Overview
AI and automation improve visibility, optimization, and coordination. They do not change physics.
When hardware decisions are wrong, no amount of software can recover lost performance.
Where AI Actually Helps
- Route optimization
- Predictive maintenance scheduling
- Fleet coordination
- Demand forecasting
These tools improve efficiency when the mechanical system is already correct.
Where AI Stops
AI cannot reduce rolling resistance caused by the wrong wheel material. It cannot prevent bearing failure caused by undersized load ratings.
- It cannot change floor conditions
- It cannot correct scrub geometry
- It cannot eliminate shock loading
Software optimizes within physical limits. Hardware defines those limits.
Common Failure Patterns
Across automation and AGV projects, failure patterns repeat.
- Premature wheel wear
- Increased push or drive force
- Noise and vibration
- Unexpected downtime
Failure Drivers by System Layer
| Layer | Common Issue | Impact |
|---|---|---|
| Software | Logic and routing errors | Moderate |
| Controls | Sensing and calibration | Moderate |
| Mechanical | Wheels, bearings, floors | High |
| Environmental | Debris, joints, gradients | High |
This table can be converted into a stacked impact chart for presentations or internal reviews.
What Works Better
- Start with floor conditions and duty cycle
- Size wheels and bearings for real loads
- Reduce rolling resistance before optimizing routes
- Validate mechanical systems before scaling software
This approach is outlined in detail in the 2026 Industrial Forecast.