ONE PROBLEM, DECODED.
Fewer passes.
Same standard.
A production-grade decision system that searches for the minimum feasible cold rolling schedule—without trading away quality, safety, or mechanical constraints.
BUILT FROM SIX YEARS OF PRODUCTION HISTORY
PRODUCTION HISTORY
ObserveREDUCTION MODEL
PredictPROCESS LIMITS
ConstrainFEASIBLE SCHEDULE
Optimize01 / THE PROBLEM
Every pass has a cost.
Every reduction has a limit.
Cold rolling reduces steel coils to a target gauge through a sequence of passes. The difficult question is not whether the target can be reached, but how to reach it in the fewest safe steps.
Pass schedules are shaped by interacting process parameters and are often built through rules or operator experience. That can leave efficiency hidden inside the process: extra passes, extra energy, and unnecessary variation.
02 / THE METHOD
Predict what is possible. Optimize what is feasible.
The model does not propose an idealized answer and hope the mill can execute it. Feasibility is part of the search itself.
We learned the relationship between process conditions and achievable thickness reduction per pass from historical production data. That predictive model became the engine of a constrained optimization framework that allocates reduction across the full sequence.
Candidate schedules are checked against the operation before they are accepted. The result is the shortest schedule the process can actually run.
HARD CONSTRAINTS / ALWAYS ACTIVE
- 01Rolling forceVERIFIED
- 02Current limitsVERIFIED
- 03Tension rangesVERIFIED
- 04Material strengthVERIFIED
- 05Final gaugeVERIFIED
03 / THE RESULT
Small changes in sequence. Measurable changes in production.
15–20%
fewer passes
for selected coil scenarios
2–3%
lower total pass count
on average across production
≈2%
energy savings
from a more efficient rolling sequence
Beyond energy, the optimized schedules improve throughput, stabilize the process, and reduce dependency on operator-driven decisions.
LESS VARIATION · MORE THROUGHPUT · LOWER ENERGY04 / YOUR PROBLEM