Comparison of Proportional Hazards Modeling, Additive Hazards Modeling and Proportional Intensity Modeling When Applied to Repairable System Reliability

Wightman, D.W.; Bendell, Tony

doi:10.1142/s0218539395000046

Cited by 3 publications

(3 citation statements)

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“…This model provides the means for modelling a circumstance when the hazard is not zero at time zero. Maximum likelihood procedures can be used to estimate this model's parameters [54].…”

Section: Two-step Regression Modelmentioning

confidence: 99%

“…PIM is similar to PHM, but with the underlying failure mechanism following a stochastic point process rather than a probabilistic distribution [63]. PIM is used to model the intensity process of failures and repairs of a repairable system which incorporates explanatory variables [54,64]. Volk et al [65] introduces PIM for both non-repairable and repairable systems utilising historic failure data and corresponding diagnostic measurements.…”

Section: Proportional Intensity Modelmentioning

confidence: 99%

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A review on reliability models with covariates

Gorjian

Mittinty

et al. 2010

Engineering Asset Lifecycle Management

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Modern Engineering Asset Management (EAM) requires the accurate assessment of current and the prediction of future asset health condition. Suitable mathematical models that are capable of predicting Time-to-Failure (TTF) and the probability of failure in future time are essential. In traditional reliability models, the lifetime of assets is estimated using failure time data. However, in most real-life situations and industry applications, the lifetime of assets is influenced by different risk factors, which are called covariates. The fundamental notion in reliability theory is the failure time of a system and its covariates. These covariates change stochastically and may influence and/or indicate the failure time. Research shows that many statistical models have been developed to estimate the hazard of assets or individuals with covariates. An extensive amount of literature on hazard models with covariates (also termed covariate models), including theory and practical applications, has emerged. This paper is a state-of-the-art review of the existing literature on these covariate models in both the reliability and biomedical fields. One of the major purposes of this expository paper is to synthesise these models from both industrial reliability and biomedical fields and then contextually group them into non-parametric and semiparametric models. Comments on their merits and limitations are also presented. Another main purpose of this paper is to comprehensively review and summarise the current research on the development of the covariate models so as to facilitate the application of more covariate modelling techniques into prognostics and asset health management.

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“…This model provides the means for modelling a circumstance when the hazard is not zero at time zero. Maximum likelihood procedures can be used to estimate this model's parameters [54].…”

Section: Two-step Regression Modelmentioning

confidence: 99%

Section: Proportional Intensity Modelmentioning

confidence: 99%

A review on reliability models with covariates

Gorjian

Mittinty

et al. 2010

Engineering Asset Lifecycle Management

View full text Add to dashboard Cite

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“…Kumar [14] applies the stratified proportional hazard model, which is the simplest and most useful extension of the proportional hazard model, to estimate the hazard and reliability of engineering assets. The proportional intensity model is exercised in different reliability fields [34][35][36][37][38]. Sun et al [39] Merits:…”

Section: Overview On Applications Of Covariate-based Hazard Modelmentioning

confidence: 99%

The Explicit Hazard Model- part 2: Applications

Gorjian

Mittinty

et al. 2010

2010 Prognostics and System Health Management Conference

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Hazard and reliability prediction of an engineering asset is one of the significant fields of research in Engineering Asset Health Management (EAHM). In real-life situations where an engineering asset operates under dynamic operational and environmental conditions, the lifetime of an engineering asset can be influenced and/or indicated by different factors that are termed as covariates. The Explicit Hazard Model (EHM) as a covariate-based hazard model is a new approach for hazard prediction which explicitly incorporates both internal and external covariates into one model. EHM is an appropriate model to use in the analysis of lifetime data in presence of both internal and external covariates in the reliability field. This paper presents applications of the methodology which is introduced and illustrated in the theory part of this study. In this paper, the semi-parametric EHM is applied to a case study so as to predict the hazard and reliability of resistance elements on a Resistance Corrosion Sensor Board (RCSB).

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Software reliability and cost models: Perspectives, comparison, and practice

Pham

2003

European Journal of Operational Research

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Comparison of Proportional Hazards Modeling, Additive Hazards Modeling and Proportional Intensity Modeling When Applied to Repairable System Reliability

Cited by 3 publications

References 0 publications

A review on reliability models with covariates

A review on reliability models with covariates

The Explicit Hazard Model- part 2: Applications

Software reliability and cost models: Perspectives, comparison, and practice

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