# Jay Lee

**Type:** Researchers  
**Canonical URL:** https://scholariq.org/researchers/jay-lee/

## Facts

| Field | Value |
| --- | --- |
| Citations | 30,865 |
| Field | Machine Fault Diagnosis Techniques |
| h-index | 72 |
| i10-index | 243 |
| Last Known Institution | University of Maryland, College Park |
| OpenAlex ID | https://openalex.org/A5100686648 |
| ORCID iD | 0000-0002-4022-4274 |
| Works | 554 |

## Researcher papers

- [A Cyber-Physical Systems architecture for Industry 4.0-based manufacturing systems](https://scholariq.org/papers/a-cyber-physical-systems-architecture-for-industry-4-0-based-manufacturing/)
- [Service Innovation and Smart Analytics for Industry 4.0 and Big Data Environment](https://scholariq.org/papers/service-innovation-and-smart-analytics-for-industry-4-0-and-big-data-environment/)
- [Prognostics and health management design for rotary machinery systems—Reviews, methodology and applications](https://scholariq.org/papers/prognostics-and-health-management-design-for-rotary-machinery-systems-reviews/)
- [Wavelet filter-based weak signature detection method and its application on rolling element bearing prognostics](https://scholariq.org/papers/wavelet-filter-based-weak-signature-detection-method-and-its-application-on/)
- [Recent advances and trends in predictive manufacturing systems in big data environment](https://scholariq.org/papers/recent-advances-and-trends-in-predictive-manufacturing-systems-in-big-data/)
- [Industrial Artificial Intelligence for industry 4.0-based manufacturing systems](https://scholariq.org/papers/industrial-artificial-intelligence-for-industry-4-0-based-manufacturing-systems/)
- [A review on prognostics and health monitoring of Li-ion battery](https://scholariq.org/papers/a-review-on-prognostics-and-health-monitoring-of-li-ion-battery/)
- [Review and recent advances in battery health monitoring and prognostics technologies for electric vehicle (EV) safety and mobility](https://scholariq.org/papers/review-and-recent-advances-in-battery-health-monitoring-and-prognostics/)
- [Industrial Artificial Intelligence in Industry 4.0 - Systematic Review, Challenges and Outlook](https://scholariq.org/papers/industrial-artificial-intelligence-in-industry-4-0-systematic-review-challenges/)
- [Intelligent prognostics tools and e-maintenance](https://scholariq.org/papers/intelligent-prognostics-tools-and-e-maintenance/)
- [Bayesian Belief Network-based approach for diagnostics and prognostics of semiconductor manufacturing systems](https://scholariq.org/papers/bayesian-belief-network-based-approach-for-diagnostics-and-prognostics-of/)

## Researcher topics

- [Machine Fault Diagnosis Techniques](https://scholariq.org/topics/machine-fault-diagnosis-techniques/)
- [Fault Detection and Control Systems](https://scholariq.org/topics/fault-detection-and-control-systems/)
- [Industrial Vision Systems and Defect Detection](https://scholariq.org/topics/industrial-vision-systems-and-defect-detection/)
- [Digital Transformation in Industry](https://scholariq.org/topics/digital-transformation-in-industry/)
- [Manufacturing Process and Optimization](https://scholariq.org/topics/manufacturing-process-and-optimization/)

## Researcher university

- [University of Maryland, College Park](https://scholariq.org/institutions/university-of-maryland-college-park/)

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Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.