Predicting iron ore fines shipment moisture

Abstract

In response to the implementation of a new schedule for iron ore fines in the International Maritime Organization's International Maritime Solid Bulk Cargoes Code, improved measures for the management of moisture have been developed. In particular, prediction of cargo moisture allows management of iron ore fines within the supply chain to facilitate the safe shipping of iron ore fines. An Autoregressive Integrated Moving Average model, augmented to allow for shipment tonnage, has been developed to predict the moisture level from previous shipments of the same product. The model explains about 60% of the moisture variance. It was found that inclusion of other available information, such as ore composition, train/rake assays and recent rainfall at port and mine did not add to the predictive power of the model.

Keywords

Iron ore Forecasting Moisture Shipping

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References

Box

and Jenkins

. 1970. Time series analysis: forecasting and control, San Francisco, CA, Holden-Day.

Diebold

. 2008. Elements of forecasting, 4th edn, Mason, OH, South Western.

Everett

. 2007. Computer aids for production systems management in iron ore mining, Int. J. Product. Econ., 110, 213–223.

Everett

and Howard

. 2011. Predicting finished product properties in mining industry from pre-extraction data, Appl. Earth Sci., 120, (3), 137–147.

International Maritime Organization. 2012. IMBSC Code, IMO Publishing, London, UK.

ISO 3085. 2002. Iron ores – experimental methods for checking the precision of sampling, sample preparation and measurement, 4th edn, International Standards, Sydney, NSW, SAI Global.

Mulrenan

. 2012. London hull underwriters join battle against liquefaction losses, Tradewinds, 2 March 2012.