A new class of Wiener process models for degradation analysis

Ye, Zhi‐Sheng; Chen, Nan; Shen, Yan

doi:10.1016/j.ress.2015.02.005

Cited by 212 publications

(75 citation statements)

References 34 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Random effects are an important aspect to consider in the degradation modeling of almost any product under study, given that most of the time there is a substantial subject-to-subject variability among the degradation processes of different individuals [33]. Which, accounts to describe the individual variability that determines the heterogeneity among the degradation paths of different product units, also known as individual variability [35].…”

Section: Science and Technologymentioning

confidence: 99%

Reliability assessment for systems with two performance characteristics based on gamma processes with marginal heterogeneous random eﬀects

Rodríguez‐Picón¹

2016

EiN

View full text Add to dashboard Cite

Article citation info: IntroductionIn recent years, important developments have been presented in the area of reliability inference of products and systems based on degradation models. Such models are important tools to obtain reliability information when few failure data is available [11], and consists in analyzing the gradual deterioration in performance of a performance characteristic (PC), also known as degradation process, in terms of the accumulated damage over time [27]. For some products, a failure would be defined at a specified critical level of degradation, which means that the product may not stop working completely as in the case of hard failures, but be defined when the cumulative degradation path crosses the critical level of degradation; such failures are known as soft failures. In general, if a failure can be defined in terms of a specified critical level of degradation it is possible to obtain a reliability assessment based on degradation process models [12]. Based on this, a modeling approach for degradation processes may consist in relating the degradation over time with a continuous stochastic process such that it is possible to describe the failure generating mechanisms.For certain PC, the desirable properties that a model must have to describe its degradation process are that the degradation process should always be positive and strictly increasing. In this paper, the gamma process is considered as a model to govern the degradation process of certain PC, given the characteristics that its increments are independent and non-negative having a gamma distribution that results in an always positive, strictly increasing stochastic process. As performance can only decrease over time, this is why it is considered to be suitable to model wear, crack growth, corrosion, consumption, fatigue, erosion, or any PC [16]. Some important applications of the gamma process in the reliability assessment of products can be found in Bagdonavicius and Nikulin [2], Park and Padgett [22], and Bagdonavicius and Nikulin [3].RodRíguez-Picón LA. Reliability assessment for systems with two performance characteristics based on gamma processes with marginal heterogeneous random effects. eksploatacja i niezawodnosc -Maintenance and Reliability 2017; 19 (1)

show abstract

Section: Science and Technologymentioning

confidence: 99%

Reliability assessment for systems with two performance characteristics based on gamma processes with marginal heterogeneous random eﬀects

Rodríguez‐Picón¹

2016

EiN

View full text Add to dashboard Cite

show abstract

“…Such models concentrate on the impact of external shocks on the increment of degradation amounts. Common stochastic processes describing degradation behaviors include gamma process, Wiener process, general path model, and inverse Gaussian process, eg, and arrival processes of random shocks are generally modeled by Poisson process, eg, In this regard, Song et al considered reliability analysis of multiple‐component series systems subject to internal degradation and external shocks with dependent shock effects; Liu et al studied the condition‐based maintenance for continuously monitored degrading systems operating in dynamic environment; Rafiee et al investigated the reliability analysis and condition‐based maintenance for failure processes with degradation‐dependent hard failure threshold.…”

Section: Introductionmentioning

confidence: 99%

Preventive maintenance policy of single‐unit systems based on shot‐noise process

Qiu

Cui

Dong

2018

Quality & Reliability Eng

View full text Add to dashboard Cite

This paper develops reliability and maintenance models for a single‐unit system subject to hard failures under random environment of external shocks. Motivated by the observations of shot‐noise process in practice, the impact of shock damage on system failure behavior is characterized by random hazard rate increments. To remove such negative impact, imperfect preventive repair is performed periodically, and preventive replacement is performed after several repairs. Considering the joint effects of both random shocks and imperfect repair on the system hazard rate, we derive recursive equations for the system reliability function. Furthermore, we investigate the optimal maintenance policy that minimizes the expected cost per unit time of the system. The applicability of the reliability and maintenance model is validated by a case study on a wind turbine system.

show abstract

“…This kind of model cannot properly capture the unit-tounit variation and temporal uncertainty. Therefore, stochastic process models show significant advantages from this viewpoint, where Wiener process, [11][12][13][14][15][16] Gamma process, [17][18][19][20] and inverse Gaussian process [21][22][23][24][25][26] are most popular ones. Among them, Wiener process has been widely adopted for numerous circumstances, such as the capacity loss of lithium-ion batteries, 27,28 the stress relaxation of electronic products, 29 as well as the parameter drift of gyros 30 and so on.…”

Section: Introductionmentioning

confidence: 99%

A novel pseudo‐maximum likelihood estimation method for accelerated degradation tests under Wiener process

Wang

Zhao

et al. 2018

Quality & Reliability Eng

View full text Add to dashboard Cite

For reliability assessment based on accelerated degradation tests (ADTs), an appropriate parameter estimation method is very important because it affects the extrapolation and prediction accuracy. The well‐adopted maximum likelihood estimation (MLE) method focuses on interpolation fitting and obtains results via maximizing the likelihood of the observations. However, a best interpolation fitting does not necessarily yield a best extrapolation. In this paper, therefore, a pseudo‐MLE (P‐MLE) method is proposed to improve the prediction accuracy of constant‐stress ADTs by considering the degradation mechanism equivalence under Wiener process. In particular, the degradation mechanism equivalence is characterized by a mechanism equivalence factor which presents the proportional relationship between degradation rate and variation. Then, the mechanism equivalence factor is determined via a two‐step method. The other model parameters can be estimated by the general MLE method. The asymptotic variances of acceleration factors and the p‐quantile of product failure time under normal condition are adopted to compare the statistical properties of the proposed method and the general MLE approach. Numerical examples show that the novel P‐MLE method may not achieve a maximum likelihood but can provide more benefits regarding prediction accuracy enhancement especially when the sample size is limited.

show abstract

A new class of Wiener process models for degradation analysis

Cited by 212 publications

References 34 publications

Reliability assessment for systems with two performance characteristics based on gamma processes with marginal heterogeneous random eﬀects

Reliability assessment for systems with two performance characteristics based on gamma processes with marginal heterogeneous random eﬀects

Preventive maintenance policy of single‐unit systems based on shot‐noise process

A novel pseudo‐maximum likelihood estimation method for accelerated degradation tests under Wiener process

Contact Info

Product

Resources

About