Article
Engineering, Industrial
Nan Zhang, Kaiquan Cai, Jun Zhang, Tian Wang
Summary: This study investigates the condition-based maintenance of a two-component system under imperfect inspection. A dual periodical inspection policy is proposed, and an algorithm is developed to achieve maintenance optimization. Numerical examples demonstrate the applicability of the model in providing reference for optimizing maintenance budget decisions.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2022)
Article
Construction & Building Technology
Andre Petersen, Ana Silva, Marco Gonzalez
Summary: Theoretical studies suggest that maintenance improves the state of conservation of buildings and components, increasing their durability and service life. This study proposes a methodology to estimate the impact of imperfect maintenance actions on the degradation condition of painted renderings in external walls, based on an extensive fieldwork survey evaluating the timing and the effect of different maintenance actions on the life cycle of these claddings.
Article
Engineering, Industrial
Fengxia Zhang, Jingyuan Shen, Haitao Liao, Yizhong Ma
Summary: This paper investigates a two-phase imperfect inspection strategy combined with a hybrid preventive maintenance policy for a three-state system, and illustrates the advantages of the method through numerical examples.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2021)
Article
Engineering, Industrial
Weikai Wang, Xian Chen
Summary: In this paper, a condition-based imperfect maintenance model based on piecewise deterministic Markov process (PDMP) is constructed. The degradation of the system includes two types: natural degradation and random shocks. The impulse optimal control theory of PDMP is used to determine the optimal maintenance strategy. A numerical study dealing with component coating maintenance problem is presented, along with sensitivity analyses on the influences of discount factor, observation interval and maintenance cost.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2023)
Article
Computer Science, Interdisciplinary Applications
Yanjing Zhang, Jingyuan Shen, Yizhong Ma
Summary: This paper studies a two-stage system subject to two competing risks, where failures are hidden and can only be detected through periodic inspections. A preventive maintenance policy based on observed system state is proposed to minimize the expected cost rate, by determining the optimal inspection interval. A numerical example is provided to demonstrate the applicability of the method and results.
COMPUTERS & INDUSTRIAL ENGINEERING
(2021)
Article
Engineering, Multidisciplinary
Yifei Wang, Chun Su, Mingjiang Xie
Summary: This study aims to optimize the inspection plan for corroded pipelines by establishing limit state functions, using Monte Carlo simulation and copula functions to evaluate the failure probability, developing a hybrid failure rate model to update the probability, and applying genetic algorithm to optimize the inspection plans.
PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART O-JOURNAL OF RISK AND RELIABILITY
(2022)
Article
Engineering, Multidisciplinary
Qingan Qiu, Baoliang Liu, Cong Lin, Jingjing Wang
Summary: This paper investigates the availability and optimal maintenance policies for systems subject to competing failure modes under continuous and periodic inspections. The models and solutions are proposed, and a numerical example for a Remote Power Feeding System is presented to validate the approach.
PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART O-JOURNAL OF RISK AND RELIABILITY
(2021)
Article
Engineering, Industrial
Jiantai Wang, Shihan Zhou, Rui Peng, Qingan Qiu, Li Yang
Summary: Inspection is essential in asset management to uncover defects and monitor equipment health. However, imperfect inspections due to technical or human errors challenge decision-making optimality. This study investigates an inspection-based replacement strategy for continuous deteriorating systems, accounting for inspection errors. The non-steady evolution trajectory is captured using a piecewise stochastic process, with inspections equally spaced to reveal system state but with a probability of missing defects. Control limits are scheduled to adjust replacement frequencies, and a cost model is optimized. A case study on high-speed train bearings demonstrates the effectiveness of the proposed strategy, reducing costs by 39% and 4% compared to two conventional policies.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2023)
Article
Computer Science, Hardware & Architecture
Jiawen Hu, Qiuzhuang Sun, Zhi-Sheng Ye
Summary: The article proposes a condition-based maintenance policy for systems subject to both degradation-induced soft failure and sudden hard failure, using Wiener process and Weibull model for degradation and baseline hazard rate. The reliability function is derived using Brownian bridge theory. A numerical study is conducted to validate the maintenance policy.
IEEE TRANSACTIONS ON RELIABILITY
(2021)
Article
Engineering, Industrial
Jiantai Wang, Xiaobing Ma, Li Yang, Qingan Qiu, Lijun Shang, Jingjing Wang
Summary: This paper investigates a hybrid inspection-replacement policy for two-stage continuously degrading assets subject to time-state-variant inspection errors. To mitigate loss due to errors, a hybrid replacement planning integrating three types of replacements is scheduled. The long run cost rate is minimized through the joint optimization of the inspection interval, degradation threshold and age limit.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2024)
Article
Engineering, Industrial
Abdessamad Ait El Cadi, Ali Gharbi, Karem Dhouib, Abdelhakim Artiba
Summary: The study presents an efficient stochastic analytical model for integrated production and preventive maintenance control in manufacturing systems. It aims to jointly optimize production and maintenance control settings by minimizing total incurred cost, evaluating model quality, and deriving relevant insights and issues.
JOURNAL OF MANUFACTURING SYSTEMS
(2021)
Article
Computer Science, Information Systems
Xiao Zhao, Jianhua Yang, Yue Qin
Summary: This paper presents an optimal condition-based maintenance strategy for a single-unit system during two-stage failure, with calculations based on renewal reward theory to determine system profit. The optimization of system profit is achieved through a hybrid factor balancing cost and availability, while sensitivity studies on decision objectives are conducted through numerical simulations.
Article
Management
Xiujie Zhao, Bin Liu, Jianyu Xu, Xiao-Lin Wang
Summary: Effective warranty policies benefit both customers and manufacturers, and reliability-oriented degradation analysis has improved the accuracy of lifetime prediction. This paper presents a systematic framework for optimizing imperfect maintenance policies for warranted products. The results show that the randomness in customers' claiming behaviors leads to conservative warranty policies, and variable objective repair levels can reduce maintenance costs.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2023)
Article
Engineering, Multidisciplinary
Lucia Bautista, Inma T. Castro, Christophe Berenguer, Olivier Gaudoin, Laurent Doyen
Summary: This paper proposes a degradation model for a two-unit series system with dependent components and imperfect maintenance. It captures the interdependence between both components using the trivariate reduction method. The paper aims to develop a preventive maintenance strategy for this system and derive the distribution of time to system failure. A cost model for the maintenance strategy is also presented.
PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART O-JOURNAL OF RISK AND RELIABILITY
(2023)
Article
Construction & Building Technology
Xin Chen, Qingsong Zhang, Rentai Liu, Xiaofeng Wang, Wanli He
Summary: Inspection robots are rarely used in metro tunnels due to the unbalanced technical indicators. This study proposes a method to develop a maintenance strategy and assess the life-cycle cost of inspection robots in metro tunnels. It is found that the inspection cycle has a non-linear relationship with the life-cycle cost, and the detection accuracy of the inspection subject is negatively correlated with the cost. An evaluation model is established to guide the intervention indexes of the inspection robot.
TUNNELLING AND UNDERGROUND SPACE TECHNOLOGY
(2023)
Article
Engineering, Industrial
Xiujie Zhao, Zhenglin Liang, Ajith K. Parlikad, Min Xie
Summary: This article proposes a risk evaluation and maintenance strategy optimization method for systems with parallel identical assets using a Bayesian framework. Order statistics are utilized to describe failure times and the incurred performance penalty cost, and a short-term value-based replacement policy is suggested to minimize cost rate. The proposed strategy considers parameter estimator variability and uncertainty of stochastic degradation processes.
Article
Computer Science, Artificial Intelligence
Yiqi Liu, Daoping Huang, Bin Liu, Qiang Feng, Baoping Cai
Summary: This paper introduces a novel ensemble learning algorithm that combines global and local GPR models to accurately predict quality-related variables in industrial processes. An adaptive ranking strategy and variable selection method further enhance the accuracy of predictions.
APPLIED SOFT COMPUTING
(2021)
Article
Engineering, Industrial
Xiaolin Wang, Bin Liu, Xiujie Zhao
Summary: This article examines a performance-based warranty for products with competing hard and soft failures, proposing three compensation policies: free replacement, penalty, and full refund. Numerical studies show that the full refund policy consistently results in the lowest total profit, while the free replacement policy can lead to higher total profit under certain conditions.
INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS
(2021)
Article
Engineering, Civil
Yuan Ren, Xiang Xu, Bin Liu, Qiao Huang
Summary: This paper introduces an age- and condition-based variable weight model (ACVWM) to address the balance problem between indexes within the performance evaluation of bridge systems. The ACVWM is more in line with the real maintenance strategy compared to the constant weight model (CWM) and condition-based variable weight model (CVWM), and its advantage lies in its capability to adjust initial weights over the service age.
KSCE JOURNAL OF CIVIL ENGINEERING
(2021)
Article
Management
Xiujie Zhao, Piao Chen, Shanshan Lv, Zhen He
Summary: This study proposes an optimization method for accelerated reliability testing to predict product return rates within a limited time using experimental means. The heterogeneity in customer usage mode and behavior is considered, and two models of product return are investigated. The study introduces global optimal planning and stress constrained planning as novel test schemes. A real example and simulation study are presented to demonstrate the effectiveness and robustness of the proposed methods.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2023)
Article
Engineering, Industrial
Piao Chen, Kilian Buis, Xiujie Zhao
Summary: This paper develops a comprehensive R package for handling the gamma distribution, covering the state-of-the-art methods of this distribution. The package allows for generating gamma random variables, estimating model parameters, and constructing statistical limits, facilitating practical applications.
JOURNAL OF QUALITY TECHNOLOGY
(2023)
Article
Engineering, Multidisciplinary
Xiang Xu, Michael C. Forde, Yuan Ren, Qiao Huang, Bin Liu
Summary: A multi-index probabilistic anomaly detection approach based on Bayesian estimation and evidential reasoning is proposed to measure uncertainties within anomaly detection and distinguish sensor faults from anomalous events. Energy and probabilistic indexes are defined and extracted from pre-processed measurements, and evidential reasoning is applied to incorporate multiple certainty degrees to differentiate sensor faults and anomalous scenarios.
STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL
(2023)
Article
Engineering, Electrical & Electronic
Hongru Cao, Haidong Shao, Bin Liu, Baoping Cai, Junsheng Cheng
Summary: This paper proposes a clustering-guided novel unsupervised domain adversarial network to address the problem of unsupervised partial transfer fault diagnosis. The network, constructed using domain-specific batch normalization, eliminates domain-specific information and enhances alignment between source and target domains. Additionally, an embedded clustering strategy is designed to learn tightly clustered target-domain features and suppress negative transfer.
IEEE SENSORS JOURNAL
(2022)
Article
Automation & Control Systems
Zhonghao Wang, Zhengguo Xu, Bin Liu, Yun Zhang, Qinmin Yang
Summary: The article proposes a hybrid cleaning scheduling policy for PV systems by combining periodic planning and dynamic adjustment. The strategy aims to optimize system efficiency and reliability through periodic cleaning and fine-tuning adjustments based on meteorological parameters, power generation, and dust deposition forecasts. Additionally, the consideration of forecasting uncertainty and risk preference of decision makers is discussed in the context of scheduling policy.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2022)
Article
Management
Xiujie Zhao, Bin Liu, Jianyu Xu, Xiao-Lin Wang
Summary: Effective warranty policies benefit both customers and manufacturers, and reliability-oriented degradation analysis has improved the accuracy of lifetime prediction. This paper presents a systematic framework for optimizing imperfect maintenance policies for warranted products. The results show that the randomness in customers' claiming behaviors leads to conservative warranty policies, and variable objective repair levels can reduce maintenance costs.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2023)
Article
Computer Science, Hardware & Architecture
Mingzhi Chen, Haidong Shao, Haoxuan Dou, Wei Li, Bin Liu
Summary: This paper proposes an improved local fusion generative adversarial network to address the challenges of dealing with extremely limited training samples and effectively fusing representative and diverse information. The proposed method is applied to the analysis of planetary gearbox vibration signals and the results show that it can generate more similar and diverse samples compared to the existing mainstream GANs using only six training samples in each type, significantly improving the accuracy of fault diagnosis task.
IEEE TRANSACTIONS ON RELIABILITY
(2023)
Article
Engineering, Industrial
Wanqing Cheng, Xiujie Zhao
Summary: Appropriate maintenance policies are crucial for improving system availability and ensuring safe operation. This paper proposes a maintenance optimization method for dependent two-component systems subjected to degradation and imperfect repair. The method considers economic and stochastic dependencies between components and uses a random-effect imperfect repair model to realistically capture the degradation process and maintainability of components. The maintenance problem is modeled using the Markov decision process and the optimal solution is obtained using the value iteration algorithm. Structural insights are obtained using stochastic orders. A numerical example is presented to illustrate the proposed methods, revealing the significant influence of imperfect repair characteristics on optimal policies.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2023)
Article
Engineering, Industrial
Jianyu Xu, Xiujie Zhao, Bin Liu
Summary: The study applied the concept of risk-aversion in the MDP maintenance model to develop risk-aware maintenance policies. By using risk functions to measure system safety levels and formulating a safety constraint, the optimal maintenance policy with risk awareness was evaluated using a linear programming approach.