Kutztown
University
of
Pennsylvania
Combining Statistics and Mathematical
Programming to
Develop Coal Blends for Optimum
Cokemaking
and Blast Furnace Operation
by
Dr.
Francis J. Vasko
ABSTRACT
An
important problem at an integrated steel producing plant is the blending of
different types of coals to make coke for the blast furnace operation. Historically linear blending models were not
appropriate because coal properties important for both optimum cokemaking and blast furnace operation do not combine
linearly and are not completely understood.
In this talk, a two-step methodology is developed to overcome these
classical modeling problems. First,
binary decision trees are used to determine what relationships are necessary in
the component coals to ensure successful cokemaking
and blast furnace operations based on data from a pilot-scale test oven
facility. Second, these relationships
are then incorporated into a mixed integer linear programming model for
blending coals used to produce coke of high quality and low cost for the blast
furnace. Finally, the model results are
utilized at the pilot-scale oven for testing and validating the new, improved
blend(s) that have been dictated by changing availabilities in the coal
sources. These steps reduced costs by both minimizing the number of blends to
be tested at the pilot-scale facility and ensuring a minimum cost coal blend
that is useable for the final operating facilities. Hypothetical, but realistic data are used to
illustrate how the models perform together.
Last updated: 30 January 2007
© 2007, KUDOM.