TY - GEN
T1 - Visualizing Token Flows Using Interactive Performance Spectra
AU - van der Aalst, Wil M.P.
AU - Tacke Genannt Unterberg, Daniel
AU - Denisov, Vadim
AU - Fahland, Dirk
PY - 2020
Y1 - 2020
N2 - Process mining techniques can be used to discover process models from event data and project performance and conformance related diagnostics on such models. For example, it is possible to automatically discover Petri nets showing the bottlenecks in production, administration, transport, and financial processes. Also basic statistics (frequencies, average delays, standard deviations, etc.) can be projected on the places and transitions of such nets to reveal performance and compliance problems. However, real-life phenomena such as overtaking, batching, queueing, concept drift, and partial blocking of multiple cases remain invisible when considering basic statistics. This paper presents an approach combining Petri-net-based discovery techniques and so-called performance spectra based on token flows. Token production and consumption are visualized such that the true dynamics of the process are revealed. Our ProM implementation supports a range of visual-analytics features allowing the user to interact with the underlying event data and Petri net. Event data related to the handling of orders are used to demonstrate the functionality of our tool.
AB - Process mining techniques can be used to discover process models from event data and project performance and conformance related diagnostics on such models. For example, it is possible to automatically discover Petri nets showing the bottlenecks in production, administration, transport, and financial processes. Also basic statistics (frequencies, average delays, standard deviations, etc.) can be projected on the places and transitions of such nets to reveal performance and compliance problems. However, real-life phenomena such as overtaking, batching, queueing, concept drift, and partial blocking of multiple cases remain invisible when considering basic statistics. This paper presents an approach combining Petri-net-based discovery techniques and so-called performance spectra based on token flows. Token production and consumption are visualized such that the true dynamics of the process are revealed. Our ProM implementation supports a range of visual-analytics features allowing the user to interact with the underlying event data and Petri net. Event data related to the handling of orders are used to demonstrate the functionality of our tool.
KW - Performance spectrum
KW - Petri nets
KW - Process mining
KW - Visual analytics
UR - http://www.scopus.com/inward/record.url?scp=85088268262&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-51831-8_18
DO - 10.1007/978-3-030-51831-8_18
M3 - Conference contribution
AN - SCOPUS:85088268262
SN - 9783030518301
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 369
EP - 380
BT - Application and Theory of Petri Nets and Concurrency - 41st International Conference, PETRI NETS 2020, Proceedings
A2 - Janicki, Ryszard
A2 - Sidorova, Natalia
A2 - Chatain, Thomas
PB - Springer
T2 - 41st International Conference on Application and Theory of Petri Nets and Concurrency, PETRI NETS 2020
Y2 - 24 June 2020 through 25 June 2020
ER -