A large integrated steel producer needed to support rising production without proportionally increasing unloading infrastructure.
70+ leaders engaged in AI Discovery
The team defined the outcome, constraints, success measures, and value at stake before designing the solution.
Historical operating data then revealed that delays occurred before, during, and after unloading—and varied by asset, material, season, and operating condition.
The solution brought together optimization, machine learning, Gen AI and intelligent Agents:
Operating rules, exceptions, and experienced-user knowledge were also embedded into the platform.
Supported by:
Target increase in daily unloading throughput
The platform was designed around the decisions managers need to make in a dynamic operating environment, not around technology for its own sake.
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