A New Stochastic Model for Systems Under General Repairs

Guo, Huairui; Liao, Haitao; Zhao, Wenhua; Mettas, Adamantios

doi:10.1109/tr.2006.890895

Cited by 45 publications

(18 citation statements)

References 15 publications

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“…This method was proposed by Kijima et al [46], which suggested that a system with virtual age V ≥ 0 behaves as if it was a new system which reached the age v without failure [46]. The main idea of the virtual age models, in fact, is to evaluate failure intensity considering virtual age instead of the real time [47].…”

Section: Virtual Age Methodsmentioning

confidence: 99%

Imperfect Maintenance Models, from Theory to Practice

Carlo¹,

Arleo²

2017

System Reliability

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The role of maintenance in the industrial environment changed a lot in recent years, and today, it is a key function for long-term profitability in an organization. Many contributions were recently written by researchers on this topic. A lot of models were proposed to optimize maintenance activities while ensuring availability and high-quality requirements. In addition to the well-known classification of maintenance activities-preventive and corrective-in the last decades, a new classification emerged in the literature regarding the degree of system restoration after maintenance actions. Among them, the imperfect maintenance is one of the most studied maintenance types: it is defined as an action after which the system lies in a state somewhere between an "as good as new" state and its pre-maintenance condition "as bad as old." Most of the industrial companies usually operate with imperfect maintenance actions, even if the awareness in actual industrial context is limited. On the practical definition side, in particular, there are some real situations of imperfect maintenance: three main specific cases were identified, both from literature analysis and from experience. Considering these three implementations of imperfect maintenance actions and the main models proposed in the literature, we illustrate how to identify the most suitable model for each real case.

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Section: Virtual Age Methodsmentioning

confidence: 99%

Imperfect Maintenance Models, from Theory to Practice

Carlo¹,

Arleo²

2017

System Reliability

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“…This test statistic follows a standard normal distribution, this test is recommended for the case when the choice is between trend exist (HPP) and trend not exist (NHPP) [3].…”

Section: Test For the Time Trend And Repair Effectmentioning

confidence: 99%

Stochastic renewal process model for maintenance (case study: thermal electricity generation in Sudan)

Qurashi

Hamdi²

2016

IJASP

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The renewal process define as a counting process where the times between the count renewals is a random variables and their distribution is identical. In the electricity generation machines there are spare parts replaced due to damage or expired and replacement process occur repeatedly and the renewal process of here assume that times between replacements are independent random variables and it has identical probability distribution. In this paper, renewal process model has applied on the time of fault for machine in Bahri Thermal Station for electricity generation, which is belong to the National Electricity Authority in Sudan during the period (2011)(2012)(2013)(2014)(2015). Through the renewal process model estimation is clear that, the failure time (renewal) for the machines follow Weibull distribution with 2-parameters and when the time trend has been tested it is clear that no trend exist which mean that the renewal process represent Homogeneous Poisson Process (HPP), and the repair rate (renewal) is occurred constantly. In addition, the findings approve that whenever the repair rate (renewal) increase the mean time between failures (MTBF) increases too and this clear in machine no (6).

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“…Knowledge of the effect of repair is important for determining optimum maintenance policy (Scarf, 1997;Dekker & Scarf, 1998;Wang, 2002;Xiang, 2013;Zhong & Jin, 2014;Kirschenmann, Popova, Damien, & Hanson, 2014) and modelling the repair effect has attracted considerable research (e.g., Malik, 1979;Nakagawa, 1988;Kijima, 1989;Doyen & Gaudoin, 2004;Guo, Liao, Zhao, & Mettas, 2007;Wu & Zuo, 2010). The repair effect can be accommodated by a number of means, such as modification of the failure intensity or reduction of the virtual age of the system.…”

Section: Motivationmentioning

confidence: 99%

“…These models, however, do not consider scenarios in which the failure processes of systems are impacted by extrinsic factors quantified through covariates, especially time-dependent covariates, although Guo et al (2007) considers a special scenario in which ϕ(t) in equation (1) is assumed to follow a power law. When dealing with time-dependent covariates, one has to be very careful since there are some complications that arise with such scenarios.…”

Section: Related Workmentioning

confidence: 99%

Decline and repair, and covariate effects

Scarf

2015

European Journal of Operational Research

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The failure processes of repairable systems may be impacted by operational and environmental stress factors. To accommodate such factors, reliability can be modelled using a multiplicative intensity function. In the proportional intensity model, the failure intensity is the product of the failure intensity function of the baseline system that quantifies intrinsic factors and a function of covariates that quantify extrinsic factors. The existing literature has extensively studied the failure processes of repairable systems using general repair concepts such as age-reduction when no covariate effects are considered. This paper investigates different approaches for modelling the failure and repair process of repairable systems in the presence of time-dependent covariates. We derive probabilistic properties of the failure processes for such systems.

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A New Stochastic Model for Systems Under General Repairs

Cited by 45 publications

References 15 publications

Imperfect Maintenance Models, from Theory to Practice

Imperfect Maintenance Models, from Theory to Practice

Stochastic renewal process model for maintenance (case study: thermal electricity generation in Sudan)

Decline and repair, and covariate effects

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