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    Wyświetlanie 1-4 z 4
    Tytuł:
    Diagnosis of Missed Ductile Iron Melts with Process Modelling
    Autorzy:
    Perzyk, M.
    Werlaty, M.
    Powiązania:
    https://bibliotekanauki.pl/articles/382916.pdf
    Data publikacji:
    2017
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    quality management
    information technology
    foundry industry
    process fault diagnosis
    ductile iron melting
    data driven model
    zarządzanie jakością
    technologia informacyjna
    przemysł odlewniczy
    diagnostyka uszkodzeń
    topienie żeliwa
    Opis:
    The paper presents an application of advanced data-driven (soft) models in finding the most probable particular causes of missed ductile iron melts. The proposed methodology was tested using real foundry data set containing 1020 records with contents of 9 chemical elements in the iron as the process input variables and the ductile iron grade as the output. This dependent variable was of discrete (nominal) type with four possible values: ‘400/18’, ‘500/07’, ‘500/07 special’ and ‘non-classified’, i.e. the missed melt. Several types of classification models were built and tested: MLP-type Artificial Neural Network, Support Vector Machine and two versions of Classification Trees. The best accuracy of predictions was achieved by one of the Classification Tree model, which was then used in the simulations leading to conversion of the missed melts to the expected grades. Two strategies of changing the input values (chemical composition) were tried: content of a single element at a time and simultaneous changes of a selected pair of elements. It was found that in the vast majority of the missed melts the changes of single elements concentrations have led to the change from the non-classified iron to its expected grade. In the case of the three remaining melts the simultaneous changes of pairs of the elements’ concentrations appeared to be successful and that those cases were in agreement with foundry staff expertise. It is concluded that utilizing an advanced data-driven process model can significantly facilitate diagnosis of defective products and out-of-control foundry processes.
    Źródło:
    Archives of Foundry Engineering; 2017, 17, 4; 123-126
    1897-3310
    2299-2944
    Pojawia się w:
    Archives of Foundry Engineering
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Methodology of Fault Diagnosis in Ductile Iron Melting Process
    Autorzy:
    Perzyk, M.
    Kozlowski, J.
    Powiązania:
    https://bibliotekanauki.pl/articles/382169.pdf
    Data publikacji:
    2016
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    quality management
    information technology
    foundry industry
    process fault diagnosis
    ductile iron
    data driven model
    zarządzanie jakością
    technologia informatyczna
    przemysł odlewniczy
    diagnostyka uszkodzeń
    żeliwo ADI
    model danych
    Opis:
    Statistical Process Control (SPC) based on the Shewhart’s type control charts, is widely used in contemporary manufacturing industry, including many foundries. The main steps include process monitoring, detection the out-of-control signals, identification and removal of their causes. Finding the root causes of the process faults is often a difficult task and can be supported by various tools, including data-driven mathematical models. In the present paper a novel approach to statistical control of ductile iron melting process is proposed. It is aimed at development of methodologies suitable for effective finding the causes of the out-of-control signals in the process outputs, defined as ultimate tensile strength (Rm) and elongation (A5), based mainly on chemical composition of the alloy. The methodologies are tested and presented using several real foundry data sets. First, correlations between standard abnormal output patterns (i.e. out-of-control signals) and corresponding inputs patterns are found, basing on the detection of similar patterns and similar shapes of the run charts of the chemical elements contents. It was found that in a significant number of cases there was no clear indication of the correlation, which can be attributed either to the complex, simultaneous action of several chemical elements or to the causes related to other process variables, including melting, inoculation, spheroidization and pouring parameters as well as the human errors. A conception of the methodology based on simulation of the process using advanced input - output regression modelling is presented. The preliminary tests have showed that it can be a useful tool in the process control and is worth further development. The results obtained in the present study may not only be applied to the ductile iron process but they can be also utilized in statistical quality control of a wide range of different discrete processes.
    Źródło:
    Archives of Foundry Engineering; 2016, 16, 4; 101-108
    1897-3310
    2299-2944
    Pojawia się w:
    Archives of Foundry Engineering
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    System zaawansowanego monitorowania i diagnostyki procesów przemysłowych 'AMandD'
    Advanced monitoring and diagnostic system of industrial processes 'AMandD'
    Autorzy:
    Kościelny, J.M.
    Syfert, M.
    Wnuk, P.
    Powiązania:
    https://bibliotekanauki.pl/articles/327448.pdf
    Data publikacji:
    2006
    Wydawca:
    Polska Akademia Nauk. Polskie Towarzystwo Diagnostyki Technicznej PAN
    Tematy:
    system wspomagania decyzji
    nadzorowanie
    diagnostyka uszkodzeń
    symulator procesów
    decision support systems
    supervision
    fault diagnosis
    process simulators
    Opis:
    W artykule zaprezentowano strukturę oraz właściwości użytkowe systemu zaawansowanego monitorowania i diagnostyki AMandD. System ten przeznaczony jest dla złożonych procesów przemysłowych. Przedstawiono opis wykorzystanych w systemie nowoczesnych algorytmów modelowania oraz detekcji i lokalizacji uszkodzeń jak i wykorzystanych rozwiązań informatycznych. Na zakończenie zarysowano także kierunki dalszych badań i rozwoju systemu.
    The paper presents structure and functional properties of the Advanced Monitoring and Diagnostic System 'AMandD' dedicated for large scale industrial processes. Applied in the system up-to-date algorithms of modeling methods and fault detection and isolation were described in the paper. Also a brief description of used IT solutions was presented. As a conclusion, the further directions of development and researches were mentioned.
    Źródło:
    Diagnostyka; 2006, 3(39); 229-238
    1641-6414
    2449-5220
    Pojawia się w:
    Diagnostyka
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Signed directed graph based modeling and its validation from process knowledge and process data
    Autorzy:
    Yang, F.
    Shah, S. L.
    Xiao, D.
    Powiązania:
    https://bibliotekanauki.pl/articles/331384.pdf
    Data publikacji:
    2012
    Wydawca:
    Uniwersytet Zielonogórski. Oficyna Wydawnicza
    Tematy:
    graf skierowany
    diagnostyka uszkodzeń
    system oceny zagrożeń
    signed directed graph
    transfer entropy
    process topology
    fault diagnosis
    process hazard assessment
    Opis:
    This paper is concerned with the fusion of information from process data and process connectivity and its subsequent use in fault diagnosis and process hazard assessment. The Signed Directed Graph (SDG), as a graphical model for capturing process topology and connectivity to show the causal relationships between process variables by material and information paths, has been widely used in root cause and hazard propagation analysis. An SDG is usually built based on process knowledge as described by piping and instrumentation diagrams. This is a complex and experience-dependent task, and therefore the resulting SDG should be validated by process data before being used for analysis. This paper introduces two validation methods. One is based on cross-correlation analysis of process data with assumed time delays, while the other is based on transfer entropy, where the correlation coefficient between two variables or the information transfer from one variable to another can be computed to validate the corresponding paths in SDGs. In addition to this, the relationship captured by data-based methods should also be validated by process knowledge to confirm its causality. This knowledge can be realized by checking the reachability or the influence of one variable on another based on the corresponding SDG which is the basis of causality. A case study of an industrial process is presented to illustrate the application of the proposed methods.
    Źródło:
    International Journal of Applied Mathematics and Computer Science; 2012, 22, 1; 41-53
    1641-876X
    2083-8492
    Pojawia się w:
    International Journal of Applied Mathematics and Computer Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-4 z 4

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