<abstract xmlns="http://www.w3.org/1999/xhtml">Background: Over the last 20 years, process mining has become a vibrant research area due to the advances in data management technologies and techniques and the advent of new process mining tools. Recently, the links between process mining and simulation modelling have become an area of interest.Objectives: The objective of the paper was to demonstrate and assess the role of process mining results as an input for discrete-event simulation modelling, using two different datasets, one of which is considered data-poor while the other one data-rich.Methods/Approach: Statistical calculations and process maps were prepared and presented based on the event log data from two case studies (smart mobility and higher education) using a process mining tool. Then, the implications of the results across the building blocks (entities, activities, control-flows, and resources) of simulation modelling are discussed.Results: Apart from providing a rationale and the framework for simulation that is more efficient modelling based on process mining results, the paper provides contributions in the two case studies by deliberating and identifying potential research topics that could be tackled and supported by the new combined approach.Conclusions: Event logs and process mining provide valuable information and techniques that could be a useful input for simulation modelling, especially in the first steps of building discreteevent models, but also for validation purposes.</abstract>

Background: Over the last 20 years, process mining has become a vibrant research area due to the advances in data management technologies and techniques and the advent of new process mining tools. Recently, the links between process mining and simulation modelling have become an area of interest.Objectives: The objective of the paper was to demonstrate and assess the role of process mining results as an input for discrete-event simulation modelling, using two different datasets, one of which is considered data-poor while the other one data-rich.Methods/Approach: Statistical calculations and process maps were prepared and presented based on the event log data from two case studies (smart mobility and higher education) using a process mining tool. Then, the implications of the results across the building blocks (entities, activities, control-flows, and resources) of simulation modelling are discussed.Results: Apart from providing a rationale and the framework for simulation that is more efficient modelling based on process mining results, the paper provides contributions in the two case studies by deliberating and identifying potential research topics that could be tackled and supported by the new combined approach.Conclusions: Event logs and process mining provide valuable information and techniques that could be a useful input for simulation modelling, especially in the first steps of building discreteevent models, but also for validation purposes.

Process Mining Contributions to Discrete-event Simulation Modelling

Faculty of Economics, Business and Tourism

Business Systems Research Journal

This work is licensed under the Creative Commons Attribution 4.0 International License.

{"article-title":"Process Mining Contributions to Discrete-event Simulation Modelling"}

Background: Over the last 20 years, process mining has become a vibrant research area due to the advances in data management technologies and techniques and...

Process Mining Contributions to Discrete-event Simulation Modelling

Online veröffentlicht: 29. Okt. 2020

Seitenbereich: 51 - 72

Eingereicht: 03. Feb. 2020

Akzeptiert: 24. Apr. 2020

DOI: https://doi.org/10.2478/bsrj-2020-0015

Schlüsselwörter
process mining, event log, simulation model, smart mobility

© 2020 Mario Jadrić et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Process Mining Contributions to Discrete-event Simulation Modelling

Online veröffentlicht: 29. Okt. 2020

Seitenbereich: 51 - 72

Eingereicht: 03. Feb. 2020

Akzeptiert: 24. Apr. 2020

DOI: https://doi.org/10.2478/bsrj-2020-0015

Schlüsselwörterprocess mining, event log, simulation model, smart mobility

© 2020 Mario Jadrić et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Schlüsselwörter
process mining, event log, simulation model, smart mobility