- Tytuł:
- Short and long forecast to implement predictive maintenance in a pulp industry
- Autorzy:
-
Rodrigues, João Antunes
Farinha, José Torres
Mendes, Mateus
Mateus, Ricardo
Cardoso, António Marques - Powiązania:
- https://bibliotekanauki.pl/articles/2057978.pdf
- Data publikacji:
- 2022
- Wydawca:
- Polska Akademia Nauk. Polskie Naukowo-Techniczne Towarzystwo Eksploatacyjne PAN
- Tematy:
-
predictive maintenance
condition based maintenance
time series
artificial neural networks
forecasting - Opis:
- Predictive maintenance is very important for effective prevention of failures in an industry. The present paper describes a case study where a wood chip pump system was analyzed, and a predictive model was proposed. An Ishikawa diagram and FMECA are used to identify possible causes for system failure. The Chip Wood has several sensors installed to monitor the working conditions and system state. The authors propose a variation of exponential smoothing technique for short time forecasting and an artificial neural network for long time forecasting. The algorithms were integrated into a dashboard for online condition monitoring, where the users are alerted when a variable is determined or predicted to get out of the expected range. Experimental results show prediction errors in general less than 10 %. The proposed technique may be of help in monitoring and maintenance of the asset, aiming at greater availability.
- Źródło:
-
Eksploatacja i Niezawodność; 2022, 24, 1; 33--41
1507-2711 - Pojawia się w:
- Eksploatacja i Niezawodność
- Dostawca treści:
- Biblioteka Nauki
Artykuł