Horn R, Zschech P (2019)
Publication Language: English
Publication Type: Conference contribution
Publication year: 2019
Publisher: universi - Universitätsverlag Siegen
City/Town: Siegen
Conference Proceedings Title: Proceedings of the 14th International Conference on Wirtschaftsinformatik
ISBN: 978-3-96182-063-4
URI: https://aisel.aisnet.org/wi2019/specialtrack01/papers/6/
DOI: 10.25819/ubsi/1016
Open Access Link: http://dx.doi.org/10.25819/ubsi/1016
The variety of data types generated in manufacturing environments leads to a situation where data-driven approaches for analytical maintenance support no longer have to be limited to the equipment level, but rather can be extended to further perspectives. To this end, this paper examines how process mining(PM) as an approach to extract knowledge about process-related relationships can be applied to support maintenance-related objectives. Our research is carried out by using exemplary data from a manufacturing company, where we successively take different data attributes from various source systems into account and apply selected PM techniques to demonstrate their applicability. As a result, we showcase how different insights can be provided, such as the analysis of a machine's internal behavior, examination of error dependencies across multiple production steps, determination of a machine’s relevance within the equipment network or the discovery of bottlenecks regarding frequencies, cycle times and costs.
APA:
Horn, R., & Zschech, P. (2019). Application of Process Mining Techniques to Support Maintenance-Related Objectives. In Ludwig T, Pipek V (Eds.), Proceedings of the 14th International Conference on Wirtschaftsinformatik. Siegen, DE: Siegen: universi - Universitätsverlag Siegen.
MLA:
Horn, Richard, and Patrick Zschech. "Application of Process Mining Techniques to Support Maintenance-Related Objectives." Proceedings of the 14th International Conference on Wirtschaftsinformatik (WI), Siegen Ed. Ludwig T, Pipek V, Siegen: universi - Universitätsverlag Siegen, 2019.
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