Research Thrust

Intelligent Asset Management and Analytics

Inferring asset health from imperfect data, and turning it into maintenance and spare-parts decisions

 

What it means

Technologies that transform noisy sensor data and uncertain maintenance practices into adaptive and robust maintenance schedules and spare parts provisioning policies.

Why it matters

Predictive analytics tools such as fault diagnostics and prognostics are often limited by noisy sensor data, inconsistent labels, unknown fault modes, and site-to-site variability. Maintenance, repair, and overhaul decisions create value only when noisy data and imperfect predictions are translated into reliable maintenance schedules and spare-parts logistics.

What this research enables

Prognostics & Health Management
Predicting machine degradation before failures disrupt production
Health Monitoring and Fault Diagnostics
Detecting abnormal asset behavior and identifying likely fault modes
Jointly Optimized Manufacturing Operations, Repairs, and Logistics
Turning uncertain health predictions into robust maintenance, production, and logistics decisions

Value to Industry

  • Earlier and more reliable warning of failures
  • Fewer unexpected failures and higher asset availability 
  • Minimize MRO costs and logistics
Capability Area

Health Monitoring and Fault Diagnostics

Detecting abnormal asset behavior and identifying likely fault modes

Operational Gap

Core Innovation

Value to Industry

Active Learning for Efficient Warranty Claim Classification

Faculty: Kamran Paynabar

 Ford 

Federated privacy–preserving fleet diagnostics

Faculty: Nagi Gebraeel

 General Electric 
Capability Area

Prognostics & Health Management

Predicting machine degradation before failures disrupt production

Operational Gap

Core Innovation

Value to Industry

Adaptive prognostics under variable operating conditions

Faculty: Nagi Gebraeel

 U.S. National Science Foundation (NSF) 

Reliability and prognostics of thermo-mechanical failures

Faculty: Jianjun Shi

 Samsung 

High voltage battery Capacity and Retention Prediction

Faculty: Kamran Paynabar

 Ford 
Capability Area

Jointly Optimized Manufacturing Operations, Repairs, and Logistics

Turning uncertain health predictions into robust maintenance, production, and logistics decisions

Operational Gap

Core Innovation

Value to Industry

Predictive planning of manufacturing operations and maintenance

Faculty: Nagi Gebraeel

 U.S. National Science Foundation (NSF) 

Joint optimization of maintenance and spare-parts logistics planning

Faculty: Nagi Gebraeel

 NASA 

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