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http://yadda.icm.edu.pl:80/baztech/element/bwmeta1.element.baztech-d48f5928-e56d-4604-9b03-e77f9a7d6b7b

Czasopismo

Fibres & Textiles in Eastern Europe

Tytuł artykułu

Proposing Probabilistic Operational Risk Assessment Model for Textile Industry Using Bayesian Approach

Autorzy Jan, M.  Khalid, M. S.  Awan, A. A.  Nisar, S. 
Treść / Zawartość
1_jan_khalid_awan_nisar_fibres_2018_1.pdf
Warianty tytułu
PL Zaproponowanie modelu probabilistycznej oceny ryzyka operacyjnego dla przemysłu tekstylnego z wykorzystaniem podejścia bayesowskiego.
Języki publikacji EN
Abstrakty
EN Accidents, operational failures and losses prompt authorities to highlight the importance of adequate systems and controls to deal with operational risk (OR). Therefore risk assessment methodology has become a dire need of major industries for undertaking valuable measured in production and operation’s research. The paper describes methodology for conducting the risk assessment of the textile operational domain in general i.e. developing a conceptual risk assessment framework and conducting the methodological implementation of the selected operational risk element using the approach proposed. The risk assessment model proposed embraces the concept of probabilistic risk assessment structural modeling using the Bayesian Approach in its generalised form that may be applied to specific textile operational settings with the definition of dimensions and scales for a specific textile environment. The generalised model proposed can also be applied to different textile industries with the insertion of real data for testing and validation. The OR prediction model proposed is GUI-based, scalable, expandable and can be tested for any textile operations with little modification in parentend nodes under the specific risk element. The paper is helpful to ensure safety and a pro-active approach in textile risk management and also contributes towards the sustainable development of industry operations in the future.
PL Wypadki, awarie i straty operacyjne skłaniają do podkreślenia znaczenia odpowiednich systemów i mechanizmów kontroli w celu radzenia sobie z ryzykiem operacyjnym (OR). W artykule opisano metodologię przeprowadzania oceny ryzyka w zakresie ogólnej działalności włókienniczej, tj. opracowanie ram koncepcyjnej oceny ryzyka i przeprowadzenie metodycznej realizacji wybranego elementu ryzyka operacyjnego z wykorzystaniem proponowanego podejścia. Proponowany model oceny ryzyka obejmuje koncepcję modelowania strukturalnego probabilistycznej oceny ryzyka z wykorzystaniem podejścia bayesowskiego w swojej uogólnionej formie, która może być stosowana do określonych ustawień operacyjnych wyrobów włókienniczych z definicją wymiarów i skal dla określonego środowiska włókienniczego. Proponowany ogólny model może również znaleźć zastosowanie w różnych branżach tekstylnych, wprowadzając rzeczywiste dane do testowania i walidacji. Proponowany model prognozowania OR, oparty na interfejsie GUI, jest skalowalny, rozszerzalny i może być zastosowany w przypadku dowolnych operacji z niewielkimi modyfikacjami w węzłach nadrzędnych/końcowych w ramach określonego elementu ryzyka. Dane zaprezentowane w artykule mogą być przydatne w zakresie zarządzania ryzykiem włókienniczym, a także wnoszą wkład do zrównoważonego rozwoju działalności przemysłowej w przyszłości.
Słowa kluczowe
PL ryzyko operacyjne   probabilistyczny model oceny ryzyka   prawdopodobieństwo   uderzenia   podejście bayesowskie  
EN operational risk   probabilistic risk assessment model   probability   impacts   Bayesian approach  
Wydawca Instytut Biopolimerów i Włókien Chemicznych
Czasopismo Fibres & Textiles in Eastern Europe
Rocznik 2018
Tom Nr 1 (127)
Strony 10--20
Opis fizyczny Bibliogr. 36 poz., rys.
Twórcy
autor Jan, M.
  • National University of Science & Technology, Department of Industrial & Manufacturing Engineering, PNEC, Karachi, Pakistan, mattari.26@gmail.com
autor Khalid, M. S.
  • National University of Science & Technology, Department of Industrial & Manufacturing Engineering, PNEC, Karachi, Pakistan
autor Awan, A. A.
  • National University of Science & Technology, Department of Management & Information System, PNEC, Karachi, Pakistan
autor Nisar, S.
  • National University of Science & Technology, Department of Industrial & Manufacturing Engineering, PNEC, Karachi, Pakistan
Bibliografia
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Uwagi
PL Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2018).
Kolekcja BazTech
Identyfikator YADDA bwmeta1.element.baztech-d48f5928-e56d-4604-9b03-e77f9a7d6b7b
Identyfikatory
DOI 10.5604/01.3001.0010.5860