4.7 Article

Maintenance optimisation for systems with multi-dimensional degradation and imperfect inspections

期刊

INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
卷 59, 期 24, 页码 7537-7559

出版社

TAYLOR & FRANCIS LTD
DOI: 10.1080/00207543.2020.1844919

关键词

Imperfect inspection; multi-dimensional degradation processes; maintenance optimisation; hidden failure; cost analysis

资金

  1. National Natural Science Foundation of China [61873096, 62073145, 71971181, 72002149]
  2. Guangdong Technology International Cooperation Project Application [2020A0505100024]
  3. Guangdong Basic and Applied Basic Research Foundation [2020A1515011057]

向作者/读者索取更多资源

This paper develops a maintenance model for systems with multiple correlated degradation processes, utilizing inspections to detect hidden failures and reduce economic losses. The research findings suggest that the inaccuracy of inspections significantly impacts operating costs, emphasizing the need to improve inspection accuracy.
In this paper, we develop a maintenance model for systems subjected to multiple correlated degradation processes, where a multivariate stochastic process is used to model the degradation processes, and the covariance matrix is employed to describe the interactions among the processes. The system is considered failed when any of its degradation features hits the pre-specified threshold. Due to the dormancy of degradation-based failures, inspection is implemented to detect the hidden failures. The failed systems are replaced upon inspection. We assume an imperfect inspection, in such a way that a failure can only be detected with a specific probability. Based on the degradation processes, system reliability is evaluated to serve as the foundation, followed by a maintenance model to reduce the economic losses. We provide theoretical boundaries of the cost-optimal inspection intervals, which are then integrated into the optimisation algorithm to relieve the computational burden. Finally, a fatigue crack propagation process is employed as an example to illustrate the effectiveness and robustness of the developed maintenance policy. Numerical results imply that the inspection inaccuracy contributes significantly to the operating cost and it is suggested that more effort should be paid to improve the inspection accuracy.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.7
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

Article Engineering, Industrial

Performance-oriented risk evaluation and maintenance for multi-asset systems: A Bayesian perspective

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.

IISE TRANSACTIONS (2022)

Article Computer Science, Artificial Intelligence

Adaptive ranking based ensemble learning of Gaussian process regression models for quality-related variable prediction in process industries

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

A performance-based warranty for products subject to competing hard and soft failures

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

An Age- and Condition-Dependent Variable Weight Model for Performance Evaluation of Bridge Systems

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

Reliability testing for product return prediction

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

A comprehensive toolbox for the gamma distribution: The gammadist package

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

Multi-index probabilistic anomaly detection for large span bridges using Bayesian estimation and evidential reasoning

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

Clustering-Guided Novel Unsupervised Domain Adversarial Network for Partial Transfer Fault Diagnosis of Rotating Machinery

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

A Hybrid Cleaning Scheduling Framework for Operations and Maintenance of Photovoltaic 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

Imperfect maintenance policies for warranted products under stochastic performance degradation

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

Data Augmentation and Intelligent Fault Diagnosis of Planetary Gearbox Using ILoFGAN Under Extremely Limited Samples

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

Maintenance optimization for dependent two-component degrading systems subject to imperfect repair

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

A risk-aware maintenance model based on a constrained Markov decision process

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.

IISE TRANSACTIONS (2022)

暂无数据