Rövidített megjelenítés

Dr. Hajnal, Éva
Marton, Dániel
Rick, Mátyás
Orosz, Gábor Tamás
2026-08-31T07:27:18Z
2026-08-31T07:27:18Z
2019
http://hdl.handle.net/20.500.14044/40278
A pilot project on an existing production line was accomplished to help to join to industry 4.0 objectives. The essential of the project is a big data analysis, which tries to find new information in the collected complex dataset and find correlation between the product quality inspection data and the data of the production line. Our final mission is to discover the cause of size and figure deviancies of a cylindrical product. One unit of a whole complex production line was investigated with statistical and intelligent data analysis methods. All the products are labelled with a unique identifier, but these were not included in the manufacturing data. The connection of the production line and the quality inspection was established by using the timestamp values. During this research classic statistical methods and smart data analysis methods, SOM data analysis were used. In the examination we could extract some interesting information. The results in the following step are utilizable by an automatic evaluation system, after that the information could be tracked back to the production line.hu_HU
dc.formatpdfhu_HU
enhu_HU
Industry 4.0 Case Study Big Data Analysis on an Industrial Databasehu_HU
Open accesshu_HU
Óbudai Egyetemhu_HU
2019. November 14.hu_HU
Székesfehérvárhu_HU
Alba Regia Műszaki Karhu_HU
Óbudai Egyetemhu_HU
Műszaki tudományok - informatikai tudományokhu_HU
databasehu_HU
data analysishu_HU
industry 4.0hu_HU
productionhu_HU
Konferenciaközleményhu_HU
AIS 2019 14th International Symposium on Applied Informatics and Related Areas organized in the frame of Hungarian Science Festival 2019 by Óbuda University Proceedingshu_HU
local.tempfieldCollectionsKönyvrészletekhu_HU
33.hu_HU
Kiadói változathu_HU
5 p.hu_HU
AIS 2019 14th International Symposium on Applied Informatics and Related Areas organized in the frame of Hungarian Science Festival 2019 by Óbuda Universityhu_HU
978-963-449-156-9hu_HU
2019hu_HU
Óbudai Egyetemhu_HU
Óbudai Egyetemhu_HU


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