Improved Production Forecasting through Geometallurgical Modeling at Iron Ore Company of Canada

- Organization:
- Canadian Institute of Mining, Metallurgy and Petroleum
- Pages:
- 17
- File Size:
- 379 KB
- Publication Date:
- Jan 1, 2009
Abstract
"A commitment to a core testing, plant modeling and reconciling technique has shown substantial economic benefits to IOC in terms of accurate production forecasting, smoother operation of the mill, improved expectations of throughput and co-operation across production departments from geology, planning, mining, and processing, to shipping of concentrate to market.This paper describes a successful seven year program of forecasting throughput of the autogenous milling circuit at the Carol Lake concentrator of IOC. Work started with audits of the grinding circuit in 2001 and benchmarking of the data collected from samples of mill feed and plant operation to the CEET mill design and throughput forecasting model.Initially 390 drill core samples were tested for SAG Power Index (SPI) to measure the energy required in milling, and the data distributed using a geostatistical technique across the two operating pits, so that hardness was estimated in each of the 40,000 blocks (or 1500 million tons) of potential ore. In 2004 a forecast of energy requirement, i.e. forecast of throughput for a given power availability at the mill, was produced for each ore block using the CEET model and used for mine planning to smooth plant throughput. The forecast for blocks mined on a monthly basis was reconciled with plant results over the next 2 years and minor changes made to the CEET model. The forecasting exercise was repeated in 2006 and in 2008 with the latest model based on the testing of almost 1300 samples of drill core at closer spacing.INTRODUCTIONThe contracting of sales to clients and the timely supply of products to meet those contracts is a cornerstone of good business practice. Ensuring the correct scheduling of production is a major concern of mining companies where the supply and qualities of the raw material is uncertain and production facilities are not flexible. This is particularly challenging when the product is of high volume and produced far from the customer, such as iron ore.Apart from the metal content of the ore being mined, the greatest impact on production scheduling is the throughput of the comminution section of the extraction plant; most notably when size reduction is achieved by autogenous grinding. The response of the mills to variability in the hardness of the ore can change throughput by as much as 50% from day to day at some plants."
Citation
APA:
(2009) Improved Production Forecasting through Geometallurgical Modeling at Iron Ore Company of CanadaMLA: Improved Production Forecasting through Geometallurgical Modeling at Iron Ore Company of Canada. Canadian Institute of Mining, Metallurgy and Petroleum, 2009.