Article
Engineering, Industrial
Xian Zhao, Xiaofei Chai, Jinglei Sun, Qingan Qiu
Summary: This paper introduces a joint optimization model that combines component switching and mission abort policies to balance the trade-off between mission success probability and system survivability, minimizing total economic loss. A numerical study on a virtual machine system is conducted to demonstrate the effectiveness of the model.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2021)
Article
Engineering, Industrial
Xian Zhao, Xiaofei Chai, Jinglei Sun, Qingan Qiu
Summary: This paper investigates the optimal mission abort policy for systems executing missions in a random environment combining cumulative shock model and run shock model. Two optimization models are constructed to minimize the expected total cost and maximize the mission success probability while providing a desired system survivability. The advantages of the constructed bivariate mission abort policy are justified through two heuristic abort policies that only consider single abort criterion.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2021)
Article
Computer Science, Interdisciplinary Applications
Siqi Wang, Xian Zhao, Zhigang Tian, Ming J. Zuo
Summary: This article discusses the reliability issues of balanced systems in engineering fields and proposes a novel mission abort policy to adapt to the characteristics of such systems. The policy considers multiple abort criteria, including the maximum component state distance and the number of damaged components.
COMPUTERS & INDUSTRIAL ENGINEERING
(2021)
Article
Engineering, Industrial
Congshan Wu, Xian Zhao, Qingan Qiu, Jinglei Sun
Summary: This paper investigates the optimal mission abort policy for the k-out-of-n: F balanced system performing a specific mission continuously. Probability indexes and optimization models are derived, with a case study provided to demonstrate the results.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2021)
Article
Computer Science, Hardware & Architecture
Guoqing Cheng, Ling Li, Lizhen Zhang, Nan Yang, Bo Jiang, Chunxia Shangguan, Yongzheng Su
Summary: This article investigates the optimal joint inspection and mission abort policies for deteriorating systems which execute a mission continuously. The decision to abort or continue the mission is based on predictive reliability, leading to cost savings. Explicit expressions for mission success probability and system survivability are derived, and the optimal joint policy aims to minimize the expected total cost including mission failure cost, system loss cost, and inspection cost.
IEEE TRANSACTIONS ON RELIABILITY
(2023)
Article
Engineering, Industrial
Gregory Levitin, Maxim Finkelstein, Yanping Xiang
Summary: The paper introduces an optimal mission abort policy that minimizes expected costs due to inspections, mission failure, and system loss. The system operates in a random environment modeled by a renewal process of shocks, where the decision to abort or continue operation depends on experienced shocks and the state of the system revealed only at inspections. The cost minimization problem is formulated with detailed numerical illustrations and discussions.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2021)
Article
Management
Xian Zhao, Jinglei Sun, Qingan Qiu, Ke Chen
Summary: This paper investigates the joint optimization of inspection and condition based mission abort policies for systems subject to continuous degradation to minimize expected costs. Numerical evaluation of heuristic policies for mission reliability and system survivability is presented, and the obtained results are validated through numerical studies.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2021)
Article
Engineering, Industrial
Xian Zhao, Haoran Liu, Yaguang Wu, Qingan Qiu
Summary: This paper focuses on the optimization of condition-based mission abort policies and system structure in a work system with random task arrivals. Different decision criteria are considered and corresponding abort policies are proposed. Mission reliability and system survivability are derived using recursive methods, and the objective is to minimize the expected total cost while balancing mission reliability and system survivability by jointly optimizing the abort policies and system structure.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2023)
Article
Engineering, Industrial
Xian Zhao, Ying Dai, Qingan Qiu, Yaguang Wu
Summary: This paper studies the optimal mission abort and allocation of standby components policies for the k-out-of-(n+m):F system considering partial mission loss. By dynamically controlling the mission abort decision and using a recursive algorithm to calculate mission reliability and system survivability, the paper aims to minimize the expected cost and balance the mission reliability and the system survivability.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2022)
Article
Management
Xian Zhao, Yu Fan, Qingan Qiu, Ke Chen
Summary: This paper investigates condition-based mission abort policies to balance mission reliability and system survivability. Degradation control limit and time threshold are dependent on duration in the normal stage. Structural properties of optimal abort thresholds are explored to minimize costs of mission and system failure.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2021)
Article
Public, Environmental & Occupational Health
Li Yang, Fanping Wei, Qingan Qiu
Summary: Information-driven mission abort is an effective approach to minimize failure risk in safety-critical systems. This study focuses on optimizing the sampling and mission abort decisions for partially observable systems, where system health state is revealed through sampling. Dynamic policies were developed based on belief state optimization models and partial health information, outperforming heuristic abort policies in controlling mission loss.
Article
Engineering, Industrial
Guoqing Cheng, Ling Li, Chunxia Shangguan, Nan Yang, Bo Jiang, Ningrong Tao
Summary: This paper presents a joint optimization approach for inspection and condition-based mission abort policy in a partially observable safety-critical system. A hidden continuous-time Markov process is used to model the system deterioration, and the condition monitoring can only provide partial information about the system's hidden state. The joint inspection and mission abort policy is developed by employing a multi-variate Bayesian control approach. The posterior probability of the system being in the warning state is updated at each inspection using Bayes' rule. The mission is aborted and the rescue procedure is initiated when the posterior probability exceeds the control limit. The problem is formulated and solved within the framework of Markov decision process, aiming to minimize the expected total cost including inspection, mission failure, and system failure cost. The paper also presents some structural properties of the control limit and provides numerical examples to demonstrate the proposed model's effectiveness.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2023)
Article
Engineering, Industrial
Gregory Levitin, Maxim Finkelstein, Yanping Xiang
Summary: The paper explores the possibility of multiple attempts for multistate systems, focusing on maximizing mission completion probability by repairing systems to 'as good as new' state after each rescue. The study finds that missions are aborted when the number of experienced shocks exceeds a predetermined threshold, and the number of attempts should be determined to maximize the success probability.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2021)
Article
Public, Environmental & Occupational Health
Xian Zhao, Xiaofei Chai, Jinglei Sun, Qingan Qiu
Summary: This article proposes a condition-based mission abort policy for safety-critical systems. The policy terminates a mission and initiates a rescue procedure immediately if the system state is worse than a control limit. The article evaluates mission reliability and system survivability to analyze the risk of mission failure and system failure. It also explores the optimal mission abort threshold and the joint optimization of mission abort and protective device selection policies.
Article
Computer Science, Hardware & Architecture
Qingan Qiu, Lisa M. Maillart, Oleg A. Prokopyev, Lirong Cui
Summary: This study investigates the mission abort policies of safety-critical mission-based systems, such as aircraft and submarines, to enhance their survivability. The mission abort decisions are considered in a two-stage degradation process, aiming to minimize the expected total cost of mission failure and system failure. The study also evaluates heuristic policies and formulates a joint optimization problem to determine the optimal mission abort policy and investment for delaying system deterioration.
IEEE TRANSACTIONS ON RELIABILITY
(2023)
Article
Engineering, Industrial
Hongyan Dui, Xuan Wei, Liudong Xing, Liwei Chen
Summary: This paper proposes a maintenance metric for improving the performance of an irrigation network and develops an optimum maintenance efficiency model. A case study of an irrigation network with 27 nodes is used to verify the practicality and effectiveness of the proposed method.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2023)
Article
Engineering, Industrial
Gregory Levitin, Liudong Xing, Yuanshun Dai
Summary: This study addresses the optimal standby mode transfer problem considering resource-constrained system elements. A new event transition-based algorithm is proposed to evaluate the expected mission downtime (EMD) of the considered standby system subject to mode transfers. Experimental results show that the EMD decreases with the increase of initial available resource, while it increases with the increase of resource consumption or stress level during mode transfers.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2023)
Article
Engineering, Industrial
Gregory Levitin, Liudong Xing, Yuanshun Dai
Summary: Motivated by real-world applications, this paper presents a model for a heterogeneous standby system with n components, which can be allocated to different positions and are subject to random shocks. The system's mission success probability depends on the allocation and activation sequence of components. The paper proposes a joint optimal allocation and activation sequence (AAS) problem and presents a new numerical algorithm and genetic algorithm for solving it. A case study of a multi-UAV standby system is provided to illustrate the proposed model and evaluate its solutions.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2023)
Article
Chemistry, Multidisciplinary
Chencheng Zhou, Liudong Xing, Qisi Liu, Honggang Wang
Summary: Selfish mining is a malicious attack in the blockchain-based bitcoin system, in which attackers collect unfair rewards by withholding blocks. Previous research on selfish mining mainly focused on cryptography design and detection of malicious behavior using different approaches. This paper proposes two network-wide defensive strategies, DDAA and ALP, aimed at disincentivizing selfish miners and increasing the system's resilience. A continuous-time Markov chain model is used to quantify the improvement in bitcoin dependability, and statistical analysis evaluates the feasibility of the proposed strategies. The DDAA method is found to be the most effective in improving bitcoin's dependability compared to an existing timestamp-based defense strategy.
APPLIED SCIENCES-BASEL
(2023)
Article
Computer Science, Information Systems
Liudong Xing, Barry W. Johnson
Summary: With the rapid development of the Internet of Things (IoT), unmanned aerial vehicles (UAVs) are playing an increasingly important role in military and civil applications. This article reviews the reliability literature of UAVs, highlighting failure causes and challenges, as well as discussing modeling, analysis, and design methods for UAV systems and subsystems. It also presents open research problems and opportunities for designing reliable and resilient UAVs and UAV-assisted IoT systems.
IEEE INTERNET OF THINGS JOURNAL
(2023)
Article
Engineering, Multidisciplinary
Guixiang Lv, Liudong Xing, Honggang Wang, Hong Liu
Summary: This paper improves the reliability of storage area networks (SANs) by implementing node degree-based load redistribution strategies to mitigate or prevent cascading failures triggered by data overloading.
INTERNATIONAL JOURNAL OF MATHEMATICAL ENGINEERING AND MANAGEMENT SCIENCES
(2023)
Article
Engineering, Multidisciplinary
Chaonan Wang, Yingxi Lie, Liudong Xing, Quanlong Guan, Chunhui Yang, Min Yu
Summary: This paper studies common cause failures that can significantly affect the reliability of a system. It proposes a model for analyzing probabilistic common cause failures, where a common cause can lead to multiple system component failures with different probabilities, and some failures can occur in a cascading manner. The model uses a directed acyclic graph structure to capture complex cascading effects, and an explicit analytical method is proposed for reliability analysis. The method is not limited to specific component time-to-failure distributions. The application and advantages of the proposed method are demonstrated through a detailed case study of a safety instrumented system for oil and gas transportation. The correctness of the method is verified using Monte Carlo simulations, and the time and space complexity of the method are also studied.
QUALITY AND RELIABILITY ENGINEERING INTERNATIONAL
(2023)
Article
Engineering, Industrial
Gregory Levitin, Liudong Xing, Yuanshun Dai
Summary: This paper models and optimizes the uploading and downloading pace distribution in a production-dual storage system to meet a specified demand during a mission time. The storage units' paces greatly affect failure probabilities and the mission success probability. A probabilistic approach is used to evaluate the mission success probability, and the optimal pace distribution is determined to maximize it. Case studies are conducted to illustrate the proposed model and solutions, along with investigations on the impacts of system parameters on the mission success probability and optimization solutions.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2023)
Article
Engineering, Industrial
Chaonan Wang, Liudong Xing, Yujie Su, Quanlong Guan, Bo Tang, Yuliang Hu
Summary: This paper proposes an analytical modeling method based on multi-valued decision diagrams (MDD) for efficient reliability analysis of dynamic voting phased mission systems (VPMS). The suggested approach takes into consideration the changing system configurations, phase-dependent failure behavior, and statistical dependencies across phases. It offers a fast MDD generation algorithm and can be applied to systems with heterogeneous components. Examples demonstrate the applications and advantages of this approach.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2023)
Article
Engineering, Industrial
Hongyan Dui, Yaohui Lu, Zhanfei Gao, Liudong Xing
Summary: In this paper, a new model is developed to study the interaction between damage and maintenance in multi-state systems exposed to multiple shocks. The model measures the system's performance efficiency and budget surplus rate, which reflect the ability to recover from shocks and respond to losses. Markov processes are used to analyze the state transition process, and a case study of a nuclear power plant is conducted to demonstrate the proposed methods. Sensitivity analysis is also performed to evaluate the shock resistance and maintenance capability of the system.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2023)
Article
Engineering, Industrial
Hongyan Dui, Xuan Wei, Liudong Xing
Summary: In many practical situations, the traditional single-criterion importance measures are no longer sufficient. This paper proposes a new multi-criteria importance measure that considers the correlation among different criteria. The proposed measure accurately identifies the weakest components in complex engineering systems.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2023)
Article
Automation & Control Systems
Heping Jia, Liudong Xing, Yi Ding, Yanbin Li, Dunnan Liu
Summary: Considerable research efforts have been devoted to modeling load-sharing systems, but existing models have limitations in terms of time-to-failure distribution, component performances, and performance constraints. This article proposes a model for a dynamic load-sharing system (DLSS) that considers the dynamic performance of each component based on load-sharing principles and capacity constraints. The proposed model also considers increasing failure rates and the effects of component degradation. An extended Markov process (EMP) method is introduced for evaluating the reliability of the DLSS with nonrepairable components, which is flexible in handling different component time-to-failure distributions and load allocation mechanisms. Numerical studies and case studies are provided to validate the proposed method and investigate the effects of model parameters.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2023)
Article
Engineering, Industrial
Gregory Levitin, Liudong Xing, Yuanshun Dai
Summary: This paper focuses on modeling and optimizing the aborting policy for a system that needs to complete multiple distinct tasks within a specific mission time. The aborting policy for each task and the execution sequence of multiple tasks greatly impact the mission performance. The proposed model can minimize mission losses using a genetic algorithm.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2024)
Article
Engineering, Industrial
Chaonan Wang, Xiaolei Wang, Liudong Xing, Quanlong Guan, Chunhui Yang, Min Yu
Summary: In this paper, efficient complete and partial approximation methods based on the central limit theorem are proposed for reliability analysis of heterogeneous k-out-of-n cold standby systems. Case studies and empirical studies demonstrate the efficiency and accuracy of the proposed methods, as well as the influence of system parameters and component time-to-failure distribution. Practice guidelines are provided, and the proposed approximation methods are generalized by considering imperfect switchover.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2023)
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)
