20.500.12556/RUNG-6220
Analiza proizvodnega procesa s podatkovnim rudarjenjem in izdelava vmesnika za napovedovanje ustreznosti motorja
magistrsko delo
An analysis of the production process using data mining and a development of a user interface for predicting the quality of engines
V današnjem času se v industriji pri tehnoloških procesih generira ogromna količina podatkov, ki so neuporabni, če se jih ne analizira in pridobi znanje iz teh podatkov na pravi način in v primernem času. Zato v teh primerih tradicionalne statistične metode včasih niso dovolj informativne, ker je treba vnaprej definirati hipotezo, ki jo kasneje potrdimo ali zavržemo. S podatkovnim rudarjenjem to ni potrebno, saj dobimo modele iz podatkov na avtomatičen način, ki lahko predstavlja novo znanje in iz tega lahko definiramo neko hipotezo. Industrijski in avtomobilski trg rasteta iz dneva v dan in da bi sledili razvoju ter analizi nastalih podatkov, moramo izbrati potrebne ukrepe, ki bi nam olajšali samo analiziranje prejetih informacij in ustrezno reagirali ob možnih odstopanjih, da bi s tem zmanjšali potencialne nastale stroške kot samo izvedbo procesa. Na eni izmed linij za montažo enega primera motorja v podjetju MAHLE Electric Drives Slovenija, d. o. o., smo iz operacij procesa vtiska ležaja v pokrov, zakovanja ležaja, natiska ležaja na rotor in vtiska rotorja videli, da kljub temu, da so operacije pri meritvah sile in poti še vedno v definiranih tolerancah, imamo precej odstopanj od referenčne vrednosti in s tem je lahko povezan tudi rezultat meritve trenja motorja. S pomočjo podatkovnega rudarjenja bi radi ugotovili, kaj je razlog za ta odstopanja, da bi jih lahko vnaprej napovedali in sprejeli ustrezne ukrepe. Za lažje razumevanje omenjene tematike in kot pomoč tehnologom na liniji pri pregledovanju potencialnih odstopanj in napovedovanju ustreznosti motorja smo pripravili tudi programski vmesnik.
Nowadays, technological industrial processes generate an enormous amount of data,
which can become useless if they are not analysed and relevant information is not
extracted appropriately and within a reasonable period of time. In many cases,
traditional statistical methods do not provide enough information, because hypotheses
need to be defined in advance, and later confirmed or refuted. However, this is not
necessary when the data mining method is applied, because data are acquired from
models automatically. The data may convey new information, which can be used to
set a hypothesis. The industrial car market is growing day by day; in order to follow
its development and data analysis, several methods must be selected to facilitate data
analysis and help us react appropriately in the event of probable deviations in order to
reduce potential costs and shorten the process itself. At the MAHLE Electric Drives
Slovenija company, we worked on one of the assembly lines for engine installation,
where bearings get embedded in the lid, forged and embedded onto the rotor, which
also gets embedded. Even though these operations are within the defined tolerances
when force and stroke are measured, several deviations from the referential value are
identified, which may influence the result of engine friction measurement. Using the
data mining method, we want to determine the reason behind these deviations in order
to be able to foresee them and adopt appropriate measures. Seeking to facilitate the
understanding of the discussed topic as well as to help engineers on the line review
potential deviations and predict the quality of the engine, we also created a software
interface. Findings obtained with the help of data mining techniques will be very useful
in planning new lines and optimizing production processes before the regular start of
production, according to the data obtained, we can use the software interface to see the
effects on the final measurements and we can predict the suitability of the engine itself.
proizvodni proces
podatkovno rudarjenje
analiza ustreznosti procesa
vmesniki
magistrske naloge
production process
data mining
process applicability analysis
interface
true
true
false
A. Pikec
Slovenski jezik
Angleški jezik
Magistrsko delo/naloga
2021-01-26 03:37:02
2021-04-03 09:00:57
2023-06-13 14:25:32
0000-00-00 00:00:00
2021
0
Nova Gorica
2021
Nova Gorica
X, 36 str.
0000-00-00
NiDoloceno
NiDoloceno
NiDoloceno
0000-00-00
0000-00-00
0000-00-00
58242563
004
URN:SI:UNG:REP:P42MEJN8
http://repozitorij.ung.si/IzpisGradiva.php?id=6220
1
https://repozitorij.ung.si/Dokument.php?lang=slv&id=21913
Aljaz_Pikec.pdf
Aljaz_Pikec.pdf
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https://repozitorij.ung.si/Dokument.php?lang=slv&id=21708
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