Abstract
Today’s companies face great challenges when attempting to quest business markets with their demands on product quality and price. However, when a company maintains high efficiency levels on its productive processes usually it has this challenge quite simplified. The great availability of data we have currently on industry plants provides a very interesting support to face this challenge, when combined with new technologies such as process mining. This paper presents a case study where the very recent process mining techniques were applied to a very particular productive process characterized for its low frequency and heterogeneity. To do this, we made some changes to the “L * life-cycle model” methodology, for applying process mining in the identification of tasks with unsatisfactory performance levels, and analyzing the most relevant and critical aspects that influence it.
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
Similar content being viewed by others
References
Utterback, J.: Mastering the dynamics of innovation: how companies can seize opportunities in the face of technological change. University of Illinois at Urbana-Champaign’s Academy for Entrepreneurial Leadership Historical Research Reference in Entrepreneurship (1994)
van der Aalst, W.: Process Mining: Discovery, Conformance and Enhancement of Business Processes. Springer Science & Business Media, Heidelberg (2011)
van der Aalst, W.: Process mining in the large: a tutorial. In: LNBIP, vol. 172, pp. 33–76 (2014)
Han, J., Kamber, M., Pei, J.: Data Mining: Concepts and Techniques. Elsevier/Morgan Kaufmann, Waltham (2012)
Van Der Aalst, W.M.P., Ter Hofstede, A.H.M., Weske, M.: Business process management: a survey. In: International Conference on Business Process Management, pp. 1–12 (2003)
Van Dongen, B.F., Alves De Medeiros, A.K., Wen, L.: Process mining: overview and outlook of Petri net discovery algorithms. In: Jensen, K., van der Aalst, W.M.P. (eds.) LNCS, pp. 225–242. Springer, Heidelberg (2009)
Van Der Aalst, W., Adriansyah, A., van Dongen, B.: Replaying history on process models for conformance checking and performance analysis. Wiley Interdiscip. Rev. Data Min. Knowl. Discov. 2, 182–192 (2012)
Van der Aalst, W.M.P., Schonenberg, M.H., Song, M.: Time prediction based on process mining. Inf. Syst. 36, 450–475 (2011)
Van der Aalst, W.: Process mining: overview and opportunities. ACM Trans. Manag. Inf. Syst. 3, 7 (2012)
Kimball, R., Caserta, J.: The Data Warehouse ETL Toolkit (2015)
IEEE Std 1849-2016: IEEE Standard for eXtensible Event Stream (XES) for Achieving Interoperability in Event Logs and Event Streams. IEEE (2016)
Chaudhuri, S., Dayal, U.: An overview of data warehousing and OLAP technology. ACM SIGMOD Rec. 26, 65–74 (1997)
Lasi, H., Fettke, P., Kemper, H.G., et al.: Industry 4.0. Bus. Inf. Syst. Eng. 6, 239–242 (2014)
Lee, J., Bagheri, B., Kao, H.A.: A cyber-physical systems architecture for Industry 4.0-based manufacturing systems. Manuf. Lett. 3, 18–23 (2015)
Witten, I.H., Frank, E.: Data Mining: Practical Machine Learning Tools and Techniques. Morgan Kaufmann, San Francisco (2005)
van der Aalst, W., Adriansyah, A., de Medeiros, A.K.A., et al.: Process mining manifesto. In: Daniel, F., Barkaoui, K., Dustdar, S. (eds.) pp. 169–194. Springer, Heidelberg (2011)
van Dongen, B., de Medeiros A.K.A., Verbeek, H.M.W. et al.: The ProM framework: a new era in process mining tool support (2005)
Process Mining http://www.processmining.org/start, http://www.processmining.org/. Accessed 9 Sep 2017
Van der Aalst, W., Weijters, T., Maruster, L.: Workflow mining: discovering process models from event logs. IEEE Trans. Knowl. Data Eng. 16, 1128–1142 (2004)
Redlich, D., Molka, T., Gilani, W., et al.: Constructs competition miner: process control-flow discovery of BP-domain constructs. In: LNCS, pp. 134–150 (2014)
Redlich, D., Molka, T., Gilani, W., et al.: Scalable dynamic business process discovery with the constructs competition miner. In: CEUR Workshop Proceedings, pp. 91–107 (2014)
Schimm, G.: Process miner - a tool for mining process schemes from event-based data. In: LNCS, pp. 525–528 (2002)
Burattin, A., Sperduti, A.: Heuristics miner for time intervals. In: Proceedings of the 18th European Symposium on Artificial Neural Networks - Computational Intelligence and Machine Learning, ESANN 2010, pp. 41–46 (2010)
Günther, C.W., Rozinat, A.: Disco: discover your processes. In: CEUR Workshop Proceedings, pp. 40–44 (2012)
Wen, L., Wang, J., Van Der Aalst, W.M.P., et al.: A novel approach for process mining based on event types. J. Intell. Inf. Syst. 32, 163–190 (2009)
Schimm, G.: Mining exact models of concurrent workflows. Comput. Ind. 53, 265–281 (2004)
Leemans, S.J.J., Fahland, D., Van der Aalst, W.M.P.: Using life cycle information in process discovery. pp. 1–12 (2016)
Van Der Aalst, W.M.P., Van Hee, K.M., Ter Hofstede, A.H.M., et al.: Soundness of workflow nets: classification, decidability, and analysis. Form. Asp. Comput. 23, 333–363 (2011)
Acknowledgments
This work has been supported by COMPETE: POCI-01-0145-FEDER-007043 and FCT - Fundação para a Ciência e Tecnologia within the Project Scope: UID/CEC/00319/2013.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer International Publishing AG, part of Springer Nature
About this paper
Cite this paper
Ribeiro, R., Analide, C., Belo, O. (2018). Improving Productive Processes Using a Process Mining Approach. In: Rocha, Á., Adeli, H., Reis, L., Costanzo, S. (eds) Trends and Advances in Information Systems and Technologies. WorldCIST'18 2018. Advances in Intelligent Systems and Computing, vol 746. Springer, Cham. https://doi.org/10.1007/978-3-319-77712-2_69
Download citation
DOI: https://doi.org/10.1007/978-3-319-77712-2_69
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-77711-5
Online ISBN: 978-3-319-77712-2
eBook Packages: EngineeringEngineering (R0)