AI Biomass Supply Chain
The Problem
“Optimize Biomass Procurement, Logistics, and Plant Feedstock”
Organizations face these key challenges:
1
Volatile feedstock availability and price driven by seasonality, competing demand (pellets, pulp/paper), and weather disruptions
2
High variability in moisture/ash/chlorine causing off-spec deliveries, contract disputes, and boiler performance losses
3
Inefficient logistics planning (routing, backhauls, dispatch, yard management) leading to higher $/ton-mile, missed delivery windows, and stockouts
Impact When Solved
3–8% reduction in delivered biomass cost via optimized sourcing, routing, and blending10–20% reduction in unplanned downtime/derates linked to fuel quality and handling variability10–25% lower average inventory and working capital while maintaining >98% fuel availability
The Shift
Real-World Use Cases
AI-Driven Optimization for Hydrogen Production
We use smart computers to help make hydrogen energy more efficiently and reliably.
optimizationemerging
7.0
Hydrogen Value Chain Optimization
HyAI helps companies make smart choices about hydrogen production and use, like a robot that tells you the best way to make and store hydrogen.
optimizationgrowing
7.0
AI Optimization for Hydrogen Production
This project uses smart computers to help make hydrogen energy cheaper and better.