Latest Research in Industrial Process Health

Top Research Topics in Industrial Process Health

• Machine Fault Diagnosis Techniques — 27 papers
• Machine Learning — 11 papers
• Fault Detection and Control Systems — 10 papers
• Artificial Intelligence — 6 papers
• Reliability and Maintenance Optimization — 6 papers
• Digital Transformation in Industry — 4 papers
• Anomaly Detection Techniques and Applications — 4 papers
• Systems and Control — 3 papers
• Time Series Analysis and Forecasting — 3 papers
• Thermochemical Biomass Conversion Processes — 2 papers

Highest-Cited Papers

1. Evidential Uncertainty-Aware Fault Diagnosis for Autonomous Spacecraft Health Management
2. A Physics-Guided Transformer–LSTM prediction Model with dynamic feature weighting for NOx emission prediction in CFB boilers
3. Interpretable Spatiotemporal Coupling Network for Robust Emission Prediction and Implicit Mechanism Mining in Sludge Gasification
4. Physics-guided deep reinforcement learning framework for reliability-based design optimization of complex mechanical systems
5. Hybrid framework for on‐the‐fly diagnosis of energy inefficiency in multi‐unit processes based on data‐driven and knowledge‐based integration
6. Development and Validation of a Dynamic Bayesian Network‐Based Adaptive Reliability Optimization Model Using Design of Experiments and Expected Information Gain
7. Uncertainty and Business-Aware Remaining Useful Life Estimation for Semiconductor Manufacturing
8. Uncertainty and Business-Aware Remaining Useful Life Estimation for Semiconductor Manufacturing
9. Time-Series Machine Learning for Fault Diagnosis and Severity Estimation in Industrial Processes
10. Toward accurate remaining useful life and state of health estimation using reinforced graph-based physics-informed neural networks enhanced with dynamic weights
11. Explainable LLM-assisted fault diagnosis for smart manufacturing using multi-trace diagnostic rationales and verification
12. Automatic design of logical gates for fault diagnosis in power systems through virus machines
13. LEADI: Operating-Mode-Aware Machine Condition Monitoring for Leak-Related Energy Anomalies—A Before-and-After Maintenance Study of a Single Production Asset
14. A Domain-Guided Feature-Fusion Framework for Ship Equipment Based on Multi-Type Features
15. Learning, fast and slow: a two-fold data-based model adaptation algorithm for processes under varying operating conditions
16. FreqCondNorm: Towards Cross-domain Predictive Maintenance through a Frequency-Conditioned Transformer Foundation Model
17. Symmetry-Aware Neural Evidential Reasoning for Aero-Engine Health-State Assessment Under Operating-Condition and Fault-Mode Asymmetries
18. Reliable Virtual Sensing: A Multi-Domain Benchmark for Robustness Under Sensor Failures
19. Conditionally linear, matrix normal state space models
20. A 3-level interpretable data-driven framework for operational analysis of industrial centrifugal pumps

Sub-Regions

• Machine Learning — 49 papers
• Machine Fault Diagnosis Techniques — 46 papers
• Fault Detection and Control Systems — 37 papers
• Power System Reliability and Maintenance — 10 papers
• Power Systems Fault Detection — 9 papers
• Time Series Analysis and Forecasting — 9 papers