Reducing the probability of failure in manufacturing equipment by quantitative FTA analysis

• Autorzy: Bujna Marián , Prístavka Miroslav , Lee Chia Kuang , Borusiewicz Andrzej , Samociuk Waldemar , Beloev Ivan , Malaga-Toboła Urszula

Identyfikatory

DOI

10.2478/agriceng-2023-0019

Warianty tytułu

PL

Zmniejszenie prawdopodobieństwa występowania awarii urządzeń produkcyjnych dzięki ilościowej analizie FTA

• Języki publikacji: EN

Abstrakty

EN

Fault Tree Analysis (FTA) is a method that directly focuses on the modes of failures. The FTA is a graphical representation of the major faults or critical failures associated with a product, as well as the causes for the faults and potential countermeasures. The aim of this research paper is to calculate the probability of the top event - the failure of the process using FTA and propose a technique to prioritize factors for action design and reduce the likelihood of a top event failure based on manufacturers' requirements. We have constructed a qualitative fault tree to produce office components packed and sealed in blister packs using a KOCH KBS-PL machine. We defined the top event G – the production of office components, packed and sealed in blister packs on the machinery KOCH KBS-PL. Then we defined events leading to top events down to individual failure factors. Based on the links between the fault tree and the probability of failure, we performed a quantitative analysis to determine the probability of failure of individual events. We found out that the probability of failure of G is 5.04%. Subsequently, we identified which factors most significantly reduce the resulting probability of failure of factor G. These are the factors: E - feed rate, F - cooling, AL - incorrect setting and D - break. It has been proven that by controlling these 4 factors, we can reduce the probability of failure of top event G to 2.36%, provided that effective measures are taken. The final proposal meets the requirements of several manufacturers for a fast, efficient, and cost-effective solution. We have created a proposal that saves time, has minimal software and hardware requirements, and is easy to use. The efficiency and effectiveness of the proposal was that we identified the weakest points in the fault tree that most significantly cause the top event to fail. This prioritized the factors for the design of the measures.

PL

Analiza Drzewa Usterek (Fault Tree Analysis, FTA) to metoda opracowana z myślą o rozwiązywaniu usterek maszyn produkcyjnych. Umożliwia ona graficzne przedstawienie głównych usterek lub krytycznych awarii oraz ich przyczyn, a także potencjalnych środków zaradczych. Celem artykułu jest obliczenie prawdopodobieństwa wystąpienia głównego zdarzenia - awarii procesu - za pomocą FTA oraz zaproponowanie techniki priorytetyzacji czynników w projektowaniu działań naprawczych i zmniejszenia prawdopodobieństwa awarii głównego zdarzenia bazując na specyfikacji producenta. W toku badań skonstruowaliśmy jakościowe drzewo usterek do produkcji komponentów biurowych pakowanych i zabezpieczanych w opakowaniach blisterowych na maszynie KOCH KBSPL. Zdefiniowaliśmy główne zdarzenie G - produkcję komponentów biurowych. Następnie zdefiniowaliśmy zdarzenia prowadzące od głównych zdarzeń aż do indywidualnych czynników awarii. Na podstawie powiązań między drzewem usterek a prawdopodobieństwem awarii przeprowadziliśmy analizę ilościową, by określić prawdopodobieństwo awarii poszczególnych zdarzeń. Okazało się, że prawdopodobieństwo awarii G wynosi 5,04%. Następnie ustaliliśmy, które czynniki najbardziej przyczyniają się do zmniejszenia wynikowego prawdopodobieństwa awarii czynnika G. Są to: E - prędkość podawania, F - chłodzenie, AL - nieprawidłowe ustawienie i D - przerwa. Udowodniliśmy, że kontrolując te cztery czynniki możemy zmniejszyć prawdopodobieństwo awarii głównego zdarzenia G do 2,36%, pod warunkiem, że zostaną podjęte skuteczne działania. Ostateczna propozycja spełnia wymagania wielu producentów, którzy oczekują szybkiego, wydajnego i niedrogiego rozwiązania. Stworzyliśmy propozycję, która oszczędza czas, ma minimalne wymagania sprzętowe i programowe oraz jest łatwa w użyciu. Efektywność i skuteczność proponowanego rozwiązania polegała na tym, że zidentyfikowaliśmy najsłabsze punkty w drzewie usterek, które w największym stopniu powodują awarię głównego zdarzenia. To pozwoliło priorytetyzować czynniki do projektowania środków zaradczych.

Słowa kluczowe

EN

fault tree; fault probability; production technology; failure mode

PL

drzewo usterek; prawdopodobieństwo usterek; technologia produkcji; tryb awarii

• Wydawca: Polskie Towarzystwo Inżynierii Rolniczej
• Czasopismo: Agricultural Engineering
• Rocznik: 2023
• Tom: Vol. 27, No. 1
• Strony: 255--271
• Opis fizyczny: Bibliogr. 44 poz., rys., tab.

Twórcy

autor

Bujna Marián

• Institute of Design and Engineering Technologies, Slovak University of Agriculture in Nitra, Slovakia

• https://orcid.org/0000-0003-4281-5649

autor

Prístavka Miroslav

• Institute of Design and Engineering Technologies, Slovak University of Agriculture in Nitra, Slovakia

• https://orcid.org/0000-0002-7957-4765

autor

Lee Chia Kuang

• Faculty of Industrial Management, Universiti Teknologi Malaysia

• https://orcid.org/0000-0001-6063-8071

autor

Borusiewicz Andrzej

• International University of Applied Sciences in Lomza, Poland

• https://orcid.org/0000-0002-1407-7530

autor

Samociuk Waldemar

• Faculty of Production Engineering, University of Life Sciences in Lublin, Głęboka 28, 20-612 Lublin, Poland

• https://orcid.org/0000-0003-1095-0651

autor

Beloev Ivan

• Department of Transport, Faculty of Transport, “Angel Kanchev” University of Ruse, Bulgaria

• https://orcid.org/0000-0003-2014-1970

autor

Malaga-Toboła Urszula

• Department of Production Engineering, Logistics and Applied Computer Science, Faculty of Production and Power Engineering, University of Agriculture in Krakow, Balicka 116B, 30-149 Krakow

• https://orcid.org/0000-0001-7918-8699

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Uwagi

Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).