Publication Details
Process Mining in a Manufacturing Company for Predictions and Planning
Mates Vojtěch, Ing., Ph.D.
Hruška Tomáš, prof. Ing., CSc. (DIFS)
Bartík Vladimír, Ing., Ph.D. (DIFS)
business process simulation, business process intelligence, data mining, process
mining, prediction, optimization, recommendation, association rules, genetic
algorithms.
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.
@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"
}