Analyzing Machine Performance Using Data Mining

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26230%2F16%3APU121664" target="_blank" >RIV/00216305:26230/16:PU121664 - isvavai.cz</a>

Výsledek na webu

<a href="http://www.fit.vutbr.cz/research/pubs/all.php?id=11230" target="_blank" >http://www.fit.vutbr.cz/research/pubs/all.php?id=11230</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/SSCI.2016.7849923" target="_blank" >10.1109/SSCI.2016.7849923</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Analyzing Machine Performance Using Data Mining

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

Analyzing Machine Performance Using Data Mining

Popis výsledku anglicky

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.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

<a href="/cs/project/LQ1602" target="_blank" >LQ1602: IT4Innovations excellence in science</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2016

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

2016 IEEE Symposium on Computational Intelligence and Data Mining

ISBN

978-1-5090-4239-5

ISSN

—

e-ISSN

—

Počet stran výsledku

7

Strana od-do

1-7

Název nakladatele

Institute of Electrical and Electronics Engineers

Místo vydání

Athens

Místo konání akce

Athens

Datum konání akce

6. 12. 2016

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000400488300099