ERP SYSTÉM JAKO ZDROJ DAT PRO PREDIKCE PROVOZNÍCH UKAZATELŮ ZA
VYUŽITÍ METOD UMĚLÉ INTELIGENCE

D 2023

ERP SYSTÉM JAKO ZDROJ DAT PRO PREDIKCE PROVOZNÍCH UKAZATELŮ ZA VYUŽITÍ METOD UMĚLÉ INTELIGENCE

BARČÁK, Tomáš, Zdeněk FRANĚK, Jan FAMFULÍK and Michal RICHTÁŘ

Basic information

Original name

ERP SYSTÉM JAKO ZDROJ DAT PRO PREDIKCE PROVOZNÍCH UKAZATELŮ ZA VYUŽITÍ METOD UMĚLÉ INTELIGENCE

Authors

BARČÁK, Tomáš (203 Czech Republic, guarantor, belonging to the institution), Zdeněk FRANĚK (203 Czech Republic, belonging to the institution), Jan FAMFULÍK (203 Czech Republic) and Michal RICHTÁŘ (203 Czech Republic)

Edition

Karviná, 4th International conference on Decision making for Small and Medium-Sized Enterprises. Conference proceedings. p. 11-17, 264 pp. 2023

Publisher

Silesian University in Opava, School of Business Administration in Karviná

Other information

Language

English

Type of outcome

Stať ve sborníku

Field of Study

10200 1.2 Computer and information sciences

Country of publisher

Czech Republic

Confidentiality degree

není předmětem státního či obchodního tajemství

Publication form

electronic version available online

References:

URL

RIV identification code

RIV/47813059:19520/23:A0000418

Organization unit

School of Business Administration in Karvina

ISBN

978-80-7510-554-7

Keywords in English

Clouds; Enterprise Resource Planning; Neural Networks; Operational Indicator; Weibull Distribution;

Změněno: 1/4/2024 21:29, Miroslava Snopková

Abstract

V originále

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.

Citovat

BARČÁK, Tomáš, Zdeněk FRANĚK, Jan FAMFULÍK and Michal RICHTÁŘ. ERP SYSTÉM JAKO ZDROJ DAT PRO PREDIKCE PROVOZNÍCH UKAZATELŮ ZA VYUŽITÍ METOD UMĚLÉ INTELIGENCE (ERP SYSTEM AS A SOURCE OF DATA FOR PREDICTING OPERATIONAL INDICATORS USING ARTIFICIAL INTELLIGENCE METHODS). Online. In Roman Šperka, Petr Suchánek, Jarmila Duháček Šebestová, Radim Dolák, Tomáš Barčák, Radka Bauerová, Šárka Čemerková, Michal Halaška, Radmila Krkošková, Kateřina Matušínská, Jiří Mazurek, Žaneta Rylková, Šárka Zapletalová. 4th International conference on Decision making for Small and Medium-Sized Enterprises. Conference proceedings. Karviná: Silesian University in Opava, School of Business Administration in Karviná, 2023, p. 11-17, 264 pp. ISBN 978-80-7510-554-7.

@inproceedings{74581,
   author = {Barčák, Tomáš and Franěk, Zdeněk and Famfulík, Jan and Richtář, Michal},
   address = {Karviná},
   booktitle = {4th International conference on Decision making for Small and Medium-Sized Enterprises. Conference proceedings.},
   editor = {Roman Šperka, Petr Suchánek, Jarmila Duháček Šebestová, Radim Dolák, Tomáš Barčák, Radka Bauerová, Šárka Čemerková, Michal Halaška, Radmila Krkošková, Kateřina Matušínská, Jiří Mazurek, Žaneta Rylková, Šárka Zapletalová},
   keywords = {Clouds; Enterprise Resource Planning; Neural Networks; Operational Indicator; Weibull Distribution;},
   howpublished = {elektronická verze "online"},
   language = {eng},
   location = {Karviná},
   isbn = {978-80-7510-554-7},
   pages = {11-17},
   publisher = {Silesian University in Opava, School of Business Administration in Karviná},
   title = {ERP SYSTÉM JAKO ZDROJ DAT PRO PREDIKCE PROVOZNÍCH UKAZATELŮ ZA VYUŽITÍ METOD UMĚLÉ INTELIGENCE},
   url = {https://demsme.opf.slu.cz/},
   year = {2023}
}

TY  - JOUR
ID  - 74581
AU  - Barčák, Tomáš - Franěk, Zdeněk - Famfulík, Jan - Richtář, Michal
PY  - 2023
TI  - ERP SYSTÉM JAKO ZDROJ DAT PRO PREDIKCE PROVOZNÍCH UKAZATELŮ ZA VYUŽITÍ METOD UMĚLÉ INTELIGENCE
PB  - Silesian University in Opava, School of Business Administration in Karviná
CY  - Karviná
SN  - 9788075105547
KW  - Clouds
KW  - Enterprise Resource Planning
KW  - Neural Networks
KW  - Operational Indicator
KW  - Weibull Distribution;
UR  - https://demsme.opf.slu.cz/
N2  - 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.
ER  -

BARČÁK, Tomáš, Zdeněk FRANĚK, Jan FAMFULÍK and Michal RICHTÁŘ. ERP SYSTÉM JAKO ZDROJ DAT PRO PREDIKCE PROVOZNÍCH UKAZATELŮ ZA VYUŽITÍ METOD UMĚLÉ INTELIGENCE (ERP SYSTEM AS A SOURCE OF DATA FOR PREDICTING OPERATIONAL INDICATORS USING ARTIFICIAL INTELLIGENCE METHODS). Online. In Roman Šperka, Petr Suchánek, Jarmila Duháček Šebestová, Radim Dolák, Tomáš Barčák, Radka Bauerová, Šárka Čemerková, Michal Halaška, Radmila Krkošková, Kateřina Matušínská, Jiří Mazurek, Žaneta Rylková, Šárka Zapletalová. \textit{4th International conference on Decision making for Small and Medium-Sized Enterprises. Conference proceedings.}. Karviná: Silesian University in Opava, School of Business Administration in Karviná, 2023, p.~11-17, 264 pp. ISBN~978-80-7510-554-7.

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