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Wyszukujesz frazę "Sika, Robert" wg kryterium: Autor


Wyświetlanie 1-2 z 2
Tytuł:
Comparison of Selected ERP Systems Supporting the Production Planning and Control on the Example of Automotive Industry
Autorzy:
Sika, Robert
Wojtala, Oliwia
Hajkowski, Jakub
Powiązania:
https://bibliotekanauki.pl/articles/2172187.pdf
Data publikacji:
2022
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
information technology
enterprise management system
automotive industry
Opis:
In many companies, along with the economic development, the use of integrated management systems is becoming more and more common, which are subject to evolution in terms of, inter alia, offered functions and new user requirements. The main purpose of this paper is to compare selected ERP (Enterprise Resource Planning) systems in the field of production planning and control on the example of the automotive industry. The paper presents the contemporary functioning of the automotive industry against the background of issues related to the integrated management systems used in them. The research part presents the proprietary methodology for the assessment of IT systems used in the automotive industry, which included a user survey. The obtained score allowed to indicate the optimal ERP class system supporting production planning and control.
Źródło:
Management and Production Engineering Review; 2022, 13, 3; 39--51
2080-8208
2082-1344
Pojawia się w:
Management and Production Engineering Review
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Application of instance-based learning for cast iron casting defects prediction
Autorzy:
Sika, Robert
Szajewski, Damian
Hajkowski, Jakub
Popielarski, Paweł
Powiązania:
https://bibliotekanauki.pl/articles/407199.pdf
Data publikacji:
2019
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
soft modelling
instance-based learning
k-nearest neighbours algorithm
cast iron casting defects
computer application
Opis:
The paper presents an example of Instance-Based Learning using a supervised classification method of predicting selected ductile cast iron castings defects. The test used the algorithm of k-nearest neighbours, which was implemented in the authors’ computer application. To ensure its proper work it is necessary to have historical data of casting parameter values registered during casting processes in a foundry (mould sand, pouring process, chemical composition) as well as the percentage share of defective castings (unrepairable casting defects). The result of an algorithm is a report with five most possible scenarios in terms of occurrence of a cast iron casting defects and their quantity and occurrence percentage in the casts series. During the algorithm testing, weights were adjusted for independent variables involved in the dependent variables learning process. The algorithms used to process numerous data sets should be characterized by high efficiency, which should be a priority when designing applications to be implemented in industry. As it turns out in the presented mathematical instance-based learning, the best quality of fit occurs for specific values of accepted weights (set #5) for number k = 5 nearest neighbours and taking into account the search criterion according to “product index”.
Źródło:
Management and Production Engineering Review; 2019, 10, 4; 101-107
2080-8208
2082-1344
Pojawia się w:
Management and Production Engineering Review
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-2 z 2

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