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Autor
Brzychczy Edyta (AGH University of Science and Technology Kraków, Poland)
Tytuł
Process Modelling Based on Event Logs
Źródło
Multidisciplinary Aspects of Production Engineering, 2018, vol. 1, s. 385-392, rys., tab., bibliogr. 18 poz.
Słowa kluczowe
Sieć Petriego, Modelowanie procesów biznesowych
Petri net, Business Process Modeling
Uwagi
streszcz., summ.
Abstrakt
Process modelling is a very important stage in a Business Process Management cycle enabling process analysis and its redesign. Many sources of information for process modelling purposes exist. It may be an analysis of documentation related directly or indirectly to the process being analysed, observations or participation in the process. Nowadays, for this purpose, it is increasingly proposed to use the event logs from organization's IT systems. Event logs could be analysed with process mining techniques to create process models expressed by various notations (i.e. Petri Nets, BPMN, EPC). Process mining enables also conformance checking and enhancement analysis of the processes. In the paper issues related to process modelling and process mining are briefly discussed. A case study, an example of delivery process modelling with process mining technique is presented. (original abstract)
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Bibliografia
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  2. Alotaibi, Y. (2016). Business process modelling challenges and solutions: a literature review. Journal of Intelligent Manufacturing, 27(4), pp. 701-723.
  3. Augusto, A., Conforti, R., Dumas, M., La Rosa, M., Maggi, F., Marrella, A., Mecella, M. and Soo, A. (2017). Automated Discovery of Process from Event Logs: Review and Benchmark. arXiv:1705.02288
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  8. Günther, C.W and van der Aalst, W.M.P. (2006). Mining Activity Clusters from Low-Level Event Logs. BETA Working Paper Series, WP 165, Eindhoven University of Technology, Eindhoven.
  9. Leemans, S. J., Fahland, D. and van der Aalst, W.M.P (2013). Discovering block-structured process models from event logs containing infrequent behavior. In: International Conference on Business Process Management. Springer, pp. 66-78.
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  13. Szpyrka, M. (2008). Petri nets in design and analysis of concurrent systems. Warszawa: WNT (in Polish).
  14. The Process Mining Manifesto by the IEEE Task Force on Process Mining, In: F. Daniel, K. Barkaoui, S. Dustdar, eds., BPM 2011 Workshops, Part I, LNBIP 99, pp. 169-194. Berlin: Springer-Verlag, 2012.
  15. Van der Aalst, W.M.P. (2009). Process-Aware Information Systems: Lessons to Be Learned from Process Mining. In: Transactions on Petri Nets and Other Models of Concurrency II, Lecture Notes in Computer Science, vol. 5460, Berlin: Springer-Verlag, pp. 1-26.
  16. Van der Aalst, W.M.P. (2016). Process Mining: Data Science in Action. Berlin: Springer-Verlag.
  17. Van der Aalst, W.M.P., Weijters, A.J.M.M. and Maruster, L. (2004). Workflow Mining: Discovering Process Models from Event Logs. IEEE Transactions on Knowledge and Data Engineering, 16(9), pp.1128-1142.
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Cytowane przez
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ISSN
2545-2827
Język
eng
URI / DOI
http://dx.doi.org/10.2478/mape-2018-0049
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