20.500.12556/RUL-108454 Data mining for fault diagnostics a case for plastic injection molding 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. fault diagnostics plastic injection molding data analytics data mining industrial data diagnosticiranje napak injekcijsko brizganje plastike analitika podatkov podatkovno rudarjenje industrijski podatki true false true Angleški jezik Slovenski jezik Članek v reviji 2019-07-03 08:12:09 2019-07-03 08:12:10 2022-08-20 03:46:32 0000-00-00 00:00:00 2019 0 0 f. 809-814 Vol. 81 2019 0000-00-00 Zaloznikova Objavljeno NiDoloceno 0000-00-00 0000-00-00 0000-00-00 658.5.012.7:681.5(045) 2212-8271 10.1016/j.procir.2019.03.204 16687643 16674843 RAZ_Kozjek_Dominik_i2019.pdf RAZ_Kozjek_Dominik_i2019.pdf 1 EC35E5350C41A392F251BB9C5E90E87F 9a853e40d3732b5763274d5b4293b7c4570253a9ca0822dd7baa7055f10d5aef ab95ff7f-a1b6-11eb-a523-00155dcfd717 https://repozitorij.uni-lj.si/Dokument.php?lang=slv&id=119552 https://www.sciencedirect.com/science/article/pii/S2212827119305098 1 https://repozitorij.uni-lj.si/Dokument.php?lang=slv&id=119409 Fakulteta za strojništvo 0 0 0