DocumentCode :
3009553
Title :
Process mining: discovering and improving Spaghetti and Lasagna processes
Author :
van der Aalst, Wil M. P.
Author_Institution :
Dept. of Math. & Comput. Sci., Eindhoven Univ. of Technol., Eindhoven, Netherlands
fYear :
2011
fDate :
11-15 April 2011
Abstract :
Process mining is an emerging discipline providing comprehensive sets of tools to provide fact-based insights and to support process improvements. This new discipline builds on process model-driven approaches and data mining. This invited keynote paper demonstrates that process mining can be used to discover a wide range of processes ranging from structured processes (Lasagna processes) to unstructured processes (Spaghetti processes). For Lasagna processes, the discovered process is just the starting point for a broad repertoire of analysis techniques that support process improvement. For example, process mining can be used to detect and diagnose bottlenecks and deviations in (semi-)structured processes. The analysis of Spaghetti processes is more challenging. However, the potential benefits are substantial; just by inspecting the discovered model, important insights can be obtained. Process discovery can be used to understand variability and non-conformance. This paper presents the L* life-cycle model consisting of five phases. The model describes how to apply process mining techniques.
Keywords :
data mining; food products; production engineering computing; L* life-cycle model; data mining; fact-based insights; lasagna processes; process discovery; process improvements; process mining; process model-driven approach; spaghetti processes; unstructured processes; Business; Catheters; Data mining; Data models; Predictive models; Process control; Schedules;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Intelligence and Data Mining (CIDM), 2011 IEEE Symposium on
Conference_Location :
Paris
Print_ISBN :
978-1-4244-9926-7
Type :
conf
DOI :
10.1109/CIDM.2011.6129461
Filename :
6129461
Link To Document :
بازگشت