Mine-to-Mill Optimization of Aggregate Production

Mine-to-Mill optimization is a total systems approach to the reduction of energy and cost in mining and mineral processing operations. Developed at the Julius Krutschnitt Mineral Research Centre (JKMRC) in Queensland, Australia, the Mine-to-Mill approach attempts to minimize energy consumption through the optimization of all steps in the size reduction process. The approach involves sampling and modeling of blasting and processing, followed by computer simulation to optimize the operation and develop alternatives. The most promising alternatives are implemented, and sampling is conducted to quantify energy savings. In the current project, the primary objective is to adapt the JKMRC Mine-to-Mill technology to the aggregates industry. The second phase of this project is being carried out at the Pittsboro Quarry located south of Chapel Hill, North Carolina. This quarry is owned by 3M Corporation and operated by Luck Stone. Based on lessons learned from the first phase work, long-term monitoring ({approx} three months) of all quarry operations is being carried out to minimize the impact of geological changes during the mining process. To date, the blasting and processing operations have been audited and modeled, the long-term monitoring of current Luck Stone practice has been completed, and a modified blasting approach has been implemented based on the results of simulations using JKSimBlast and JKSimPlant. The modified blasting approach is expected to increase the primary throughput by 15% and the secondary throughput by approximately 6%, with an overall specific energy reduction of around 1%. Long-term monitoring is currently underway to evaluate the impact the modified blasting approach. This report summarizes the current status of work at the Pittsboro Quarry

Modelling of verticle spindle mills. Part 2: integrated models for E-mill MPS and CKP mills

The sub-models of comminution and classification for vertical spindle mill (VSM) presented in Part 1 of this paper have been integrated in the VSM simulation models for the E-mill, MPS mill and CKP mill. Plant survey data from an E-mill (ball-race) and MPS mill (roller-race), both including internal streams and external sampling, and the CKP mill (roller-race without internal classification) were used to calibrate the VSM sub-model parameters for each device. It was found that the fitted comminution and classification model parameters were closely related to the primary air flow rates in the VSM operation. Relationships between the sub-model parameters and the air flow rates were established. Once the models are calibrated, no further model parameters fitting is required. The VSM models have been implemented in Microsoft Excel via the MDK (Model Development Kits) protocol. A number of potential applications of the JKMRC VSM models for coal-fired power stations and other industries are discussed

Modelling of verticle spindle mills. Part 1: Sub-models for comminution and classification

A new mechanistic model for vertical spindle mills (VSM) has been developed by Julius Kruttschnitt Mineral Research Centre (JKMRC) at the University of Queensland. Unlike the previous work in the literature, which treats the VSM as a “black box”, the present work incorporates two sets of variables in the model: (1) the coal specific property, and (2) the machine specific variables. The VSM model is presented in two parts/papers. The first part presents the sub-models for comminution and classification in the VSM. The second part describes the integration of the sub-models to simulate industrial scale E-Mill, MPS and CKP mills. The sub-models include mill power prediction, size specific energy calculation, size dependent breakage function, product size distribution estimation, elutriation classification and gas cyclone classification. The coal breakage property was measured with a JKFBC grinding device and modelled using a size-dependent breakage function. The machine specific variables include mill geometry, air classifier geometry, coal feed rate, primary air flow rate, air temperature, air pressure, grinding table rotational speed, mill spider hydraulic load and mill power draw. These variables are incorporated in the comminution and classification functions based on physical principles

Geometallurgical mapping and modelling of comminution performance at the Cadia East porphyry deposit

Cu-Au porphyry deposits are large tonnage low-grade resources dependent on processing large volumes of material. The ability to understand and predict comminution perfonnance is critical, as it is frequently the rate-limiting step during processing. Parameters required from geometallurgical mapping and modelling of comminution perfonnance are: • Axb processing domains based on impact breakage variability, and • BMWi processing domains showing grind response variability which lead to • Mine throughput domains for a specific comminution circuit configuration. Due to the cost and/or large sample requirements of traditional comminution tests, insufficient data density and distribution of comminution indices commonly exist, making it difficult to model and map deposit scale variability. One method routinely applied to three dimensional domaining is to have an a priori zoning based on geological features (lithology, alteration, mineralogy, textures), and then apply to all material within a given domain the metallurgical values measured on a single sample or average of samples from that domain. The problem with this approach is that commonly the geological domains do not reflect comminution response, therefore compromising the quality of the average domain estimate. To resolve this problem an alternate integrated geometallurgical mapping and modelling method is applied to model and map comminution performance at Cadia East. This paperuses adata set of -32000 assay measurements andgeologicallogginginformation, integrated with -150 comminution measurements to analyse and develop proxy support models for comminution indices (ie Axb, BMWi, and throughput) based on inherent geological variability. Discrete downhole comminution processing domains are created, mapping orebody response while maintaining inherent variability

Development of new comminution testing methodologies for geometallurgical mapping of ore hardness and throughput

The emerging discipline of ‘geometallurgy’ is becoming increasingly recognised as a discrete and high-value activity that reflects an ongoing trend towards more effective mine site integration and optimisation. Constrained sampling that reflects and defines inherent ore body variability is a key geometallurgical requirement. This requires use of larger numbers of low-cost physical testing which can be applied to small sample volumes suitable for defining natural variability. The AMIRA P843 ‘GeMIII’ project (Geometallurgical Mapping and Mine Modelling) is a major industry-supported research initiative designed to develop new tools, methods and protocols to support geometallurgical integration. As part of this integrated research a new more rapid low-cost comminution test (GeM Comminution index) has been developed which can be employed as a front line tool for geometallurgical mapping purposes and predictive throughput modelling. The test has been designed to be inserted into routine assay sample preparation and is based on constrained jaw crushing protocols linked to analysis of resultant size distributions. Extensive validation and modelling has shown the GeM Comminution Index (Ci) is correlated with the Drop Weight index A*b and Bond Mill Work Index (BMWi). Large scale trials have been conducted within a commercial assay laboratory to demonstrate and optimise incorporation of the Ci test into routine sample preparation protocols. While Ci based estimates of A*b and BMWi are not as precise compared to larger volume more expensive test-work, the ability to undertake large numbers of tests typically in a systematic downhole manner, provides a high level of data support through adjacency. A Ci based approach is highly suitable for variability mapping, domaining and selecting large composite samples for more precise testing. Within the context of the AMIRA P843 project this forms part of an integrated work fl ow designed to support geometallurgical integration. The development of a comminution test linked to routine assay sample preparation represents significant value adding to a process that in most cases is already going to be carried out. This paper introduces the Ci test concept and application to geometallurgical testing for throughput modelling