Discover simulation scenario from log

We can automatically enhance a BPMN model with simulation parameters extracted from an event log. This feature reduces the time and increases the data accuracy needed to perform simulations. For example, many large businesses have more than 100 activities per process to analyze, so manually adding the simulation parameters will take a lot of time. We can extract the simulation parameters by selecting the option “Include simulation parameters” to obtain a model ready for simulation.

Open the log we would like to perform the simulation on in the Process discoverer.

Switch from the Process map to BPMN model using the slider in the Visualization settings tab.

Note

Depending on the complexity of the model, we can play around with the abstraction slider settings. The discovered model will be based on the current abstraction slider settings.

After applying all the necessary settings and filter(s), click the Save dropdown  and click Save BPMN model.

Enter the model’s name, description, and version number and tick the Include simulation parameters box. Click OK.

By default, the BPMN model is saved in the same working directory as the log file. We can also specify a folder by clicking Browse. Select the folder and click OK.

A notification showing the file was successfully saved pops up. The BPMN model is saved in the folder specified.

We can simulate the generated BPMN model. To simulate the discovered model, return to Apromore Portal, right-click the model, and click Simulate.

Enter the name of the simulated log. Click Save.

Discover probability distributions in simulation models

When a BPMN model is saved with simulation parameters, each activity in the model is assigned a probability distribution (normal, exponential, fixed, or uniform) depending on the distribution of activity durations in the event log.

Discover attributes and their probability distributions

When a BPMN model is saved with simulation parameters, the attributes of the event log are also saved in the simulation scenario.

For each case attribute, the simulation scenario will contain its data type (String, Integer, Real, Timestamp) and its probability distribution (normal, exponential, uniform, fixed).

In the screenshot below, “Country” is a categorical case attribute, and its probability distribution is as follows: NZL – 29%, JPN – 25%, SGP – 25%, and AUS – 22%.

Conversely, in the screenshot below, “Discount” is another discovered case attribute with Numerical datatype. It follows an exponential distribution with a mean of 89215.05.

Note

When a simulation model is discovered, only case attributes are included in the simulation scenario. Event attributes are not included in a discovered simulation model but can be added manually. To learn more about adding event attributs, see Attributes.