Balanced systems are extensively utilized in various engineering fields. However, the study of maintenance optimization for balanced systems under dependent competing risks is very limited, and the existing method for orthodox multi-unit systems cannot solve the maintenance problem of balanced systems. Thus, we present a novel maintenance optimization method for systems with multiple balanced units. The units in the system are assumed to experience multiple failure processes due to continuous degradation and external shock damage. The system failure occurs in the following situations: (1) the deterioration levels of units on the symmetric positions exceed critical thresholds. (2) the deterioration level of any unit reaches the failure threshold. (3) the shock magnitude is greater than the hard failure threshold. By employing a customized deep reinforcement learning algorithm, we derive the optimal maintenance policy under a fixed planning horizon. Notably, our approach differs from previous research on maintenance optimization for balanced systems, the proposed method avoids the discretizing of the deterioration state. This significantly enhances computational efficiency, particularly when applied to multi-unit balanced systems. Numerous numerical studies illustrate the effectiveness of our proposed maintenance optimization method for multi-unit balanced systems.

Hengchang Liu

Bo Li

Fengming Yao

Gexi Hu

Lei Xie

Reliability Engineering & System Safety

Reliability Engineering and System Safety is an international journal devoted to the development and application of methods for the enhancement of the safety and reliability of complex technological systems, like nuclear power plants, chemical plants, hazardous waste facilities, space systems, offshore and maritime systems, transportation systems, constructed infrastructure and manufacturing plants. The journal normally publishes only articles that involve the analysis of substantive problems related to the reliability of complex systems or present techniques and/or theoretical results that have a discernable relationship to the solution of such problems. An important aim is to achieve a balance between academic material and practical applications.

The following topics are within the scope of the journal: methods for reliability and probabilistic safety assessment; model and parameter uncertainties; aleatory and epistemic uncertainties, sensitivity analysis, data collection and analysis; engineering judgement and expert opinions; human reliability; test and maintenance policies; models for ageing and life extension; systems analysis of the impact of earthquakes, fires, tornadoes, winds, floods, etc.; codes, standards and safety criteria; operator decision support systems; software reliability; methods and applications of automatic fault detection and diagnosis; dynamic reliability; design and evaluation of man machine systems and human interfaces; design innovation for safety and reliability; safety culture; accident investigation and management. The journal does not normally publish articles that involve fuzzy sets and related non-probabilistic methods unless they contribute significantly to the solution of substantive problems related to the analysis of real systems.

The journal will contain contributed material in the form of original research papers, review articles, industrial case studies, safety recommendations, and short communications.

Reliability Engineering and System Safety is an international journal dedicated to the development and application of methods aimed at enhancing the safety and reliability of complex technological systems, such as nuclear power plants, chemical plants, hazardous waste facilities, space systems, offshore and maritime systems, transportation systems, constructed infrastructure, and manufacturing plants. The journal typically publishes articles that analyze substantive problems related to the reliability of complex systems or present techniques and/or theoretical results that have a clear relationship to solving such problems. A key objective is to achieve a balance between academic content and practical applications.

The following topics are within the scope of the journal: methods for reliability and probabilistic safety assessment; model and parameter uncertainties; aleatory and epistemic uncertainties; sensitivity analysis; data collection and analysis; engineering judgment and expert opinions; human reliability; test and maintenance policies; models for aging and life extension; systems analysis of the impacts of earthquakes, fires, tornadoes, winds, floods, etc.; codes, standards, and safety criteria; operator decision support systems; software reliability; methods and applications of automatic fault detection and diagnosis; dynamic reliability; design and evaluation of man-machine systems and human interfaces; design innovation for safety and reliability; safety culture; accident investigation and management. The journal does not typically publish articles involving fuzzy sets and related non-probabilistic methods unless they significantly contribute to solving substantive problems related to the analysis of real systems.

The journal will contain contributed material in the form of original research papers, review articles, industrial case studies, safety recommendations, and short communications.

《Reliability Engineering and System Safety》是一本国际期刊，致力于开发和应用方法，以提高复杂技术系统的安全性和可靠性。这些系统包括核电站、化工厂、有害废物设施、航天系统、海上和海洋系统、交通系统、建筑基础设施和制造工厂。期刊通常只发表涉及复杂系统可靠性相关实质性问题分析的文章，或提出与解决此类问题有明显关系的技术和/或理论结果。期刊的重要目标是实现学术材料与实际应用之间的平衡。

期刊的范围包括以下主题：可靠性和概率安全评估的方法；模型和参数的不确定性；随机和认知不确定性；敏感性分析；数据收集与分析；工程判断和专家意见；人类可靠性；测试和维护政策；老化和寿命延长模型；地震、火灾、龙卷风、风、洪水等影响的系统分析；规范、标准和安全标准；操作员决策支持系统；软件可靠性；自动故障检测和诊断的方法与应用；动态可靠性；人机系统和人机界面的设计与评估；安全和可靠性的设计创新；安全文化；事故调查与管理。期刊通常不发表涉及模糊集和相关非概率方法的文章，除非它们对解决与真实系统分析相关的实质性问题有显著贡献。

期刊将包含以原创研究论文、综述文章、工业案例研究、安全建议和简短通讯等形式提交的材料。

Category	Quartile
工程技术	1
工程技术, 工程工业	1
工程技术, 运筹学与管理科学	1

Maintenance optimization of multi-unit balanced systems using deep reinforcement learning

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Journal Info

Category	Quartile
OPERATIONS RESEARCH & MANAGEMENT SCIENCE	1