Computer Optimization of Mineral Processing Plants

Computer Optimization of Mineral Processing Plants

Steady-state simulation is now an operational tool used to assist mineral processing engineers in the design, adaptation and improvement of mineral processing plants.

Since 1988, the computer applications team of the Mineral Technology Department of BRGM has been developing and distributing a simulation software, now in use in more than twenty countries, by universities, research centers, engineering companies, manufacturers and mining groups for design and optimization purposes.

The Shila Case Study

The Shila Mine. In the first months of 1990, Minera Shila S.A. (jointly owned in equal shares by Cedimin S.A., a 65% subsidiary of the French Group BRGM and Buenaventura S.A., a Peruvian company) began production at the Shila gold and silver mine, in southern Peru.

mineral-processing-plants-partnership-approach-required-for-a-plant-optimization-project

mineral processing plants initial flowsheet

Problem definition. A few months after start up, Minera Shila decided to increase the throughput to 135 tpd. The equipment was originally scaled up to allow such an increase, but it soon became obvious that the ball mill was unable to adjust to this increased capacity. About 31 tpd of unground material were rejected by the outlet screen (“Granza” flowrate) and stored on an outside pad.

General Approach to an Optimization Project

An optimization project is generally approached through an integrated procedure, which is divided into two steps: the first consists in creating a simulator of the existing processing plant; the second, in testing different modifications with this simulator and evaluating all the simulation results in technical (characteristics of the products, power drawn by the main equipment) and economic (estimation of the capital cost investment) terms.

 

mineral-processing-plants-material-balance-software-program

Choice and calibration of mathematical models. Several models are available for each unit operation. Some (called level-O models in USIM PAC) do not really predict how units will perform; they simply calculate output streams for a specification on unit performance given by the software user. These models, sometimes called flowsheeting models, are not well adapted to simulate an existing plant because they do not take into account the sizes of the equipment.

Simulation. When all the models are calibrated, the main USIM PAC algorithm chains them to reproduce the plant operation (see Figure 5). The user must then compare the results with the experimental data to verify the validity of the simulator.

mineral-processing-plants-basic-functions-of-a-steady-state-simulator

Modified plant simulation

First Phase Decreasing the “Granza” Flowrate at the Shila Plant

Plant flowsheet. The crushing and grinding circuits are illustrated on Figure 2. A primary Denver jaw crusher (15″ x24″), reduces the run-of-mine ore from 300 mm (12″) top size down to 75 mm (3″). A double deck vibrating screen separates the minus 12.5 mm (½”) material from the crushed product. The screen oversize is further reduced in a standard (3′) Symons cone crusher running in open circuit. The crushed product and the screen undersize are then stored in a 200 t bin. The crushing unit runs about 6 hours a day. An Allis Chalmer ball mill (6′ x 6′) grinds the crushed ore down to 200 µm (75 mesh) in closed circuit with a 14″ cyclone. A jig installed between the mill discharge and the cyclone recovers the coarse free gold particles.

mineral-processing-plants-comparison-between-sampled-and-simulated-data

Technical conclusions for decreasing the “Granza” flowrate

  • Integrating the secondary cone crusher in a closed circuit gives the best improvement to the ball mill operation.
  • Reducing the opening of the cone crusher gives less improvement.
  • The “Granza” flowrate is then negligible while the d80 of flotation feed falls to 150 µm.

mineral processing plants flowsheet

Second Phase Increasing the Shila Plant Capacity

Having adopted the modified flowsheet, with the secondary crusher has been included in a closed circuit on a screen, Minera Shila S.A. later decided to increase the plant capacity from 135 to 230 tpd.

New sampling was carried out by the plant operators, a simulator of the new flowsheet was built to take into account the closed circuit. The main properties of the original simulator, such as the ore model and the unit operation models, were retained. A material balance was run on the new sampled data and the models were calibrated with this new data set.

mineral processing plants comparison of the simulated flowsheet configurations

mineral processing plants flowsheet proposed

Value of the Partnership Approach to an Optimization Study

The Shila case study has shown that, at almost every step in the optimization project, cooperation is needed between the process engineer and the simulation specialist.

The optimization study can be done by one and the same person as long as he has a sufficient understanding in the use of simulation, a good know-how in mineral processing and a detailed knowledge of the plant operation. Most process engineers now use “notebook” computers, when auditing a plant; this may be merely for taking notes or making some technical and economic calculations with a spreadsheet, but increasingly it is for using technical software such as a process simulator.

mineral processing plants flowsheet drawing

mineral processing plants material balance

mineral processing plants models

mineral processing plants usim pac

mineral processing plants crushing and grinding circuit

mineral processing plants sampling

mineral processing plants initial flowsheet-2

computer-aided optimization of mineral processing plants a case study increasing the capacity of the shila gold mine peru