State-age-dependent maintenance policies for deteriorating systems with Erlang sojourn time distributions
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Cited by (42)
Cost effective scheduling of imperfect inspections in systems with hidden failures and rescue possibility
2019, Applied Mathematical ModellingCitation Excerpt :Refer to [6] for a survey explaining and comparing different models. Examples include periodic inspections or preventive maintenance models [3,7–10], age-dependent models [11–13], condition-based inspection models [14–16], predictive models [17–19], opportunistic policies [1,20–23], preparedness models [24], reference-time based models [25,26], risk-based inspections [27–29], etc. Based on time span considered, inspection policies have been investigated for systems over infinite and finite time horizons while the finite one is more practical as the mission time or operation time of real-world system units is usually limited [30,31].
Bayesian prediction for flowgraph models with covariates. An application to bladder carcinoma
2016, Journal of Computational and Applied MathematicsAn integrated framework for online diagnostic and prognostic health monitoring using a multistate deterioration process
2014, Reliability Engineering and System SafetyCitation Excerpt :The second limitation of current studies is the lack of model selection approaches. In other words, in most work in the literature, it is assumed that the structure of the multistate degradation process is already known [15,16]. Here, structure refers to certain elements, such as the number of states, the connectivity between states, the distribution of transitions between states, the stochastic relationship between the actual health states and the condition monitoring data, which together characterize the associated multistate degradation process.
Design and management of manufacturing systems for production quality
2014, CIRP Annals - Manufacturing TechnologyFatigue crack growth estimation by relevance vector machine
2012, Expert Systems with ApplicationsCitation Excerpt :Many researchers have focused on the problem of building exhaustive models of deteriorating components and structures to implement model-based prognostic tools. Markov and semi-Markov models have been widely exploited for achieving analytical results (Baruah & Chinnam, 2005; Bérenguer, Grall, & Castanier, 2000; Dong & He, 2007; Grall, Bérenguer, & Chu, 1998; Hontelez, Burger, & Wijnmalen, 1996; Kopnov, 1999; Lam & Yeh, 1994; Samanta, Vesely, Hsu, & Subudly, 1991; Yeh, 1997). On the basis of these models, several approaches have been proposed to analyze reliability-based and condition-based maintenance policies (Castanier, Bérenguer, & Grall, 2002; Chen & Trivedi, 2005; Pulkkinen & Uryas’ev, 1992; Vlok, Coetzee, Banjevic, Jardine, & Makis, 2002).
Optimal integrated process control and maintenance under general deterioration
2012, Reliability Engineering and System SafetyCitation Excerpt :In this context Kao [12], So [13], Lam and Yeh [14], Moustafa et al. [15] and Kim and Makis [16] derive optimal state-dependent or state-age-dependent preventive maintenance policies but they assume that the actual operating state is continuously and accurately known. Yeh [17,18] and Chen and Trivedi [19] expand the previous semi-Markovian models assuming intermittent inspections and derive the optimal inspection frequency as well, but they also assume that inspections provide perfect information about the process state. More general non-Markovian maintenance models under continuous and accurate monitoring have been presented by Al-Ali and Murari [20], Murthy and Iskadar [21], Su and Chang [22] and Panagiotidou and Tagaras [23,24].