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    Wyświetlanie 1-3 z 3
    Tytuł:
    Forecasts of Size of Steel Production in Poland until 2022
    Autorzy:
    Gajdzik, B.
    Powiązania:
    https://bibliotekanauki.pl/articles/2064914.pdf
    Data publikacji:
    2018
    Wydawca:
    STE GROUP
    Tematy:
    steel production
    forecasts
    adaptation models
    Opis:
    The article presents the results of forecasting the volume (size) of steel production in Poland based on selected adaptation models. The data used in forecasting were the annual size of steel production in the period from 2000 to 2017. Data on the size of steel production in Poland were obtained from reports of both the Polish Steel Association in Katowice (Poland) and the World Steel Association. The accuracy of predictions was determined by the values of real deviation of forecasted variable from forecasts (extinguished - ex post) using square root calculated from mean square error of apparent forecasts, ie RMSE - Root Mean Square Error and mean value of relative error of expired forecasts Ψ. Forecasts can be used in making decisions in metallurgical enterprises for building production scenarios.
    Źródło:
    Multidisciplinary Aspects of Production Engineering; 2018, 1, 1; 499--505
    2545-2827
    Pojawia się w:
    Multidisciplinary Aspects of Production Engineering
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    The importance of prediction methods in industry 4.0 on the example of steel industry
    Autorzy:
    Gajdzik, Bożena
    Powiązania:
    https://bibliotekanauki.pl/articles/2064839.pdf
    Data publikacji:
    2019
    Wydawca:
    STE GROUP
    Tematy:
    steel production
    Industry 4.0
    prediction
    forecasts
    Opis:
    This paper presents the importance of the prediction of steel production in industry 4.0 along with forecasts for steel production in the world until 2022. In the last two decades, the virtual world has been increasingly entering production. Today’s manufacturing systems are becoming faster and more flexible – easily adaptable to new products. Steel is the basic structural material (base material) for many industrial sectors. Industries such as automotive, mechanical engineering, construction and transport use steel in their production processes. Prediction methods in cyber-physical production systems are gaining in importance. The task of prediction is to reduce risk in the decision-making process. In autonomous manufacturing systems in industry 4.0 the role of prediction is more active than passive. Forecasts have the following functions: warning, reaction, prevention, normative, etc. The growing number of customized solutions in industry 4.0 translates into new challenges in the production process. Manufacturers must respond to individual customer needs more quickly, be able to personalize products while reducing energy and resource costs (saving energy and resources can increase the product competitiveness). The modern market becomes increasingly unpredictable. Production prediction under such conditions should be carried out continuously, which is possible because there is more empirical data and access to data. Information from the ongoing monitoring of the company’s production is directly transferred to the prospective evaluation. In view of the contemporary reciprocal use of automation, data processing, data exchange and manufacturing techniques, there is greater access to external data, e.g. on production in different target markets and with global, international, national, regional coverage. Companies can forecast in real time, and the forecasts obtained give the possibility to quickly change their production. Industry 4.0 (from the business objective point of view) aims to provide companies with concrete economic benefits – primarily by reducing manufacturing costs, standardizing and stabilizing quality, increasing productivity. Industry 4.0 aims to create a given autonomous smart factory system in which machines, factory components and services communicate and cooperate with each other, producing a personalized product. The aim of this paper is to present new challenges in the production processes in relation to steel production, as well as to prepare and present forecasts of (quantitative) steel production of territorial, global and temporary range until 2022, taking into account the applied production technologies (BOF and EAF). For forecasting purposes, classic trend models and adaptive trend models were used. This methodology was used to build separate forecasts for: total steel production, BOF steel and EAF steel. Empirical data is world steel production in 2000-2017 (annual production volume in Mt).
    Źródło:
    Multidisciplinary Aspects of Production Engineering; 2019, 2, 1; 283--295
    2545-2827
    Pojawia się w:
    Multidisciplinary Aspects of Production Engineering
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Analiza wahań w przebiegu czasowym wielkości produkcji stali na świecie wraz z prognozowaniem wielkości produkcji do 2020 roku
    Analysis of fluctuations in the time trend of world steel production and prognosis od steel production until 2020
    Autorzy:
    Gajdzik, B.
    Szymszal, J.
    Powiązania:
    https://bibliotekanauki.pl/articles/326833.pdf
    Data publikacji:
    2017
    Wydawca:
    Politechnika Śląska. Wydawnictwo Politechniki Śląskiej
    Tematy:
    produkcja światowa
    produkcja stali
    modelowanie prognostyczne
    prognozy
    world production
    steel production
    prognostic modeling
    forecasts
    Opis:
    W artykule omówiono sytuację na światowym rynku stali, ze szczególnym uwzględnieniem dynamiki zmian w wielkości produkcji stali w ostatnich latach. Na podstawie danych statystycznych wielkości produkcji stali za lata 2000-2015 zbudowano prognozy zmian w poziomie produkcji stali na świecie do 2020 roku, uwzględniając cykliczność zmian.
    The article presents the situation in the global steel market, with particular emphasis on the dynamics of changes in the volume of steel production in recent years. Based on statistics (world steel production) from the years 2000-2015 was built the forecast volume of steel production in the world by 2020, according to cycles of changes.
    Źródło:
    Zeszyty Naukowe. Organizacja i Zarządzanie / Politechnika Śląska; 2017, 102; 63-79
    1641-3466
    Pojawia się w:
    Zeszyty Naukowe. Organizacja i Zarządzanie / Politechnika Śląska
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-3 z 3

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