Quality Of Iron Ore Research Articles

English

Cleveland-Cliffs Michigan Operations (CCMO) produces 13.0 million long tons of high quality iron ore pellets annually for consumption in the blast furnaces of both domestic and foreign steel producers. Annual total material movement is approximately 80 million long tons, of which half is waste rock. Since the inception of mining in 1962, over 1.3 billion long tons of waste rock have been placed in waste rock stockpiles. Geographically the mining area is rolling to rugged topography. Landforms are the product of repeated continental glaciation and vary from till and outwash plains to steeply sloped hills with dendritic surface drainage patterns. Sandy glacial drift is the parent material for soils in the area, the thickness of which varies from bedrock to several hundred feet thick in localized areas. The local climate is classified as cool to temperate with 110 to 130 frost-free days and the area generally experiences a surplus water regime with an annual precipitation of 35 inches, of which half is in the form of snow. Current and developing reclamation practices for waste rock stockpiles will be reviewed. These include the use of paper mill residuals, municipal biosolids and a developing program with composted municipal solid waste. In addition to the pulp and paper mills, waste water treatment plant and county landfill, other entities involved include the county soil conservation district, a forestry services contractor, an explosives contractor, and a well drilling contractor.

Iron ore production scheduling to improve product quality

Iron ore quality depends upon successive shipments being uniform in composition, not only in iron but also in several other minerals. The production process involves several stages of scheduling, from the mine face, through railing, stockpiling and ship loading. At each of these stages there is potential to improve the composition uniformity through appropriate scheduling procedures. This paper discusses a variety of algorithms and simulation models developed to aid these scheduling decisions.