Study Of Cost Control System For Metal Mines Based On Data Mining Techniques

Metallic mineral resources are non-renewable. The process of exploration is very problematic in China. Inferior infrastructure and equipment raises the dilution rate of ores, thereby wasting mineral resources. In addition, without proper governmental regulations and well-established mining laws, much low-grade ore is discarded intentionally or unintentionally, which seriously hinder mineral resources from sustainable development. Therefore, increasing market competition makes effective cost control one of the most important and urgent issues of mental mining companies.In this paper, results of domestic and foreign research are briefly analyzed, which demonstrates that the ideas of many researchers are confined to qualitative methods, lacking of the application of advanced techniques and technologies such as data mining and the overall solution for cost control. In addition, their analytical results are inferior in visualization and user interface, which makes their methods quite difficult for practice use. Based on these problems and the idea of combining qualitative and quantitative methods, this paper first makes a thorough analysis of cost control in metal mines, proposes a reasonable cost breakdown method and analyzes cost affecting factors. Secondly, in terms of quantitative analysis, this paper analyzed cost affecting factors and cost components using data mart, online analytical processing and data mining techniques, which provides the significance order of cost affecting factors and cost components and decision rules. The proposed method is very fast and effective, since it provides effective standards and methods for inspecting the condition of cost control. Aiming at the lack of overall solutions of domestic and foreign research, cost control system for metal mines is developed in this paper, which includes such modules as online analytical processing and data mining. The qualities of this system such as effective user interaction enable decision makers to analyze cost data and derive potential rules from cost data. Finally, this system is successfully applied in SAN SHAN DAO Gold Mine, which includes the construction of cost data mart, online analytical processing of cost data, analysis of cost affecting factors, analysis of cost components, and the estimation of cost status. The effectiveness of this system illustrates that this system improves the accuracy and reliability of cost calculation, thereby making cost analysis and decision making more effective, and reducing the cost of mental production process.