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Title:PREGLED IN UPORABA POSTOPKOV OPTIMIRANJA OBSTOJNOSTI PRI STRUŽENJU
Authors:ID Zupanič, Boštjan (Author)
ID Čuš, Franci (Mentor) More about this mentor... New window
ID Župerl, Uroš (Comentor)
Files:.pdf UNI_Zupanic_Bostjan_2012.pdf (18,33 MB)
MD5: 1ACF708E4DC21F0853D195D5D7ADF26A
PID: 20.500.12556/dkum/8d1efab3-0a38-4963-bb34-3bd7c139f284
 
Language:Slovenian
Work type:Undergraduate thesis
Typology:2.11 - Undergraduate Thesis
Organization:FS - Faculty of Mechanical Engineering
Abstract:V diplomski nalogi so predstavljene veličine, ki vplivajo na optimiranje obstojnosti pri struženju. Opisane in prikazane so metode, s katerimi pridemo do realnih rezultatov ob uporabi določene baze podatkov in upoštevanjem medsebojnega vpliva obdelovanec, orodje, vpenjalo, stroj in hladilno mazalno sredstvo. Za prikaz optimiranja so uporabljeni analitični modeli ter prikaz modelov umetne inteligence (nevronske mreže, genetski algoritem). Podani so principi zajemanja signalov pri odrezavanju ter vključitev teh signalov v sistem adaptivnega optimiranja krmilja ter procesa.
Keywords:odrezavanje, optimiranje, optimiranje odezovalnih procesov, umetna inteligenca
Place of publishing:Maribor
Publisher:[B. Zupanič]
Year of publishing:2012
PID:20.500.12556/DKUM-22722 New window
UDC:621.941-048.34(043.2)
COBISS.SI-ID:16850454 New window
NUK URN:URN:SI:UM:DK:HTYFE9GA
Publication date in DKUM:29.06.2012
Views:1838
Downloads:161
Metadata:XML DC-XML DC-RDF
Categories:KTFMB - FS
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Secondary language

Language:English
Title:REVIEW AND OPTIMIZATION OF TOOL WEAR IN TURNING OPERATIONS
Abstract:In this work I have considered all parameters that influence the optimization of tool wear in turning. I have presented the methods that help us come to realistic results when considering specific databases and the correlation of the cutting tool, work piece, clamping, machine and cooling fluid. An analytic and artificial intelligence models (neutral network and genetic algorithm) have been used for the optimization modeling. There is also an overview of data acquisition and the use of this data in an adaptive control optimization model.
Keywords:cutting, optimization, cutting process optimization, artificial intelligence, adaptive control optimization


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