Remaining useful life prediction using prognostic methodology based on logical analysis of data and Kaplan–Meier estimation

Ragab, Ahmed; Ouali, Mohamed-Salah; Yacout, Soumaya; Osman, Hany

doi:10.1007/s10845-014-0926-3

Cited by 46 publications

(22 citation statements)

References 29 publications

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“…The Kaplan-Meier estimator 40 is an empirical non-parametric technique to estimate asset reliability. 41,42 It makes no assumptions about the probability distribution, which is used to estimate equipment reliability. 42 The Kaplan-Meier estimator for asset reliability assessment can be calculated with few assumptions required.…”

Section: Kaplan-meier Estimatormentioning

confidence: 99%

Reliability modelling with redundancy—A case study of power generation engines in a wastewater treatment plant

Jolfaei

Jin

Linden

et al. 2019

Quality & Reliability Eng

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Power generators are critical assets in wastewater treatment plants (WWTPs) in Australia and many countries. Better managing the lifetime, minimising failures, improving reliability and availability, and reducing operating and maintenance costs of the power generation assets are still challenging topics for water utilities. This case study aims to develop power generation system reliability and availability modelling considering redundancy to minimise operation and maintenance costs. The two‐parameter Weibull model was used to assess system reliability and availability to power generation engines in WWTPs. The Kaplan‐Meier method (a time‐driven estimation technique) and the log beta‐Weibull model (which is suitable for modelling censored and uncensored data) were used to analyse and validate the modelling results. Shape and scale parameters of the Weibull models were estimated by maximising the log‐likelihood function using non‐linear optimisation. Hazard and reliability functions were calculated using the Weibull model. Results using two‐parameter Weibull, Kaplan‐Meier, and log beta‐Weibull models display low reliability and high hazard rate over time, which was associated with spark plug failure due to a suboptimal start and stop operation strategy.

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Section: Kaplan-meier Estimatormentioning

confidence: 99%

Reliability modelling with redundancy—A case study of power generation engines in a wastewater treatment plant

Jolfaei

Jin

Linden

et al. 2019

Quality & Reliability Eng

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“…The results of comparing the formulas in both methodologies are listed in Tables and . It is noticed that the proposed methodology outperforms the methodology proposed in …”

Section: Application To Nasa Prognostic Turbofan Engine Datasetmentioning

confidence: 99%

“…A powerful pattern‐based machine learning approach called logical analysis of data (LAD) was applied to CBM diagnostics in . From the perspective of the CBM decision makers, LAD is used as a supervised learning technique to automatically generate, from condition monitoring data, interpretable patterns and translate them into diagnostic rules, without any statistical treatments or assumptions, even if the data are highly correlated or time varying . Moreover, LAD can deal effectively with noisy or missing data, as reported in …”

Section: Introductionmentioning

confidence: 99%

“…The LAD prognostic methodology proposed in considers only the condition monitoring data that are collected at/or immediately before the system failure. This means that all the bulk of information embedded in system's historical observations are ignored.…”

Section: Introductionmentioning

confidence: 99%

“…11 From the perspective of the CBM decision makers, LAD is used as a supervised learning technique to automatically generate, from condition monitoring data, interpretable patterns and translate them into diagnostic rules, without any statistical treatments or assumptions, even if the data are highly correlated or time varying. 12,13 Moreover, LAD can deal effectively with noisy or missing data, as reported in. 14,15 From the reliability analysis perspective, Kaplan-Meier (KM) is commonly applied as a non-parametric technique to provide an estimate for the survival function, based on the historical lifetime data collected from a set of systems.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Pattern‐based prognostic methodology for condition‐based maintenance using selected and weighted survival curves

Ragab

Yacout

Ouali

et al. 2017

Quality & Reliability Eng

Self Cite

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This paper proposes a pattern‐based prognostic methodology that combines logical analysis of data (LAD) as an event‐driven diagnostic technique, and Kaplan–Meier (KM) estimator as a time‐driven technique. LAD captures the effect of the instantaneous conditions on the health state of a monitored system, while KM estimates the baseline reliability curve that reflects the effect of aging, based on the observed historical failure times. LAD is used to generate a set of patterns from the observed values of covariates that represent the operating conditions and condition indicators. A pattern selection procedure is carried out to select the set of significant patterns from all the generated patterns. A survival curve is estimated, for each subset of observations covered by each selected pattern. A weight that reflects the coverage of each pattern is assigned to its survival curve. Given a recently collected observation, the survival curve of a monitored system is updated on the basis of the patterns covering that observation. The updated curve is then used to predict the remaining useful life of the monitored system. The proposed methodology is validated using a common dataset in prognostics: the turbofan degradation dataset that is available at NASA prognostic repository. Copyright © 2017 John Wiley & Sons, Ltd.

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Operability Forecasting Combining Neural Network and Survival Analysis with an Application to Hot Corrosion in Turbofan

Langhendries

Lacaille

2023

Lecture Notes in Mechanical Engineering

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Remaining useful life prediction using prognostic methodology based on logical analysis of data and Kaplan–Meier estimation

Cited by 46 publications

References 29 publications

Reliability modelling with redundancy—A case study of power generation engines in a wastewater treatment plant

Reliability modelling with redundancy—A case study of power generation engines in a wastewater treatment plant

Pattern‐based prognostic methodology for condition‐based maintenance using selected and weighted survival curves

Operability Forecasting Combining Neural Network and Survival Analysis with an Application to Hot Corrosion in Turbofan

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