| | SLO | ENG | Cookies and privacy

Bigger font | Smaller font

Show document Help

Title:Spremljanje obrabe rezalnega orodja z uporabo umetne inteligence : diplomsko delo
Authors:ID Jukić, Andrej (Author)
ID Šafarič, Riko (Mentor) More about this mentor... New window
ID Klančnik, Simon (Mentor) More about this mentor... New window
ID Peršak, Tadej (Comentor)
Files:.pdf VS_Jukic_Andrej_2022.pdf (2,03 MB)
MD5: 9432756B903FEA51A5F055A41C96AEF1
 
.zip VS_Jukic_Andrej_2022.zip (552,87 KB)
MD5: 289A362DFE643AF492116110212ACBD7
 
Language:Slovenian
Work type:Bachelor thesis/paper
Typology:2.11 - Undergraduate Thesis
Organization:FERI - Faculty of Electrical Engineering and Computer Science
Abstract:V diplomskem delu so na začetku predstavljena obravnavana področja, kjer se teoretično spoznamo s proizvodnimi sistemi, umetno inteligenco, klasifikacijo, učnimi algoritmi, merami za ocenjevanje in z obdelovalnim postopkom rezkanja. Bistvenega pomena je področje klasifikacije in mer za ocenjevanje, zaradi tega sta ti dve področji bolj podrobno opisani. Po teoretičnem izhodišču sledi poglavje praktične izvedbe, pri katerem smo predstavljeno teorijo uresničili. V tem sklopu so opisani trije poizkusi, kjer smo preverjali zastavljene teze s pomočjo gravirnega stroja Lakos 150 in računalniškega programa Matlab, ki je podpiral strojno učenje (klasifikacijo). S poizkušanjem smo tako potrdili vse teze, dosegli večino zastavljenih ciljev, pri čemer nismo dosegli glavnega cilja dela (uspešna klasifikacija glede na status orodja) zaradi strokovne zahtevnosti področja.
Keywords:umetna inteligenca, strojno učenje, klasifikacija, rezkanje
Place of publishing:Maribor
Place of performance:Maribor
Publisher:[I. Jovanovič]
Year of publishing:2022
Number of pages:1 spletni vir (1 datoteka PDF (XV, 50 f.))
PID:20.500.12556/DKUM-82958 New window
UDC:004.85:621.937(043.2)
COBISS.SI-ID:139369475 New window
Publication date in DKUM:25.10.2022
Views:928
Downloads:74
Metadata:XML DC-XML DC-RDF
Categories:KTFMB - FERI
:
Copy citation
  
Average score:(0 votes)
Your score:Voting is allowed only for logged in users.
Share:Bookmark and Share



Hover the mouse pointer over a document title to show the abstract or click on the title to get all document metadata.

Licences

License:CC BY-NC-ND 4.0, Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International
Link:http://creativecommons.org/licenses/by-nc-nd/4.0/
Description:The most restrictive Creative Commons license. This only allows people to download and share the work for no commercial gain and for no other purposes.
Licensing start date:12.09.2022

Secondary language

Language:English
Title:Tool condition monitoring using artificial intelligence
Abstract:In the diploma work, the discussed areas are presented at the beginning, where we get to know theoretically about production systems, artificial intelligence, classification, learning algorithms, evaluation measures and the machining process of milling. The area of classification and evaluation measures is of vital importance, so these two areas are described in more detail. The theoretical starting point is followed by the chapter on practical implementation, in which we put the presented theory into practice. In this section, three experiments are described, where we checked the proposed theses with the help of the Lakos 150 engraving machine and the computer program Matlab, which supported machine learning (classification). Through experimentation, we confirmed all theses, achieved most of the set goals, but did not achieve the main goal of the task (successful classification according to the status of the tool), due to the professional complexity of the field.
Keywords:artificial inteligence, machine learning, classification, milling


Comments

Leave comment

You must log in to leave a comment.

Comments (0)
0 - 0 / 0
 
There are no comments!

Back
Logos of partners University of Maribor University of Ljubljana University of Primorska University of Nova Gorica