| Hematite ore dressing process, a procedure of sequential ore processing comprising of raw material treatment, shaft furnace roasting, ore grinding, magnetic separation, and concentrated ore disposal,is adopted to separate the useful elements from the gangue and other harmful ingredients in the hematite ores, while its product of concentrated iron ore will be supplied as the raw material to the steel production industry. Global production indices reflecting the output, quality, cost and production efficiency include monthly concentrate output, concentrate grade, concentration ratio and ore consumption in hematite ore dressing process.One of the objective of planning and scheduling in the dressing process is to determine the production and operating planning based on the target values of global production indices, subsequently, instruction is also determined to start or stop equipments, assign water and power, and so on.The other is that the global production indices are decomposed hierarchically to determine the daily global production indices including processing capacity, concentrate grade, concentrate output and ratio of operation shift. Technical indices of working procedure are determined by the technical department based on the daily global production indices, such as particle size in grinding process, recovery rate of overflow for shaft furnace roasting process.Set points of process control system are determined according to the technical indices, and outputs track the set points. As a result, global production indices can be controlled to achieve their target values.There are multi-layer, multi-objective, multi-restriction, time varying, and nonlinear characteristic in decomposing process for global production indices in mineral-processing factory. For example, monthly ore consumption is decomposed to the output of operation shift; and concentrate grade, output and ratio are decomposed from month to day. Concentrate grade, output and ratio, and ore input, should be controlled in the target range,,as well as stock of concentrate should be minimum and equilibrium, and so on. Lots of restrictions in decomposing process such as equipments, stock, ore grade and ore cost. There are strong nonlinear characteristic between state and capacity of stock, and between daily concentrate output and production capacity of equipments.It is difficult to optimize global production indices using the conventional approach, so manual decomposing for global production indices is adopted in the mineral processing factory today. The process is time-wasting, and the global production indices can not achieve target values while satisfating the restrictions.Combining the the National 863 High Technology Program Project of "Research and Development of Integrated Automatic System on Ore Concentrate Process (2004AA412030)",the research of optimizing decomposing approach for the optimizing control of the global production indices is developed. The optimizing approach to determine the daily global production indices is proposed, which ensures the actual global production indices are controlled in the target range. The optimizing software is designed and developed. The optimizing decomposing approach is tested by some experiments, the results proves the validity of the approach.The main works are as follows:(1)The optimizing approach for daily global production indices proposed in this dissertation consists of optimizing approach for monthly ore consumption, daily ore consumption and processing capcity of operation shift in each process.At first, optimal values for monthly ore input can be obtained with the optimizing approach. Based on optimal values for monthly ore consumption, concentrate grade and output and ratio are determined with the metal equilibrium formula. Considering the restriction for concentrate grade and output and ratio,the optimal value of daily ore consumption can be obtained.Based on the daily ore consumption, concentrate grade and output and ratio are determined with the metal equilibrium formula. Considering the restriction for concentrate grade, output and ratio,the optimal output for operation shift in each process can be obtained. Based on the optimal output for operation shift in each process, concentrate grade, output and ratio are determined with the metal equilibrium formula. After above steps, daily global production indices are determined.Nonlinear objective programming model which decision value is monthly ore consumption is built in the optimizing algorithm for monthly ore consumption, which takes the least error of global production indices based on importance as objective function, and considers the restriction for the target range of global production indices, concentrate cost, the summation of ore supply. Using the improved genetic algorithm as recursion, the optimal monthly ore consumption is determined.Nonlinear multi-objective programming model whose decision value is daily ore consumption is built in the optimizing algorithm for daily ore input, which takes the least error between daily concentrate output and the mean daily concentrate output of one month as objective function, and considers the restriction for the target range of global production indices, concentrate cost, the summation of ore supply. Using the improved particle swarm optimization algorithm,the optimal daily ore consumption is determined.Nonlinear multi-objective programming model whose decision value is the processing capacity of operation shift is built in the optimizing algorithm for operation shift, which takes the least prcessing capacity variety between the previous operation shift and next as objective function, and considers the restriction for the range of the concentrate cost, the summation of ore supply. Using the improved particle swarm optimization algorithm with multi-objective, the optimal processing capacity of operation shift is determined.(2) Base on the Web Service technology and Microsoft Visual Studio 2005,the optimizing software package is build with Visual C# and Matlab programming language and SQL Server 2000 database. The above optimizing approach is implemented using this software package.This software package includes system management module, optimizing for monthly ore consumption and metal equilibrium computation module, optimizing for daily ore consumption and metal equilibrium computation module, optimizing for processing capacity of each operation shift and metal equilibrium computation module, information query module, system maintenance module, and so on.(3)In a certain hematite ore dressing factory, the target values of global production indices are as follows:concentrate grade is 52.66%, concentrate output is 182.3 thousands ton, concentrate ratio is 2.0049, ore consumption is 365.5 thousands ton. Using the optimizing software package, the decomposing results are as follows:concentrate grade is 52.69%, concentrate output is 183.386 thousands ton, concentrate ratio is 1.9887, ore consumption is 364.7 thousands ton, the global production indices are in their target values bound. Comparing with the manual operation, the error between actual and target value of concentrate grade descends from 0.11% to 0.03%,the error between actual and target value of concentrate output descends from 3.3 thousands ton to 1.086 thousands ton, actual value of ore consumption descends from 395.3 thousands ton beyond target range to 364.7 thousands ton in the target range, actual value of concentrate ratio descends from 2.131 beyond target range to 1.9887 in the target range, equilibrium for concentrate output heighten 16.09%,5.86% reduction for concentrate stock is achieved, waster of concentrate grade descends from 18 to 6.The results of experiment show that this approach can provide optimizing reference values of daily global production. |
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