A competitive model for predicting the readiness of the maintenance system has been developed using the semi-Markov model.
The method of using the Semi-Markov model in a complex system has been presented.
The method of estimating the parameters of the semi-Markov model has been presented in a situation where the sojourn time distributions in the given state are not identifiable using one of the classical distributions.
Diagnostics and evaluation of a transport company in terms of its readiness have beenmade
Modelling the time that the system remains in a given state using classical distributions is not always possible. In many cases, empirical distributions are multimodal due to the influence of external, hidden factors and the selection of the best classical distributions may lead to erroneous results. In the article the method of diagnosis of influence of hidden factors into sojourn time of semi-Markov models was presented. In order to capture hidden factors, the authors proposed to model the distributions of the sojourn time with a mixture of distributions, which is a significant novelty in relation to the studies presented in the literature. Hidden factors directly affect the reliability of technical systems. Detecting the existence of these factors enables more accurate modeling of system readiness. Paying attention to irregularities caused by hidden factors makes it possible to reduce system maintenance costs. Such a system model provides complete information and enables a reliable assessment of the system readiness and maintenance.
CITATIONS(15):
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A MATHEMATICAL MODEL FOR IDENTIFYING MILITARY TRAINING FLIGHTS Anna Borucka, Przemysław Jabłoński, Krzysztof Patrejko, Łukasz Patrejko Aviation
Application of Logistic Regression to Analyze The Economic Efficiency of Vehicle Operation in Terms of the Financial Security of Enterprises Malgorzata Grzelak, Paulina Owczarek, Ramona-Monica Stoica, Daniela Voicu, Radu Vilău Logistics
The use of the multi-sequential LSTM in electrical tomography for masonry wall moisture detection Monika Kulisz, Grzegorz Kłosowski, Tomasz Rymarczyk, Anna Hoła, Konrad Niderla, Jan Sikora Measurement
The use of decision trees to identify the causes of failures in a medical enterprise - a case study Izabela Rojek, Małgorzata Jasiulewicz-Kaczmarek, Mariusz Piechowski, Dariusz Mikołajewski IFAC-PapersOnLine
Improving the efficiency of greasing operations with the lubrication management support system - a case study Mariusz Piechowski, Ryszard Wyczółkowski, Waldemar Paszkowski, Artur Meller IFAC-PapersOnLine
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