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The Performance Spectrum Miner (PSM) is a visual analytics tool for process performance analysis. It takes an event log in a CSV or XES format, visualizes the flow of all cases over time, and gives detailed insights into performance characteristics.
The PSM visualization
The PSM project provides two implementations of the Performance Spectrum Miner as a plugin to the Process Mining Framework ProM and as a stand-alone application.
The PSM project is the result of the joint research project on Process Mining in Logistics between Eindhoven University of Technology and Vanderlande Industries, and developed by Vadim Denisov, Elena Belkina, and Dirk Fahland.
Unbiased, Fine-Grained Description of Processes Performance from Event Data (BPM2018)
BPIC'2018: Mining Concept Drift in Performance Spectra of Processes (BPIC2018)
The PSM is implemented and tested with Java 8 and is not binary compatible with other Java versions.
java -version
in the command line. You should get a response like this:java version "1.8.0_171"
Java(TM) SE Runtime Environment (build 1.8.0_171-b11)
Java HotSpot(TM) 64-Bit Server VM (build 25.171-b11, mixed mode)
*If you do not want to change your current Java installation to Java 8, you can download Java 8 and explicitly call it while starting the PSM or ProM (in 'ProM.bat'), for example://
"C:\Program Files\Java\jre1.8.0_171\bin\java.exe" -jar perf_spec-assembly-1.0.2.jar
[Not available yet...]()
PackageManager.bat
)ProM.bat
in any text editor and change parameter –Xmx
from 4
to a value equal to your laptop's RAM size minus 2ProM.bat
to run the PSMPackageManager.bat
)java -jar perf_spec-assembly-1.1.1.jar
to run the PSMAnalyzing the Performance Spectrum of a process with the PSM has three steps:
Additionally the PSM allows encoding and exporting performance spectrum-based features into a training and test sets.
session.psm
). You can load this transformed data also later into ProM by loading the session.psm
meta-data file.session.psm
). You can load this transformed data also later via the Open... button.Often event data are available in the CSV format as a database or a distributed file storage dump, stored in one or many CSV files. Converting such dumps to XES format can be difficult for large event logs. The PSM supports a direct import of one or many CSV files. To prepare CSV file(s) for import, put the file(s) into a directory and provide a description as a text ini file with extension .csvdir
. This file must include the following fields (see example):
Field | Sample value | Comment |
---|---|---|
dateFormat |
dd-MM-yyyy HH:mm:ss.SSS |
Datetime format in Java DateTimeFormatter format |
zoneId |
Europe/Amsterdam |
Time zone ID in Java ZoneId format |
startTime |
01-09-2018 00:00:00.000 |
Since then the performance spectrum should be computed, in the format described above |
endTime |
08-09-2018 00:00:00.000 |
Until then the performance spectrum should be computed, in the format described above |
caseIdColumn |
CaseID |
Column name for case ID |
activityColumn |
Activity |
Column name for activity |
timestampColumn |
Timestamp |
Column name for timestamp |
Import your .csvdir
file and use it in the PSM plugin, exactly as XES files.
Import your .csvdir
file and use it exactly as XES files.
Sometimes event data are availabe not as an event log but as segments. Find here how to import such data into the PSM.
The main window of the Performance Spectrum Miner is divided into
In the visualization panel, each horizontal segment shows how cases move over time (x-axis) from one activity to the next activity (y-axis).
By default the visualization shows Lines. In the figure below, each colored line describes one case moving from Send Fine to Insert Fine Notification. The x-coordinates of the start and end point of each line visualize the moments in time when Send Fine and Insert Fine Notification occurred, respectively. The color of the line depends on the classification that was chosen in the transformation step, which can be retrieved via the Legend button in the control and filtering panel.
The performance spectrum shows among other things:
While the Lines show the speed of cases, the amount of cases over time can be visualized by checking Bars in the control and filtering panel.
The stacked bars provide aggreate information about how many cases started, ended, or were pending in particular time-window between the two activities of the segment. The parameters of this aggregation are chosen in the transformation step, see the User Manual for details. In the example above, the stacked bars show that the process experienced a very high amount of cases going from Send Fine to Insert Fine Notification in particular period (the exact time will be shown on the bottom left when hovering the mouse over the respective part of the visualization). The coloring indicates that in this period, the cases were processed much slower than in other period. The number 2988 in the label of the segment tells that there were at a maximum 2988 cases transitioning together through this part of the process.
The Performance Spectrum can be explored in various ways.
.*Send Fine.*
will include all segments involving Send FineSend Fine:.*
will include all segments starting with Send Fine and leading to some other activityMore detailed information can be found in
The Performance Spectrum Miner project is the result of the joint research project on Process Mining in Logistics between Eindhoven University of Technology and Vanderlande Industries. It was developed by
The project makes the Performance Spectrum Miner available under the GNU LGPL v3.0 (see file LICENSE)
The objective of the PSM project is to
Do you have...
More information about the Process Mining in Logistics project focusing on process performance analysis can be found at the project website.
Please see the contribution guidelines for this project