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Title: Analiza proizvodnega procesa s podatkovnim rudarjenjem in izdelava vmesnika za napovedovanje ustreznosti motorja : magistrsko delo Authors: ID Pikec, Aljaž (Author) ID Ivanovska, Aneta (Mentor) More about this mentor... Files: http://repozitorij.ung.si/IzpisGradiva.php?id=6220   Aljaz_Pikec.pdf (934,78 KB) MD5: 894174999CA6D224B8EE48BFCF526227   Language: Slovenian Work type: Master's thesis/paper Typology: 2.09 - Master's Thesis Organization: PTF - Faculty of Engineering and Management Abstract: 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. Keywords: proizvodni proces, podatkovno rudarjenje, analiza ustreznosti procesa, vmesniki, magistrske naloge Place of publishing: Nova Gorica Place of performance: Nova Gorica Publisher: A. Pikec Year of publishing: 2021 Year of performance: 2021 Number of pages: X, 36 str. PID: 20.500.12556/RUNG-6220  COBISS.SI-ID: 58242563  UDC: 004 NUK URN: URN:SI:UNG:REP:P42MEJN8 Publication date in RUNG: 03.04.2021 Views: 2482 Downloads: 142 Metadata:     Cite this work Plain text BibTeX EndNote XML EndNote/Refer RIS ABNT ACM Ref AMA APA Chicago 17th Author-Date Harvard IEEE ISO 690 MLA Vancouver : Copy citation

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Secondary language

Language:	English
Title:	An analysis of the production process using data mining and a development of a user interface for predicting the quality of engines
Abstract:	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.
Keywords:	production process, data mining, process applicability analysis, interface

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