Publication detail

Process Mining in a Manufacturing Company for Predictions and Planning

POSPÍŠIL, M. MATES, V. HRUŠKA, T. BARTÍK, V.

Original Title

Process Mining in a Manufacturing Company for Predictions and Planning

Type

journal article - other

Language

English

Original Abstract

Simulation can be used for analysis, prediction and optimization of business processes. Nevertheless, process models often differ from reality. Data mining techniques can be used to improve these models based on observations of a process and resource behavior from detailed event logs. More accurate process models can be used not only for analysis and optimization, but also for prediction and recommendation as well. This paper analyses process models in a manufacturing company and its historical performance data. Based on the observation, a simulation model can be created and used for analysis, prediction, planning and for dynamic optimization. Focus of this paper is in different data mining problems that cannot be solved easily by well-known approaches like Regression Tree.

Keywords

business process simulation, business process intelligence, data mining, process mining, prediction, optimization, recommendation, association rules, genetic algorithms.

Authors

POSPÍŠIL, M.; MATES, V.; HRUŠKA, T.; BARTÍK, V.

RIV year

2013

Released

31. 12. 2013

ISBN

1942-2628

Periodical

International Journal on Advances in Software

Year of study

2013

Number

3

State

United States of America

Pages from

283

Pages to

297

Pages count

16

URL

BibTex

@article{BUT106393,
  author="Milan {Pospíšil} and Vojtěch {Mates} and Tomáš {Hruška} and Vladimír {Bartík}",
  title="Process Mining in a Manufacturing Company for Predictions and Planning",
  journal="International Journal on Advances in Software",
  year="2013",
  volume="2013",
  number="3",
  pages="283--297",
  issn="1942-2628",
  url="http://www.thinkmind.org/index.php?view=article&articleid=soft_v6_n34_2013_6"
}