ERP SYSTÉM JAKO ZDROJ DAT PRO PREDIKCE PROVOZNÍCH UKAZATELŮ ZA VYUŽITÍ METOD UMĚLÉ INTELIGENCE
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F47813059%3A19520%2F23%3AA0000418" target="_blank" >RIV/47813059:19520/23:A0000418 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
ERP SYSTÉM JAKO ZDROJ DAT PRO PREDIKCE PROVOZNÍCH UKAZATELŮ ZA VYUŽITÍ METOD UMĚLÉ INTELIGENCE
Original language description
The article shows an overview of the standard functions of the ERP (Enterprise Resource Planning) information system in manufacturing companies and deals with the ERP system data for the optimization of reliability, management and product quality process. A comprehensive approach to data collection, processing and their storage in the ERP system (cloud storage, data warehouses) is necessary for successful management of the production process. By using advanced statistical and artificial intelligence methods (neural networks, trees, logistic regression), it is possible to analyze the data and obtain additional knowledge and dependencies in the data. The application part of the article presents the prediction of reliability indicators. From the ERP system database, the data set of a time to failure has been obtained. This data for the creation of a parametric model, based on Weibull distribution, has been used. The article demonstrates the application of artificial neural networks for the prediction of reliability indicators, and a parametric model based on the Weibull distribution has been created from the input data.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2023
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
4th International conference on Decision making for Small and Medium-Sized Enterprises. Conference proceedings.
ISBN
9788075105547
ISSN
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e-ISSN
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Number of pages
7
Pages from-to
11-17
Publisher name
Silesian University in Opava, School of Business Administration in Karviná
Place of publication
Karviná
Event location
Petrovice u Karviné, Czech Republic
Event date
May 18, 2023
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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