Prediction Of Surface Miner’s Production Efficiency

Surface miner’s production efficiency is the foundation of surface miner’sapplication. It can provide the basis for decision-makers to determine the miningmethod, machine selection, production planning, and make techno-economic analysisof surface miner. Currently, despite there are many methods to predict surface miner’sproduction efficiency, but the prediction methods and systems are far from perfect,each method has its advantages and disadvantages and application scope. In this paper,using theoretical methods, semi-theoretical-empirical methods and empirical methodsto establish prediction formula of production, set up three types of surface miner’sproduction efficiency formulas and used the collected actual production efficiencydatas or cutting test datas, having comprehensive and comparative analysis for theprediction formula established with three kinds of methods, verify each other, in orderto improve the prediction’s reliability and accuracy of surface miner’s production.Themain working contents and conclusions of this paper are as follows.(1) The cutting theory, experimental results and the analysis of productionexperience, show that the main factors of affecting the cutting specific energy areuniaxial compressive strength and rock quality designation, they can be used asindicators of predict cutting specific energy. The main factors of affecting the surfaceminer’s production efficiency are rock quality designation, brittle index and surfaceminer’s cutting power, they can be used to established empirical fomula of surfaceminer’s production efficiency.(2) Using Evans cutting force model as the theoretical foundation，establishedthe theoretical formula of surface miner’s production efficiency prediction. Contrastbetween this formula’s predicting production efficiency and actual productionefficiency of surface miner, the standard deviation of relative error’s absolute value is18.96%.(3) Using energy conservation law to establish the relationship of surfaceminer’s production efficiency, cutting specific energy and cutting power, we got thesemi-theoretical-empirical methods of surface miner’s production efficiency. Using thisformula to predict the surface miner’s production efficiency, it shows that the results are more accurate, the standard deviation of relative error’s absolute value is14.15%.(4) For selected main factors of surface miner’s production efficiency,established empirical formula of surface miner’s production efficiency by nonlinearregression, linear regression and combination index regression，respectively. Usingthe surface miner’s actual production efficiency as standards, compared and verifiedthe established empirical formula of surface miner’s production efficiency and theexisting empirical formula. The results show that the Gehring formula’s error is larger,the predicting results of Dey&Ghose formula is closer to the actual value. In theobtained empirical formulas, the nonlinear regression prediction is more accuracythan the linear regression, the combination index regression is more realistic.(5) we found that under the same cutting power and lithology, Compared withroadheader and the surface miner’ production efficiency. The results show thatsurface miner’s production efficiency is1.5~2.5times of roadheader’s.(6) Used multiple regression model to analyze the correlation between cuttingspecific energy with rock quality designation and rock uniaxial compressive strength,we got the formula of cutting specific energy. Using the actual cutting specific energydata as standards, compared the established prediction formula of cutting specificenergy with Roxborough cutting specific energy prediction formula, found that ourprediction formula of cutting specific energy’s calculated accuracy is higher.