Detail publikace

Analyzing Machine Performance Using Data Mining

POSPÍŠIL, M. BARTÍK, V. HRUŠKA, T.

Originální název

Analyzing Machine Performance Using Data Mining

Typ

článek ve sborníku ve WoS nebo Scopus

Jazyk

angličtina

Originální abstrakt

This paper focuses on analysis of machine performance in a manufacturing company. Machine behavior can be complex, because it usually consists of many tasks. Performance of these tasks depends on product attributes, worker's speed, and therefore, analysis is not simple. Performance analysis results can be used for different purposes. Prediction and description are typical products of data mining. Prediction should be used for online monitoring of the manufactory process and as an input for a scheduler. Description can serve as information for managers to know which attributes of products cause problems more frequently. However manufacturing processes are complex, every process is quite unique. Our long term goal is to generalize the most common patterns to build general analyzer. This task is not simple because the lack of real word data and information. Therefore this work may contribute to the other researchers in their understanding of real world manufacturing problems.

Klíčová slova

Process mining, data mining, manufacturing, performance analysis, simulation, prediction, monitoring, scheduling.

Autoři

POSPÍŠIL, M.; BARTÍK, V.; HRUŠKA, T.

Vydáno

13. 7. 2016

Nakladatel

Institute of Electrical and Electronics Engineers

Místo

Athens

ISBN

978-1-5090-4239-5

Kniha

2016 IEEE Symposium on Computational Intelligence and Data Mining

Strany od

1

Strany do

7

Strany počet

7

URL

https://www.fit.vut.cz/research/publication/11230/

BibTex

@inproceedings{BUT131008,
  author="Milan {Pospíšil} and Vladimír {Bartík} and Tomáš {Hruška}",
  title="Analyzing Machine Performance Using Data Mining",
  booktitle="2016 IEEE Symposium on Computational Intelligence and Data Mining",
  year="2016",
  pages="1--7",
  publisher="Institute of Electrical and Electronics Engineers",
  address="Athens",
  doi="10.1109/SSCI.2016.7849923",
  isbn="978-1-5090-4239-5",
  url="https://www.fit.vut.cz/research/publication/11230/"
}