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

Kód výsledku v 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>

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

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

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

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

Popis výsledku anglicky

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.

Druh

D - Stať ve sborníku

CEP obor

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OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

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Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2023

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

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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Počet stran výsledku

7

Strana od-do

11-17

Název nakladatele

Silesian University in Opava, School of Business Administration in Karviná

Místo vydání

Karviná

Místo konání akce

Petrovice u Karviné, Czech Republic

Datum konání akce

18. 5. 2023

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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