Details

Analiza vpeljave proizvodnega informacijskega sistema Kiner v podjetju Domel : zaključna strokovna naloga visoke poslovne šole
ID Jelovčan, Jana (Author), ID Trkman, Peter (Mentor) More about this mentor... This link opens in a new window

URLURL - Presentation file, Visit http://www.cek.ef.uni-lj.si/vps_diplome/jelovcan1099.pdf This link opens in a new window

Language:Slovenian
Keywords:informatika, informacijski sistemi, Kiner, produkcija, kontrola, stroški, produktivnost, primeri
Work type:Final paper
Typology:2.11 - Undergraduate Thesis
Organization:EF - School of Economics and Business
Place of publishing:Ljubljana
Publisher:[J. Jelovčan]
Year:2020
Number of pages:II, 27 str.
PID:20.500.12556/RUL-122789 This link opens in a new window
UDC:659.2
COBISS.SI-ID:25526758 This link opens in a new window
Publication date in RUL:15.12.2020
Views:2070
Downloads:69
Metadata:XML DC-XML DC-RDF
:
JELOVČAN, Jana, 2020, Analiza vpeljave proizvodnega informacijskega sistema Kiner v podjetju Domel : zaključna strokovna naloga visoke poslovne šole [online]. Bachelor’s thesis. Ljubljana : J. Jelovčan. [Accessed 25 March 2025]. Retrieved from: http://www.cek.ef.uni-lj.si/vps_diplome/jelovcan1099.pdf
Copy citation
Share:Bookmark and Share

Secondary language

Language:English
Title:The analysis of implementation of manufacturing execution system Kiner - case of Domel
Keywords:informatics, information systems, production, control, costs, productivity, cases

Similar documents

Similar works from RUL:
  1. DEEP LEARNING METHODS FOR BIOMETRIC RECOGNITION BASED ON EYE INFORMATION
  2. Part of speech tagging of slovene language using deep neural networks
  3. Automatic classification of buildings with deep learning
  4. Object detection and classification in aquatic environment using convolutional neural networks
  5. Superposition and compression of deep neutral networks
Similar works from other Slovenian collections:
  1. Time series classification based on convolutional neural networks
  2. The preparation of photos' dataset and its classification using deep neural networks
  3. Prediction of geospatial raster data using convolutional neural networks
  4. Development of an advanced system for lane detection on GPU platforms
  5. Comparison of different deep neural network learning algorithms in autonomous driving

Back