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.
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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.
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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
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