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Calibrated for NBSK — Configurable for Any Kraft Furnish
About the Book
Every Kraft pulp mill runs on spreadsheets. Dozens of them — one for steam balance, one for chemical cost, one for the recovery boiler, none of them connected. Change the kappa target and you manually update four files. Miss one and the numbers lie.
This book replaces that stack with a single Python model.
Digital Twin for Kraft Pulp Mills in Python is a complete, process-flow-ordered simulation of a softwood Kraft mill — from wood yard to baled pulp, from fiber balance to EBITDA. Every module is connected. Change one parameter and the full mill recalculates in milliseconds: steam balance, chemical consumption, power export, cash cost per ADt, and CapEx payback — all at once.
The model is calibrated to a 1,217 ADt/d NBSK reference mill and validated against real operating data. The furnish is fully configurable — switch softwood to hardwood or mixed furnish by changing two parameters.
WHAT'S INSIDE
WHO THIS BOOK IS FOR
Process engineers, mill managers, and technical consultants who need to run "what-if" scenarios faster than a spreadsheet allows — and understand exactly why the numbers change.
No prior Python experience is required beyond the ability to run a script. If you can read a process flow diagram, you can use this model.
LIVING BOOK
This is a living book. All future updates are delivered automatically to purchased copies through Leanpub at no extra charge.
Planned additions include a hardwood kraft deep module, a Streamlit UI dashboard, and multi-mill comparison tools.
About the Author
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