01
AI in Automation
- Computer vision for inspection and localization.
- Machine learning for anomaly detection.
- Predictive models for equipment health.
- Optimization for scheduling and resource allocation.
- Learning-based control and system identification.
- Natural-language interfaces for operators and engineers.
02
Predictive Maintenance
Predictive maintenance estimates equipment condition or future failure risk from historical and real-time observations. Useful features may include vibration, temperature, current, pressure, cycle counts, acoustic signals, and operating context.
03
Hybrid Intelligent Control
A robust architecture can combine learned models with conventional feedback control, deterministic constraints, and safety mechanisms. The learned component handles perception or adaptation while lower-level control maintains physical behavior within known limits.