Article
Engineering, Multidisciplinary
Shengjin Tang, Fengfei Wang, Xiaoyan Sun, Xiaodong Xu, Chuanqiang Yu, Xiaosheng Si
Summary: This paper proposes an unbiased parameters estimation method and analyzes the impact of model mis-specification in Wiener process-based degradation models with random effects. Experimental results demonstrate that the proposed method is superior to other estimation methods and suggest considering random effects in the modeling.
APPLIED MATHEMATICAL MODELLING
(2022)
Article
Engineering, Multidisciplinary
Mitra Fouladirad, Massimiliano Giorgio, Gianpaolo Pulcini
Summary: Most stochastic models used to describe the evolution of technological unit degradation assume unlimited increase in degradation level. However, in reality, degradation phenomena are typically bounded. This paper investigates the potential of a new bounded degradation model to accurately describe and predict the future evolution of bounded degradation phenomena.
QUALITY AND RELIABILITY ENGINEERING INTERNATIONAL
(2023)
Article
Engineering, Industrial
Wennian Yu, Wenbing Tu, Il Yong Kim, Chris Mechefske
Summary: This study proposes a new method for estimating the RUL of degrading systems by constructing a nonlinear-drift-driven Wiener process model considering three common sources of uncertainty. The results demonstrate the importance of including nonlinear degradation characteristics and uncertainty factors in RUL estimation, especially for the offline estimation scenario.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2021)
Article
Engineering, Industrial
Kai Song, Lirong Cui
Summary: Due to the complexity and multi-functionality of modern products, there are usually multiple performance characteristics that can reflect the degradation states. This paper proposes a gamma process based degradation model for analyzing bivariate dependent degradation data. The model captures the dependency between the two degradation processes using a common random effect. A real-time prediction method for the remaining useful life of the product is also proposed using Bayesian method.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2022)
Article
Mathematics, Applied
Fiaz Ahmad Bhatti, G. G. Hamedani, Mashail M. Al Sobhi, Mustafa C. Korkmaz
Summary: The BXII-PC distribution is a four-parameter lifetime model with flexible hazard rate, featuring flexible failure rate and density function shapes. Various mathematical properties and six estimation methods have been established, with simulation studies and real data application confirming the model's potential.
Article
Computer Science, Hardware & Architecture
Cheng-Hsun Wu, Tzong-Ru Tsai, Ming-Yung Lee
Summary: This article introduces a two-stage maximum likelihood estimation (TSML) process for a time-transformed model, demonstrating its consistency, asymptotic normality, and ease of use for reliability engineers. Additionally, TSML estimators can provide valuable information about unknown accelerated relationship laws.
IEEE TRANSACTIONS ON RELIABILITY
(2021)
Article
Computer Science, Hardware & Architecture
Zhijie Wang, Qingqing Zhai, Lijuan Shen
Summary: This paper investigates the degradation rate of degrading products operating under dynamic environments. Instead of using a random walk to model the time-varying degradation rate, the authors propose using an autoregressive model to accommodate the randomness and stationarity of the environmental effects. A Wiener process is used to model the degradation process, and an Expectation-Maximization algorithm is developed for parameter estimation. The explicit probability density function for the remaining useful life is derived for remaining useful life prediction.
IEEE TRANSACTIONS ON RELIABILITY
(2023)
Article
Engineering, Multidisciplinary
Tianyang Pang, Tianxiang Yu, Bifeng Song
Summary: Remaining useful life (RUL) is crucial for prediction and health management. Due to unit-to-unit heterogeneity in degradation, precise degradation trajectories of individual bivariate systems are difficult to obtain. To predict the RUL of an individual system, a parameter in the nonlinear transformation path of the degradation model is proposed as an indicator to capture the heterogeneity of the degradation process, enabling accurate degradation prediction. Additionally, a prediction method based on this improved degradation model, using an improved parameter updating approach based on the Bayesian approach, is developed for RUL estimation of degrading systems. The proposed method is validated and compared with the conventional method using GaAs lasers dataset and practical degrading system case data, demonstrating superior prediction accuracy.
Article
Statistics & Probability
Xiaoping Liu, Bin Guo, Lijian Xia, Xiao Tian, Lijie Zhang
Summary: A multi-objective optimization method for accelerated degradation test based on Wiener process is proposed in this article to solve the difficulty or even conflicting test configurations caused by different optimization objective functions. By establishing an accelerated degradation model and using a multi-objective optimization model, the test configurations for multi-objectives can be obtained.
COMMUNICATIONS IN STATISTICS-THEORY AND METHODS
(2022)
Article
Engineering, Industrial
Shuyi Zhang, Qingqing Zhai, Yaqiu Li
Summary: This study incorporates both measurable covariates and unobservable factors into degradation modeling using the Wiener process. The impacts of the covariates and unobservable factors on degradation rate are accounted for. Maximum likelihood estimation and simulation-based algorithm are used for remaining useful life prediction. The proposed model is validated through simulation study and applied to battery degradation and outdoor coating weathering datasets.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2023)
Article
Mathematical & Computational Biology
Hans-Peter Piepho, Johannes Forkman, Waqas Ahmed Malik
Summary: The paper discusses the importance of checking inconsistency between direct and indirect evidence in network meta-analysis and proposes an evidence-splitting model. The author introduces a new method based on residual maximum likelihood to address the bias in parameter estimation. Simulation results show the competitive performance of this method in terms of bias and mean squared error. The limitations of the evidence-splitting model are also discussed.
RESEARCH SYNTHESIS METHODS
(2023)
Article
Engineering, Mechanical
Zhijian Wang, Yuntian Ta, Wenan Cai, Yanfeng Li
Summary: This paper proposes a two-stage remaining useful life prediction model based on the degradation angle (DA), which accurately identifies the change point between stages and matches different degradation states using different drift functions, leading to improved prediction accuracy.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2023)
Article
Engineering, Industrial
Yu Wang, Qiufa Liu, Wenjian Lu, Yizhen Peng
Summary: The study of the remaining useful life (RUL) has gained momentum in recent years for ensuring system availability. The proposed general time-varying Wiener process (GTWP) considers the dynamic and multi-source variability of a degradation process jointly. A state-space model is constructed to depict the evolution of model parameters over time, and an approximate analytical form for the estimated RUL is derived under the concept of the first hitting time (FHT). The results from simulation cases and real-world data demonstrate the generalizability, accuracy, and faster convergence of the proposed model compared to existing homogeneous models.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2023)
Article
Computer Science, Interdisciplinary Applications
Haizhen Zhu, Xueqi Wang, Mingqing Xiao, Zhao Yang, Xilang Tang, Bincheng Wen
Summary: This paper develops a novel reliability model considering storage and working degradation, categorizing IWS into scheduled and random based on predetermined or random duration times. The randomness in duration times of each state period and the accumulative duration time of each state are analyzed and considered, with the effectiveness of the model illustrated through analytical and Monte Carlo simulation results.
COMPUTERS & INDUSTRIAL ENGINEERING
(2021)
Article
Mathematics
Tzong-Ru Tsai, Yuhlong Lio, Jyun-You Chiang, Yi-Jia Huang
Summary: A new life performance index is proposed for evaluating the quality of lifetime products. The study utilizes maximum likelihood estimation and Bayesian methods to infer the parameters of the Weibull distribution and the new life performance index. Results show that the Bayesian approaches outperform the maximum likelihood estimation method in terms of relative bias, relative mean square error, and coverage probability for estimators.
Article
Engineering, Industrial
Mateusz Oszczypala, Jakub Konwerski, Jaroslaw Ziolkowski, Jerzy Malachowski
Summary: This article discusses the issues related to the redundancy of k-out-of-n structures and proposes a probabilistic and simulation-based optimization method. The method was applied to real transport systems, demonstrating its effectiveness in reducing costs and improving system availability and performance.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2024)
Article
Engineering, Industrial
Wencheng Huang, Haoran Li, Yanhui Yin, Zhi Zhang, Anhao Xie, Yin Zhang, Guo Cheng
Summary: Inspired by the theory of degree entropy, this study proposes a new node identification approach called Adjacency Information Entropy (AIE) to identify the importance of nodes in urban rail transit networks (URTN). Through numerical and real-world case studies, it is found that AIE can effectively identify important nodes and facilitate connections among non-adjacent nodes.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2024)
Article
Engineering, Industrial
Hongyan Dui, Yaohui Lu, Liwei Chen
Summary: This paper discusses the four phases of the system life cycle and the different costs associated with each phase. It proposes an improvement importance method to optimize system reliability and analyzes the process of failure risk under limited resources.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2024)
Article
Engineering, Industrial
Xian Zhao, Chen Wang, Siqi Wang
Summary: This paper proposes a new rebalancing strategy for balanced systems by switching standby components. Different switching rules are provided based on different balance conditions. The system reliability is derived using the finite Markov chain imbedding approach, and numerical examples and sensitivity analysis are presented for validation.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2024)
Article
Engineering, Industrial
Fengyuan Jiang, Sheng Dong
Summary: Corrosion defects are the primary causes of pipeline burst failures. The traditional methodologies ignore the effects of random morphologies on failure behaviors, leading to deviations in remaining strength estimation and reliability analysis. To address this issue, an integrated methodology combining random field, non-linear finite element analysis, and Monte-Carlo Simulation was developed to describe the failure behaviors of pipelines with random defects.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2024)
Article
Engineering, Industrial
Guoqing Cheng, Jiayi Shen, Fang Wang, Ling Li, Nan Yang
Summary: This paper investigates the optimal joint inspection and mission abort policies for a multi-component system with failure interaction. The proportional hazards model is used to characterize the effect of one component's deterioration on other components' hazard rates. The optimal policy is studied to minimize the expected total cost, and some structural properties of the optimal policy are obtained.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2024)
Article
Engineering, Industrial
Hongyan Dui, Yaohui Lu, Shaomin Wu
Summary: A new resilience model is proposed in this paper for systems under competing risks, and related indices are introduced for evaluating the system's resilience. The model takes into account the degradation process, external shocks, and maintenance interactions of the system, and its effectiveness is demonstrated through a case study.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2024)
Article
Engineering, Industrial
Yang Li, Jun Xu
Summary: This paper proposes a translation model based on neural network for simulating non-Gaussian stochastic processes. By converting the target non-Gaussian power spectrum to the underlying Gaussian power spectrum, non-Gaussian samples can be generated.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2024)
Article
Engineering, Industrial
Yanyan Liu, Keping Li, Dongyang Yan
Summary: This paper proposes a new random walk method, CBDRWR, to analyze the potential risk of railway accidents. By combining accident causation network, we assign different restart probabilities to each node and improve the transition probabilities. In the case study, the proposed method effectively quantifies the potential risk and identifies key risk sources.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2024)
Article
Engineering, Industrial
Nan Hai, Daqing Gong, Zixuan Dai
Summary: The current risk management of utility tunnel operation and maintenance is of low quality and efficiency. This study proposes a theoretical model and platform that offer effective decision support and improve the safety of utility tunnel operation and maintenance.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2024)
Article
Engineering, Industrial
Tomoaki Nishino, Takuya Miyashita, Nobuhito Mori
Summary: A novel modeling methodology is proposed to simulate cascading disasters triggered by tsunamis considering uncertainties. The methodology focuses on tsunami-triggered oil spills and subsequent fires and quantitatively measures the fire hazard. It can help assess and improve risk reduction plans.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2024)
Article
Engineering, Industrial
Mingjiang Xie, Yifei Wang, Jianli Zhao, Xianjun Pei, Tairui Zhang
Summary: This study investigates the effect of rockfall impact on the health management of pipelines with fatigue cracks and proposes a crack propagation prediction algorithm based on rockfall impact. Dynamic SIF values are obtained through finite element modeling and a method combining multilayer perceptron with Paris' law is used for accurate crack growth prediction. The method is valuable for decision making in pipeline reliability assessment and integrity management.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2024)
Article
Engineering, Industrial
Saeed Jamalzadeh, Lily Mettenbrink, Kash Barker, Andres D. Gonzalez, Sridhar Radhakrishnan, Jonas Johansson, Elena Bessarabova
Summary: This study proposes an integrated epidemiological-optimization model to quantify the impacts of weaponized disinformation on transportation infrastructure and supply chains. Results show that disinformation targeted at transportation infrastructure can have wide-ranging impacts across different commodities.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2024)
Article
Engineering, Industrial
Jiaxi Wang
Summary: This paper investigates the depot maintenance packet assignment and crew scheduling problem for high-speed trains. A mixed integer linear programming model is proposed, and computational experiments show the effectiveness and efficiency of the improved model compared to the baseline one.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2024)
Article
Engineering, Industrial
Yuxuan Tian, Xiaoshu Guan, Huabin Sun, Yuequan Bao
Summary: This paper proposes a DFMs searching algorithm based on the graph neural network (GNN) to improve computational efficiency and adaptively identify DFMs. The algorithm terminates prematurely when unable to identify new DFMs.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2024)