Modeling multivariate degradation processes with time‐variant covariates and imperfect maintenance effects
Published 2020 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
Modeling multivariate degradation processes with time‐variant covariates and imperfect maintenance effects
Authors
Keywords
-
Journal
APPLIED STOCHASTIC MODELS IN BUSINESS AND INDUSTRY
Volume -, Issue -, Pages -
Publisher
Wiley
Online
2020-12-11
DOI
10.1002/asmb.2600
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- Life cycle cost analysis considering multiple dependent degradation processes and environmental influence
- (2020) Bin Liu et al. RELIABILITY ENGINEERING & SYSTEM SAFETY
- Virtual age, is it real? ‐ Discussing virtual age in reliability context
- (2020) Maxim Finkelstein et al. APPLIED STOCHASTIC MODELS IN BUSINESS AND INDUSTRY
- Semiparametric and nonparametric evaluation of first-passage distribution of bivariate degradation processes
- (2020) Lochana K. Palayangoda et al. RELIABILITY ENGINEERING & SYSTEM SAFETY
- Imperfect repair in degradation processes: A Kijima-type approach
- (2019) Waltraud Kahle APPLIED STOCHASTIC MODELS IN BUSINESS AND INDUSTRY
- Planning Accelerated Reliability Tests for Mission-Oriented Systems Subject to Degradation and Shocks
- (2019) Xiujie Zhao et al. IISE Transactions
- Maintenance policy for a system with a weighted linear combination of degradation processes
- (2019) Shaomin Wu et al. EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
- A review on maintenance optimization
- (2019) Bram de Jonge et al. EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
- Statistical Modeling of Multivariate Destructive Degradation Tests with Blocking
- (2019) Qiuzhuang Sun et al. TECHNOMETRICS
- Managing Component Degradation in Series Systems for Balancing Degradation Through Reallocation and Maintenance
- (2019) Qiuzhuang Sun et al. IISE Transactions
- Reliability and availability analysis of stochastic degradation systems based on bivariate Wiener processes
- (2019) Qinglai Dong et al. APPLIED MATHEMATICAL MODELLING
- Pairwise model discrimination with applications in lifetime distributions and degradation processes
- (2019) Piao Chen et al. NAVAL RESEARCH LOGISTICS
- Copula-based reliability analysis of degrading systems with dependent failures
- (2019) Guanqi Fang et al. RELIABILITY ENGINEERING & SYSTEM SAFETY
- Semiparametric estimate of the efficiency of imperfect maintenance actions for a gamma deteriorating system
- (2019) Gabriel Salles et al. JOURNAL OF STATISTICAL PLANNING AND INFERENCE
- Bayesian planning of step-stress accelerated degradation tests under various optimality criteria
- (2018) Xiujie Zhao et al. APPLIED STOCHASTIC MODELS IN BUSINESS AND INDUSTRY
- Degradation data analysis and remaining useful life estimation: A review on Wiener-process-based methods
- (2018) Zhengxin Zhang et al. EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
- Stochastic comparisons of imperfect maintenance models for a gamma deteriorating system
- (2018) Sophie MERCIER et al. EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
- On Modeling Bivariate Wiener Degradation Process
- (2018) Ancha Xu et al. IEEE TRANSACTIONS ON RELIABILITY
- Environmental Risk Assessment of Emerging Contaminants Using Degradation Data
- (2018) Lanqing Hong et al. JOURNAL OF AGRICULTURAL BIOLOGICAL AND ENVIRONMENTAL STATISTICS
- Big data and reliability applications: The complexity dimension
- (2018) Yili Hong et al. JOURNAL OF QUALITY TECHNOLOGY
- Reliability analysis considering dynamic material local deformation
- (2018) Wujun Si et al. JOURNAL OF QUALITY TECHNOLOGY
- Optimal Inspection and Replacement Policy Based on Experimental Degradation Data with Covariates
- (2018) Xiujie Zhao et al. IISE Transactions
- Joint Online RUL Prediction for Multi-Deteriorating Systems
- (2018) Weiwen Peng et al. IEEE Transactions on Industrial Informatics
- A review on condition-based maintenance optimization models for stochastically deteriorating system
- (2017) Suzan Alaswad et al. RELIABILITY ENGINEERING & SYSTEM SAFETY
- Bivariate Analysis of Incomplete Degradation Observations Based on Inverse Gaussian Processes and Copulas
- (2016) Weiwen Peng et al. IEEE TRANSACTIONS ON RELIABILITY
- An optimal replacement policy for complex multi-component systems
- (2016) R. Ahmadi INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
- Reliability of complex systems under dynamic conditions: A Bayesian multivariate degradation perspective
- (2016) Weiwen Peng et al. RELIABILITY ENGINEERING & SYSTEM SAFETY
- A condition-based maintenance policy for multi-component systems with Lévy copulas dependence
- (2016) Heping Li et al. RELIABILITY ENGINEERING & SYSTEM SAFETY
- Nonlinear general path models for degradation data with dynamic covariates
- (2015) Zhibing Xu et al. APPLIED STOCHASTIC MODELS IN BUSINESS AND INDUSTRY
- Degradation-based maintenance decision using stochastic filtering for systems under imperfect maintenance
- (2015) Mimi Zhang et al. EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
- Statistical Methods for Degradation Data With Dynamic Covariates Information and an Application to Outdoor Weathering Data
- (2015) Yili Hong et al. TECHNOMETRICS
- Stochastic modelling and analysis of degradation for highly reliable products
- (2014) Zhi-Sheng Ye et al. APPLIED STOCHASTIC MODELS IN BUSINESS AND INDUSTRY
- On the Modelling of Imperfect Repairs for a Continuously Monitored Gamma Wear Process Through Age Reduction
- (2014) Sophie Mercier et al. JOURNAL OF APPLIED PROBABILITY
- Optimal Design for Step-Stress Accelerated Degradation Test with Multiple Performance Characteristics Based on Gamma Processes
- (2013) Zhengqiang Pan et al. COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION
- Criticality measures for components with multi-dimensional degradation
- (2013) Xiao Liu et al. IIE TRANSACTIONS
- Residual life estimation based on bivariate non-stationary gamma degradation process
- (2013) Xiaolin Wang et al. JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION
- Reliability Meets Big Data: Opportunities and Challenges
- (2013) William Q. Meeker et al. Quality Engineering
- A preventive maintenance policy for a continuously monitored system with correlated wear indicators
- (2012) Sophie Mercier et al. EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
- Residual life estimation based on bivariate Wiener degradation process with time-scale transformations
- (2012) Xiaolin Wang et al. JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION
- Bivariate degradation analysis of products based on Wiener processes and copulas
- (2012) Zhengqiang Pan et al. JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION
- Reliability modeling of degradation of products with multiple performance characteristics based on gamma processes
- (2011) Zhengqiang Pan et al. RELIABILITY ENGINEERING & SYSTEM SAFETY
- Bivariate Gamma wear processes for track geometry modelling, with application to intervention scheduling
- (2011) Sophie Mercier et al. Structure and Infrastructure Engineering
- Progressive-Stress Accelerated Degradation Test for Highly-Reliable Products
- (2010) Chien-Yu Peng et al. IEEE TRANSACTIONS ON RELIABILITY
- Linear and Nonlinear Preventive Maintenance Models
- (2010) Shaomin Wu et al. IEEE TRANSACTIONS ON RELIABILITY
- Optimal design of accelerated degradation tests based on Wiener process models
- (2010) Heonsang Lim et al. JOURNAL OF APPLIED STATISTICS
- Bivariate constant stress degradation model: LED lighting system reliability estimation with two-stage modelling
- (2009) J. K. Sari et al. QUALITY AND RELIABILITY ENGINEERING INTERNATIONAL
- A survey of the application of gamma processes in maintenance
- (2007) J.M. van Noortwijk RELIABILITY ENGINEERING & SYSTEM SAFETY
- Optimal non-periodic inspection for a multivariate degradation model
- (2007) C.T. Barker et al. RELIABILITY ENGINEERING & SYSTEM SAFETY
Find Funding. Review Successful Grants.
Explore over 25,000 new funding opportunities and over 6,000,000 successful grants.
ExploreAsk a Question. Answer a Question.
Quickly pose questions to the entire community. Debate answers and get clarity on the most important issues facing researchers.
Get Started