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.
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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
Original language English
Type of outcome Proceedings paper
Field of Study 10200 1.2 Computer and information sciences
Country of publisher Czech Republic
Confidentiality degree is not subject to a state or trade secret
Publication form electronic version available online
WWW 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;
Changed by Changed by: Miroslava Snopková, učo 43819. Changed: 1/4/2024 21:29.
Abstract
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.
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