31 11TH MILL OPERATORS’ CONFERENCE 2012 / HOBART, TAS, 29 - 31 OCTOBER 2012 INTRODUCTION UG2 platinum ore has a friable mineral-bearing seam composed predominantly of chromite. Hanging- and foot- walls predominate with reasonably competent silicate. The ore is, in theory, well-suited to autogenous grinding and this has been successfully practiced. However, if the fraction of hard waste is too low, the mill throughput decreases. This challenge has driven operations to switch to high ball load ROM milling. However, their hope is to return to the more economic AG milling, but clear operating limits are required to assess the longer-term viability in relation to their various ore-bodies and mining techniques. Therefore, a pilot plant campaign was planned and conducted to test mixtures of UG2 ore (silicate and chromite) and hard waste silicate, using an AG mill in open circuit (Bueno et al, 2011). Three tests were conducted at the following feeding conditions: 1. 20 per cent UG2 +60 mm: 80 per cent UG2 -60 mm 2. 20 per cent waste +60 mm : 80 per cent UG2 -60 mm 3. ten per cent waste +60 mm : 90 per cent UG2 -60 mm. The data from the pilot tests show clear effects of the multi- component feed on AG mill performance: • The hard component accumulated in the mill load and trommel oversize, due to its slow breakdown characteristics, and was retained in the coarser size fractions. • The proportion of coarse particles in the AG mill feed was necessary to maintain good AG performance, as the coarse particles act as grinding media. A lack of coarse particles lead to the AG mill ‘sanding up’, resulting in decreased throughput and reduced energy efficiency. • As the soft component increased in the feed, the mill throughput increased but the mill product became coarser. • There is an optimal blend of multi-component feed, based on a balance between the ratios of the hard to soft and the coarse to fine. UG2 ore and waste characterisation Samples of UG2 and waste mill feed, collected during the pilot campaign, were used in a comprehensive ore composition and breakage characterisation program. The density distribution for each feed material is presented in Figure 1. The results of component specific breakage characterisation tests, conducted using the JKDWT and Bond tests (Napier-Munn et al, 2005), are show in Table 1. The density distribution data indicated three classes of components for UG2 ore, but the JKDWT results show that there is almost no difference in UG2 low and mid density particles. The data also show that chromite rocks are not competent, as indicated by the high A × b figures, and that low-density silicate rocks in the UG2 ore are less competent than in specific waste samples. Multi-component autogenous/semi- autogenous grinding model The current JKSimMet models (Napier-Munn et al, 2005) assume a uniform feed, and describe it using a single set 1. SAusIMM, PhD Candidate, Julius Kruttschnitt Mineral Research Centre, Sustainable Minerals Institute, 40 Isles Road, Indooroopilly Qld 4068. Email: m.bueno@uq.edu.au 2. FAusIMM, Chair in Sustainable Comminution, Julius Kruttschnitt Mineral Research Centre, Sustainable Minerals Institute, 40 Isles Road, Indooroopilly Qld 4068. Email: malcolm.powell@uq.edu.au How to Use Hard Ore Components as Grinding Media M P Bueno 1 and M S Powell 2 ABSTRACT The commonly used SAB, SABC and run-of-mine (ROM) ball mill circuits can achieve high throughputs with good operating stability. However, these circuits consume a substantial amount of grinding media, which can have a substantial impact on the OPEX and the ‘carbon footprint’, specifically when viewed as an ‘embodied’ energy input. On the other hand, fully autogenous (AG) circuits can operate at much lower operating costs, but with limited throughput. The control of AG mills, fed by ores with hard and soft components, can also be challenging, due to the sensitivity of the mill to the ratio of hard to soft components. In this paper, a multi-component modelling approach was used to demonstrate that the harder component should be used as grinding media, and its use should be kept to a minimum to avoid reduction in the mill throughput. There is an optimal blend of hard to soft, and any optimal blending condition is both ore-dependent and mill-specific. Establishing this blend is challenging, and consequently discourages the use of autogenous mills. The new modelling approach addresses this challenge by providing a quantitative prediction of the influence of blending soft and hard components in a mill. This prediction can then be used to establish the required blend for maintaining a stable and efficient operation in autogenous grinding mode.