Efficient Planning Models For Underground Coal Mines

Business planning in the coal' industry revolves around the production and quality forecast. It is difficult to accurately estimate costs and revenues until the production forecast is made. At mines where production comes from multiple sections, quality is tied to each section's production. Blending becomes a part of the planning process. In order to respond to rapidly changing business climate, a reliable program is needed to accurately forecast the effects of changes in key parameters affecting the production. This paper discusses an efficient, intuitive, and economical approach to underground coal mine planning program which uses a PC-based relational database as the programming platform to forecast production and quality. The program was developed at a major coal company. The relational nature of the production planning data, the programming algorithm, and the underlying principles are discussed in this paper.