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A Data-driven holistic approach to fault prognostics in a cyclic manufacturing process
ID
Kozjek, Dominik
(
Avtor
),
ID
Vrabič, Rok
(
Avtor
),
ID
Kralj, David
(
Avtor
),
ID
Butala, Peter
(
Avtor
)
PDF - Predstavitvena datoteka,
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(5,74 MB)
MD5: 11C76356A40624B99BD77452642DBFF8
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Izvleček
The complexity of manufacturing systems is increasing due to the increased requirements related to the variety and quality of the products, their complexity, and due to the general technological developments. In turn, the data related to the manufacturing processes is growing in size and in complexity. This presents new challenges for real-time monitoring, diagnostics, and prognostics of the processes. The challenges are addressed by new tools, methodologies, and concepts, collectively referred to as Big Data. The paper deals with the use of advanced methods for prognostics of infrequent faults on available but highly dimensional manufacturing process data. A holistic approach, which includes data generation, acquisition, storage, processing, and prognostics, is shown in a case of a plastic injection moulding process. Real industrial data acquired from five injection moulding machines and the Manufacturing Execution System within a period of six months is used. It is shown how the approach is able to tackle the high dimensionality and the large size of the data to create and evaluate prediction models for prognostics of the unplanned machine stops.
Jezik:
Angleški jezik
Ključne besede:
fault diagnostics
,
Big Data
,
plastic injection moulding
Tipologija:
1.08 - Objavljeni znanstveni prispevek na konferenci
Organizacija:
FS - Fakulteta za strojništvo
Leto izida:
2017
Št. strani:
F. 1-6
PID:
20.500.12556/RUL-101581
UDK:
658.5(045)
ISSN pri članku:
2212-8271
DOI:
10.1016/j.procir.2017.03.109
COBISS.SI-ID:
15509787
Datum objave v RUL:
18.06.2018
Število ogledov:
2477
Število prenosov:
733
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Objavi na:
Gradivo je del zbornika
Naslov:
The 50th CIRP Conference on Manufacturing Systems, May 3rd - 5th, Taichung, Taiwan
COBISS.SI-ID:
15509531
Gradivo je del revije
Naslov:
Procedia CIRP
Založnik:
Elsevier
ISSN:
2212-8271
COBISS.SI-ID:
12981019
Sekundarni jezik
Jezik:
Slovenski jezik
Ključne besede:
diagnosticiranje napak
,
velepodatki
,
brizganje plastike
Projekti
Financer:
ARRS - Agencija za raziskovalno dejavnost Republike Slovenije
Številka projekta:
P2-0270
Naslov:
Proizvodni sistemi, laserske tehnologije in spajanje materialov
Financer:
Drugi - Drug financer ali več financerjev
Program financ.:
Ministry of Higher Education, Science and Technology of the Republic of Slovenia
Številka projekta:
1000-15-510
Financer:
Drugi - Drug financer ali več financerjev
Program financ.:
Ministry of Higher Education, Science and Technology of the Republic of Slovenia
Številka projekta:
C330-16-529000
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