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Data mining for fault diagnostics : a case for plastic injection molding
ID Kozjek, Dominik (Avtor), ID Vrabič, Rok (Avtor), ID Kralj, David (Avtor), ID Butala, Peter (Avtor), ID Lavrač, Nada (Avtor)

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Izvleček
In manufacturing processes the automated identification of faulty operating conditions that might lead to insufficient product quality and reduced availability of the equipment is an important and challenging task. This paper proposes a data mining approach to the identification of complex faults, i.e. unplanned machine stops in plastic injection molding. Several data mining methods are considered, with a focus on the abilities to reveal patterns of faulty operating conditions and on the interpretation of the induced models with the objective to find the data mining method that best corresponds to the nature of the plastic-injection-molding process and the related data. Well-known data mining methods, i.e. J48, random forests, JRip rules, naïve Bayes, and k-nearest neighbors are applied to real industrial data. The results show that tested data mining methods can be effectively used to reveal patterns related to faulty operating conditions. The interpretation capacity of the tested methods, their ability to describe the operating conditions, and to reveal patterns related to faulty operating conditions, are demonstrated and discussed.

Jezik:Angleški jezik
Ključne besede:fault diagnostics, plastic injection molding, data analytics, data mining, industrial data
Vrsta gradiva:Članek v reviji
Tipologija:1.08 - Objavljeni znanstveni prispevek na konferenci
Organizacija:FS - Fakulteta za strojništvo
Status publikacije:Objavljeno
Različica publikacije:Objavljena publikacija
Leto izida:2019
Št. strani:f. 809-814
Številčenje:Vol. 81
PID:20.500.12556/RUL-108454 Povezava se odpre v novem oknu
UDK:658.5.012.7:681.5(045)
ISSN pri članku:2212-8271
DOI:10.1016/j.procir.2019.03.204 Povezava se odpre v novem oknu
COBISS.SI-ID:16687643 Povezava se odpre v novem oknu
Datum objave v RUL:03.07.2019
Število ogledov:1704
Število prenosov:732
Metapodatki:XML RDF-CHPDL DC-XML DC-RDF
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Gradivo je del zbornika

Naslov:52nd CIRP Conference on Manufacturing Systems (CMS), Ljubljana, Slovenia, June 12-14, 2019
COBISS.SI-ID:16674843 Povezava se odpre v novem oknu

Gradivo je del revije

Naslov:Procedia CIRP
Založnik:Elsevier
ISSN:2212-8271
COBISS.SI-ID:12981019 Povezava se odpre v novem oknu

Sekundarni jezik

Jezik:Slovenski jezik
Ključne besede:diagnosticiranje napak, injekcijsko brizganje plastike, analitika podatkov, podatkovno rudarjenje, industrijski podatki

Projekti

Financer:ARRS - Agencija za raziskovalno dejavnost Republike Slovenije
Številka projekta:P2-0270
Naslov:Proizvodni sistemi, laserske tehnologije in spajanje materialov

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