8. IEEE (2012)
Adriansyah, A.: Aligning observed and modeled behavior. Ph.D. thesis, Eindhoven University of Technology (2014)
Hastie, T., Tibshirani, R., Friedman, J.: The Elements of Statistical Learning. Springer Series in Statistics. Springer New York Inc., New York (2001)
Neuts, M.F.: Renewal processes of phase type. Nav. Res. Logistics Q. 25(3), 445–454 (1978)
Mandelbaum, A., Zeltyn, S.: Estimating characteristics of queueing networks using transactional data. Queueing systems 29(1), 75–127 (1998)
Mandelbaum, A., Zeltyn, S.: Service engineering in action: the Palm/Erlang-A queue, with applications to call centers. In: Advances in Services Innovations, pp. 17–45. Springer, Heidelberg (2007)
Kingman, J.: On queues in heavy traffic. J. Roy. Stat. Soc. Ser. B (Methodol.) 24, 383–392 (1962)
Asmussen, S.: Phase-type distributions and related point processes: fitting and recent advances. In: International Conference on Matrix-Analytic Methods in Stochastic Models, pp. 137–149 (1996)
Aslett, L.J., Wilson, S.P.: Markov chain monte carlo for inference on phasetype models. ISI (2011)
Leemans, S.J.J., Fahland, D., van der Aalst, W.M.P.: Discovering block-structured process models from event logs containing infrequent behaviour. In: Lohmann, N., Song, M., Wohed, P. (eds.) BPM 2013 Workshops. LNBIP, vol. 171, pp. 66–78. Springer, Heidelberg (2014)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer International Publishing Switzerland
About this paper
Cite this paper
Senderovich, A., Leemans, S.J.J., Harel, S., Gal, A., Mandelbaum, A., van der Aalst, W.M.P. (2016). Discovering Queues from Event Logs with Varying Levels of Information. In: Reichert, M., Reijers, H. (eds) Business Process Management Workshops. BPM 2016. Lecture Notes in Business Information Processing, vol 256. Springer, Cham. https://doi.org/10.1007/978-3-319-42887-1_13
Download citation
DOI: https://doi.org/10.1007/978-3-319-42887-1_13
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-42886-4
Online ISBN: 978-3-319-42887-1
eBook Packages: Computer ScienceComputer Science (R0)