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MOSYURCHAK, A.; VESELKOV, V.; TURYGIN, A.; HAMMER, M.
Original Title
PROGNOSIS OF BEHAVIOUR OF MACHINE TOOL SPINDLES, THEIR DIAGNOSTICS AND MAINTENANCE
English Title
Type
Scopus Article
Original Abstract
The present article focuses on the use of neural networks to predict the behaviour of certain diagnostic parameters of spindles of machine tools. An online vibro-diagnostics is used, and from many specific measured parameters, the effective value of some variables in the time series. The results are used in the maintenance based on the technical condition, in particular, in preventive and proactive maintenance. This procedure is completely original and allows for better setting of maintenance policy, which is also beneficial for planning maintenance costs. The article also mentions the necessity to implement the steps described, also in the context of the Industry 4.0 initiative, and further, it briefly discussesprognostics, technical diagnostics, maintenance and maintenance systems. The used neural networks and the calculation procedure are also analysed. The conclusions obtained are evaluated.
English abstract
Keywords
Neural networks, prognosis of diagnostic parameters behaviour, machine tool spindle, preventive and proactive maintenance, maintenance system, Industry 4.0
Key words in English
Authors
RIV year
2018
Released
13.12.2017
Publisher
MM publishing, s.r.o. (2017)
Location
ČR
ISBN
1805-0476
Periodical
MM Science Journal
Number
5
State
Czech Republic
Pages from
2100
Pages to
2104
Pages count
4
URL
http://www.mmscience.eu/content/file/archives/MM_Science_201794.pdf
BibTex
@article{BUT142883, author="Andriy {Mosyurchak} and Vladimir {Veselkov} and Andrei {Turygin} and Miloš {Hammer}", title="PROGNOSIS OF BEHAVIOUR OF MACHINE TOOL SPINDLES, THEIR DIAGNOSTICS AND MAINTENANCE ", journal="MM Science Journal", year="2017", number="5", pages="2100--2104", doi="10.17973/MMSJ.2017\{_}12\{_}201794", issn="1803-1269", url="http://www.mmscience.eu/content/file/archives/MM_Science_201794.pdf" }