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Inventory classification using multi-criteria ABC analysis, neural networks and cluster analysis

Tomislav Šarić orcid id orcid.org/0000-0002-6339-7936 ; J. J. Strossmayer University of Osijek, Mechanical Engineering Faculty in Slavonski Brod, Trg Ivane Brlić-Mažuranić 2, 35 000 Slavonski Brod, Croatia
Katica Šimunović ; J. J. Strossmayer University of Osijek, Mechanical Engineering Faculty in Slavonski Brod, Trg Ivane Brlić-Mažuranić 2, 35 000 Slavonski Brod, Croatia
Danijela Pezer ; J. J. Strossmayer University of Osijek, Mechanical Engineering Faculty in Slavonski Brod, Trg Ivane Brlić-Mažuranić 2, 35 000 Slavonski Brod, Croatia
Goran Šimunović orcid id orcid.org/0000-0002-7159-2627 ; J. J. Strossmayer University of Osijek, Mechanical Engineering Faculty in Slavonski Brod, Trg Ivane Brlić-Mažuranić 2, 35 000 Slavonski Brod, Croatia


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Puni tekst: engleski pdf 2.742 Kb

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Sažetak

The work presents a research on inventory ABC classification using various multi-criteria methods (AHP method and cluster analysis) and neural networks. For the real inventory sample data and previously conducted traditional ABC analysis the applications of the mentioned methods in inventory classification have also been investigated. The applied methods’ obtained results have been used to evaluate their usage possibilities in real manufacturing environment. The investigations carried out in the present work create real conditions for a better inventory control and implementation of the results in the ERP system inventory module.

Ključne riječi

ABC analysis; AHP methodology; cluster analysis; inventory classification; neural networks

Hrčak ID:

129102

URI

https://hrcak.srce.hr/129102

Datum izdavanja:

29.10.2014.

Podaci na drugim jezicima: hrvatski

Posjeta: 7.233 *