Semi-Markov approach for reliability modelling of light utility vehicles

被引:18
作者
Oszczypala, Mateusz [1 ]
Ziolkowski, Jaroslaw [1 ]
Malachowski, Jerzy [1 ]
机构
[1] Mil Univ Technol, Inst Mech & Computat Engn, Fac Mech Engn, Warsaw, Poland
来源
EKSPLOATACJA I NIEZAWODNOSC-MAINTENANCE AND RELIABILITY | 2023年 / 25卷 / 02期
关键词
semi-Markov model; reliability modelling; readiness; maintenance analysis; transportation system; CHAIN MODEL; SYSTEMS; COMPONENTS; FAILURE;
D O I
10.17531/ein/161859
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Vehicles are important elements of military transport systems. Semi-Markov processes, owing to the generic assumption form, are a useful tool for modelling the operation process of numerous technical objects and systems. The suggested approach is an extension of existing stochastic methods employed for a wide spectrum of technical objects; however, research on light utility vehicles complements the subject gap in the scientific literature. This research paper discusses the 3-state semi-Markov model implemented for the purposes of developing reliability analyses. Based on an empirical course of the operation process, the model was validated in terms of determining the conditional probabilities of interstate transitions for an embedded Markov chain, as well as parameters of time distribution functions. The Laplace transform was used to determine the reliability function, the failure probability density function, the failure intensity, and the expected time to failure. The readiness index values were calculated on ergodic probabilities.
引用
收藏
页数:13
相关论文
共 60 条
  • [1] Dynamic reliability modeling for general standby systems
    Alkaff, Abdullah
    Qomarudin, Mochamad Nur
    Purwantini, Elly
    Wiratno, Stefanus Eko
    [J]. COMPUTERS & INDUSTRIAL ENGINEERING, 2021, 161
  • [2] [Anonymous], 2013, STAT INFERENCE DISCR, DOI DOI 10.1007/978-81-322-0763-4
  • [3] Reliability prediction-based improved dynamic weight particle swarm optimization and back propagation neural network in engineering systems
    Bai, Bin
    Zhang, Junyi
    Wu, Xuan
    Zhu, Guang Wei
    Li, Xinye
    [J]. EXPERT SYSTEMS WITH APPLICATIONS, 2021, 177
  • [4] Sequential Interval Reliability for Discrete-Time Homogeneous Semi-Markov Repairable Systems
    Barbu, Vlad Stefan
    D'Amico, Guglielmo
    Gkelsinis, Thomas
    [J]. MATHEMATICS, 2021, 9 (16)
  • [5] Numerical treatment of homogeneous and non-homogeneous semi-Markov reliability models
    Blasi, A
    Janssen, J
    Manca, R
    [J]. COMMUNICATIONS IN STATISTICS-THEORY AND METHODS, 2004, 33 (03) : 697 - 714
  • [6] FORECASTING THE READINESS OF SPECIAL VEHICLES USING THE SEMI-MARKOV MODEL
    Borucka, Anna
    Niewczas, Andrzej
    Hasilova, Kamila
    [J]. EKSPLOATACJA I NIEZAWODNOSC-MAINTENANCE AND RELIABILITY, 2019, 21 (04): : 662 - 669
  • [7] BRAYER EF, 1957, ROY STAT SOC C-APP, V6, P67
  • [8] A novel reliability allocation approach using the OWA tree and soft set
    Chang, Kuei-Hu
    [J]. ANNALS OF OPERATIONS RESEARCH, 2016, 244 (01) : 3 - 22
  • [9] Multi-State Reliability Systems Under Discrete Time Semi-Markovian Hypothesis
    Chryssaphinou, Ourania
    Limnios, Nikolaos
    Malefaki, Sonia
    [J]. IEEE TRANSACTIONS ON RELIABILITY, 2011, 60 (01) : 80 - 87
  • [10] Single-use reliability computation of a semi-Markovian system
    D'Amico, Guglielmo
    [J]. APPLICATIONS OF MATHEMATICS, 2014, 59 (05) : 571 - 588