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Projects / Programmes source: ARIS

Raziskava kaotičnih lastnosti brusilnega procesa (Slovene)

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Research activity

Code Science Field Subfield
2.21.00  Engineering sciences and technologies  Technology driven physics   

Code Science Field
T121  Technological sciences  Signal processing 
T210  Technological sciences  Mechanical engineering, hydraulics, vacuum technology, vibration and acoustic engineering 
Keywords
grinding, chaos, neural networks
Evaluation (rules)
source: COBISS
Evaluation of bibliographic research performance indicators according to ARIS methodology
Citations Citations for bibliographic records in COBIB.SI that are linked to records in citation databases
source: WoS source: Scopus source: COBISS
Researchers (4)
no. Code Name and surname Research area Role Period No. of publications
1.  00800  PhD Igor Grabec  Computer science and informatics  Researcher  1998 - 2001  696 
2.  18081  PhD Janez Gradišek  Mechanical design  Researcher  1998 - 2001  92 
3.  09002  Peter Mužič  Manufacturing technologies and systems  Researcher  1999 - 2001  95 
4.  10425  PhD Egon Susič  Computer science and informatics  Head  1998 - 2001  44 
Organisations (1)
no. Code Research organisation City Registration number No. of publications
1.  0782  University of Ljubljana, Faculty of Mechanical Engineering  Ljubljana  1627031  29,223 
Abstract
The development of modern grinding systems requires the increased use of both adaptive control and machine intelligence technologies. Due to the chaotic properties of fundamental processes, that take place during the grinding process, the aforementioned requirement has not been satisfied yet. Recent development of the methods of chaotic dynamics analysis and neural networks are very promising as new approaches to the characterization of manufacturing processes. The aim of this project is to apply these novel methods to the problem of grinding characterization.
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