Call for Papers
Call for Papers | 
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Areas of Particular Interest / 重点关注领域
The conference particularly welcomes research and applications related to electronic components (including electromechanical components), electronic circuits and functional modules, electronic equipment and products, and electronic and complex engineering systems. Contributions from other reliability-related engineering domains are also welcome.
会议特别关注电子元器件（包括机电组件）、电子电路与功能模块、电子设备与产品、电子系统及复杂工程系统等对象的可靠性研究与工程应用，同时欢迎其他可靠性相关工程领域的研究成果。
- Digital Twin Architectures and System Integration
数字孪生架构与系统集成- Multiphysics and Multiscale Digital Twin Modeling
多物理场与多尺度数字孪生建模- Physics–Data Hybrid Modeling and Surrogate Models
机理—数据融合建模与代理模型- Model Calibration, Verification, Validation, and Uncertainty Quantification
模型校准、验证确认与不确定性量化- Real-Time State Estimation and Dynamic Model Updating
实时状态估计与模型动态更新- Digital Threads and Lifecycle Data Integration
数字主线与全寿命周期数据集成- Condition Monitoring and System Health Assessment
状态监测与系统健康评估- Fault Diagnosis, Prognostics, and Remaining Useful Life Estimation
故障诊断、状态预测与剩余寿命估计- Predictive Maintenance and Health Management Decision-Making
预测性维护与健康管理决策- Real-Time Digital Twins and Edge–Cloud Collaboration
实时数字孪生与边缘—云协同
- System Reliability Modeling and Assessment
系统可靠性建模与评估- Dynamic, Time-Dependent, and Multi-State Reliability
动态、时变与多状态系统可靠性- Dependent Failures, Common-Cause Failures, and Cascading Effects
相关失效、共因失效与级联效应- Reliability of Complex Networks and Systems of Systems
复杂网络与体系级系统可靠性- Mission-Profile-Based Reliability and Mission Assurance
基于任务剖面的可靠性与任务保障- Resilience Modeling, Metrics, and Assessment
系统韧性建模、度量与评估- Fault-Tolerant Design and Graceful Degradation
容错设计与系统渐进降级- Recovery, Restoration, and Adaptive Reconfiguration
系统恢复、功能重建与自适应重构- System-Level Reliability Allocation, Redundancy, and Architecture Optimization
系统级可靠性分配、冗余与架构优化- Human, Software, and Cyber-Physical System Reliability
人因、软件与信息物理系统可靠性
- AI-Enabled Automated Reliability Modeling
人工智能驱动的可靠性自动建模- Physics-Informed and Hybrid AI for Reliability
面向可靠性的物理信息与混合智能方法- AI-Driven Anomaly Detection and Fault Diagnosis
人工智能驱动的异常检测与故障诊断- AI-Based Prognostics and Remaining Useful Life Prediction
基于人工智能的状态预测与剩余寿命预测- Multimodal and Multi-Source Reliability Data Fusion
多模态与多源可靠性数据融合- Transfer Learning, Few-Shot Learning, and Domain Adaptation
迁移学习、小样本学习与领域自适应- Generative AI and Foundation Models for Reliability Engineering
面向可靠性工程的生成式人工智能与基础模型- Knowledge Graphs and Intelligent Reliability Reasoning
可靠性知识图谱与智能推理- Explainable, Causal, and Trustworthy AI
可解释、因果与可信人工智能- Uncertainty-Aware Learning and Out-of-Distribution Generalization
不确定性感知学习与分布外泛化
- Reliability and Quality Consistency Modeling, Characterization, and Assessment
可靠性与质量一致性建模、表征与评估- Unit-to-Unit and Lot-to-Lot Variability and Consistency Assessment
个体间与批次间差异及一致性评估- Manufacturing Variability and Process–Reliability Interaction
制造波动及其与可靠性的交互作用- Statistical Process Control and Intelligent Quality Analytics
统计过程控制与智能质量分析- Quality Consistency Design and Optimization
质量一致性设计与优化- Reliability-Based Design, Robust Design, and Tolerance Optimization
可靠性设计、稳健设计与公差优化- Reliability Testing, Qualification, and Accelerated Testing
可靠性试验、鉴定与加速试验- Screening, Burn-In, and Early-Failure Control
可靠性筛选、老炼与早期失效控制- Failure Analysis, Root-Cause Identification, and Corrective Action
失效分析、根因识别与纠正措施- Supplier Quality, Component Assurance, and Supply-Chain Reliability
供应商质量、元器件保证与供应链可靠性
- Regular Research Papers (REG): Novel theoretical and methodological contributions
- Industrial Practice Papers (PER): Real-world case studies, implementation experiences
- Tool and Artifact Papers (TAR): New software tools, datasets, benchmark studies
- Position Papers: Visionary perspectives on future reliability challenges