Petri nets simulation for operational analytics based on process data: An overview

Natanael Yabes Wirawan; Riska Asriana Sutrisnowati; Sunghyun Sim; Nur Ichsan Utama; Nur Ahmad Wahid; Taufik Nur Adi; Yulim Choi; Imam Mustafa Kamal; Iq Reviessay Pulshashi; Hyerim Bae

doi:10.24507/icicelb.09.10.1033

Petri nets simulation for operational analytics based on process data: An overview

Natanael Yabes Wirawan
, Riska Asriana Sutrisnowati
, Sunghyun Sim
, Nur Ichsan Utama
, Nur Ahmad Wahid
, Taufik Nur Adi
, Yulim Choi
, Imam Mustafa Kamal
, Iq Reviessay Pulshashi
, Hyerim Bae^*

^*Corresponding author for this work

Big Data Department
Pusan National University
Dong-Nam Grand ICT R&D Center
Industrial Engineering Department

Research output: Contribution to journal › Article › peer-review

2 Citations (Scopus)

Abstract

This paper highlights an initial study on a framework for developing a semiautomatic Petri nets simulation model for operational analytics. Starting from pro-cess/event data gathering from companies’ software information systems, we calculate the simulation parameters (e.g., distribution parameters, and simulation logic). After-wards, we build the model by integrating the simulation parameters and process execution logics. Also, we incorporate into the framework several algorithms that are designed to handle large-sized data.

Original language	English
Pages (from-to)	1033-1040
Number of pages	8
Journal	ICIC Express Letters, Part B: Applications
Volume	9
Issue number	10
DOIs	https://doi.org/10.24507/icicelb.09.10.1033
Publication status	Published - 2018
Externally published	Yes

Keywords

Distributed processing
Event logs
Petri nets
Process mining
Simulation

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10.24507/icicelb.09.10.1033

Cite this

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title = "Petri nets simulation for operational analytics based on process data: An overview",

abstract = "This paper highlights an initial study on a framework for developing a semiautomatic Petri nets simulation model for operational analytics. Starting from pro-cess/event data gathering from companies{\textquoteright} software information systems, we calculate the simulation parameters (e.g., distribution parameters, and simulation logic). After-wards, we build the model by integrating the simulation parameters and process execution logics. Also, we incorporate into the framework several algorithms that are designed to handle large-sized data.",

keywords = "Distributed processing, Event logs, Petri nets, Process mining, Simulation",

author = "Wirawan, \{Natanael Yabes\} and Sutrisnowati, \{Riska Asriana\} and Sunghyun Sim and Utama, \{Nur Ichsan\} and Wahid, \{Nur Ahmad\} and Adi, \{Taufik Nur\} and Yulim Choi and Kamal, \{Imam Mustafa\} and Pulshashi, \{Iq Reviessay\} and Hyerim Bae",

note = "Publisher Copyright: {\textcopyright} 2018 ICIC International.",

year = "2018",

doi = "10.24507/icicelb.09.10.1033",

language = "English",

volume = "9",

pages = "1033--1040",

journal = "ICIC Express Letters, Part B: Applications",

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TY - JOUR

T1 - Petri nets simulation for operational analytics based on process data

T2 - An overview

AU - Wirawan, Natanael Yabes

AU - Sutrisnowati, Riska Asriana

AU - Sim, Sunghyun

AU - Utama, Nur Ichsan

AU - Wahid, Nur Ahmad

AU - Adi, Taufik Nur

AU - Choi, Yulim

AU - Kamal, Imam Mustafa

AU - Pulshashi, Iq Reviessay

AU - Bae, Hyerim

PY - 2018

Y1 - 2018

N2 - This paper highlights an initial study on a framework for developing a semiautomatic Petri nets simulation model for operational analytics. Starting from pro-cess/event data gathering from companies’ software information systems, we calculate the simulation parameters (e.g., distribution parameters, and simulation logic). After-wards, we build the model by integrating the simulation parameters and process execution logics. Also, we incorporate into the framework several algorithms that are designed to handle large-sized data.

AB - This paper highlights an initial study on a framework for developing a semiautomatic Petri nets simulation model for operational analytics. Starting from pro-cess/event data gathering from companies’ software information systems, we calculate the simulation parameters (e.g., distribution parameters, and simulation logic). After-wards, we build the model by integrating the simulation parameters and process execution logics. Also, we incorporate into the framework several algorithms that are designed to handle large-sized data.

KW - Distributed processing

KW - Event logs

KW - Petri nets

KW - Process mining

KW - Simulation

UR - https://www.scopus.com/pages/publications/85052991445

U2 - 10.24507/icicelb.09.10.1033

DO - 10.24507/icicelb.09.10.1033

M3 - Article

AN - SCOPUS:85052991445

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VL - 9

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EP - 1040

JO - ICIC Express Letters, Part B: Applications

JF - ICIC Express Letters, Part B: Applications

IS - 10

ER -

Petri nets simulation for operational analytics based on process data: An overview

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Keywords

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