Prof. Ing. Tomáš Hruška, CSc.

POSPÍŠIL Milan, BARTÍK Vladimír and HRUŠKA Tomáš. Analyzing Machine Performance Using Data Mining. In: 2016 IEEE Symposium on Computational Intelligence and Data Mining. Athens: Institute of Electrical and Electronics Engineers, 2016, pp. 1-7. ISBN 978-1-5090-4239-5.
Publication language:english
Original title:Analyzing Machine Performance Using Data Mining
Title (cs):Analýza výkonnosti stroje s využítím získávání znalostí
Proceedings:2016 IEEE Symposium on Computational Intelligence and Data Mining
Conference:IEEE Symposium on Computational Intelligence and Data Mining 2016
Place:Athens, GR
Publisher:Institute of Electrical and Electronics Engineers
Process mining, data mining, manufacturing, performance analysis, simulation, prediction, monitoring, scheduling.
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.
   author = {Milan Posp{\'{i}}{\v{s}}il and Vladim{\'{i}}r
	Bart{\'{i}}k and Tom{\'{a}}{\v{s}} Hru{\v{s}}ka},
   title = {Analyzing Machine Performance Using Data Mining},
   pages = {1--7},
   booktitle = {2016 IEEE Symposium on Computational Intelligence and Data
   year = 2016,
   location = {Athens, GR},
   publisher = {Institute of Electrical and Electronics Engineers},
   ISBN = {978-1-5090-4239-5},
   doi = {10.1109/SSCI.2016.7849923},
   language = {english},
   url = {}

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