Sustainable Processing of Mineral Resources

17

Int. J. Soc. Mater. Eng. Resour. Vol.20, No.1, (Apr. 2014)

1　INTRODUCTION

　Growth of global economy and the development of new technologies continually demands for an increased supply of minerals and metals. This sets sustainability challenges for the mining and minerals processing industry pertaining to the・ efficient use of mineral raw materials including waste

management and recycling, prevention of material losses and emissions,

・ reduction of energy demands and related emissions of greenhouse gases, directly and indirectly related to production,

・ availability of water and its allocation between different competing stakeholder groups,

・ consideration of environmental impacts from mine start-up and operation to closure and reclamation,

・ societal constraints as given by changed legislation, health and safety issues, competition with other sectors, and lastly

・ the availability of skilled people. 　In Europe these challenges have been identified on both national and international level, leading to the formulation of national mineral strategies in several countries, e.g. Finland 2010 [1], Sweden 2013 [2] or Germany 2010 [3] ; as well as the definition of roadmaps for research and development, for instance the research agenda formulated by the European ERA-MIN expert network on industrial handling of raw materials for European industries [4]. In Sweden a new mining research program [5] has recently been launched that with a view to the entire value chain focuses on sustainable mining and processing of primary and secondary resources. 　Meeting the challenges of future resource supply and productivity will require increased investment and operating costs with additional capital needed for a more sustainable processing [6] but on the other hand there is a chance of generating higher revenue from improved resource utilization and reduced energy consumption.

2　SUSTAINABLE MINERAL PROCESSING

　Within mineral processing available technologies have matured during recent decades but there is still a considerable potential for improvement. With respect to sustainability the major challenges in mineral processing - in research and development as well as in industrial mineral production - lie in improving the overall resource efficiency for particular ore deposits, i.e. enhanced recovery of valuable minerals with reduced energy consumption and water demands while minimizing also the waste from production.

　New challenges arise from the future exploitation of deposits with more complicated ore properties. The general trend is towards lower grades, fine-grained ores and a more complex mineralogy. The decrease in ore grades is illustrated in Figure 1 showing the development over time for different commodities taken from an Australian study [7]. Considering this enhanced mineral liberation and separation processes are required to still produce concentrate at sufficiently high grades and recoveries.

Sustainable Processing of Mineral Resources

Jan ROSENKRANZ and Pertti LAMBERG

Department of Civil, Environmental and Natural Resource Engineering Luleå University of Technology, SE-97187 Luleå, Sweden

E-mail : [email protected]

This paper reviews some of the recent challenges in the sustainable processing of primary mineral resources and discusses the technical prospects for meeting these challenges. The second part describes the integrated approach of geometallurgy being a prerequisite for improving resource efficiency along the production chain of minerals and metals. The different elements of a geometallurgical program are discussed and examples for ongoing geometallurgical research and education as pursued at Luleå University of Technology are presented.

Key Words : Mineral processing, Sustainability, Resource efficiency, Geometallurgy

ReviewReceived February 24, 2014Accepted for Publication March 1, 2014©2014 Soc. Mater. Eng. Resour. Japan

Figure 1　Decreasing ore grades, based on Mudd [7]

18 Jan ROSENKRANZ et al.


　Mineral liberation is achieved by grinding the ore to fine particle sizes. The comminution stage is usually not only the most energy-intensive step within mineral processing plants - compare Figure 2 for the energy saving potential identified for the US mining industry [8] - but it is also crucial for all subsequent steps in mineral beneficiation, as the sufficient liberation of valuable minerals is the key prerequisite for any downstream ore concentration process. 　However, the selection and operation of comminution devices today are often not effective due to limited ore characterization, particularly when ignoring the variability in liberation size within an ore body [9]. Lack of knowledge with respect to ore texture and mineral associations results in aiming for fixed product particle size whereas in many cases this means unnecessarily fine grinding. Also adjusting the breakage mechanism (in terms of mode of stress, stress intensity and rate) to the mineral texture of a particular ore can lead to an enhanced liberation already at coarser particle sizes, thus allowing decreasing the size reduction ratio and energy demands as well as enhancing downstream processing. 　In recent years new avenues in grinding have been explored by introducing new mill types to the comminution of hard minerals. This mainly comprises the adaption of mills from other application areas (industrial minerals, cement) to ore comminution, as for instance the high pressure grinding rolls (HPGR) and different types of stirred media mills [10]. Recent developments relate to make also vertical spindle mills available. 　Selection of the appropriate breakage mechanism or equipment type respectively in one grinding stage, does not only affect the overall energy utilization. Also the downstream beneficiation can be improved as certain types of milling devices particularly support the formation of micro cracks. Inducing micro cracks, partly coinciding with the mineral grain boundaries, results in particle weakening and increased liberation and therefore facilitates subsequent grinding and concentrating processes. For instance recovery from leaching processes is usually facilitated by an increased number of micro cracks [11]. 　Novel comminution technologies based on high voltage electro dynamic fragmentation, pre-weakening by microwave assistance or ultrasonic treatment have been investigated [12] [13][14], showing that grindability and mineral liberation can principally be enhanced while scale-up to industrially relevant capacities is still an issue. Chemical pre-treatment refers to the utilization of grinding aids to decrease energy losses in the pulp but also to using chemicals that effect crack initiation and propagation [15]. 　Design and operating conditions of comminution devices can

then be further optimized using advanced modeling and simulation methods [16]. Particle simulations based on computational physics, as the discrete element method or similar, allow improving the design and performance of mills and crushers with respect to energy utilization and liner wear. Figure 3 shows the results from a DEM study of a tumbling mill using input data from an in-mill sensor that measured the mill liner deflection due to the charge dynamics for model verification [17].

　Finally improved comminution can also be achieved by process optimization on grinding circuit level as well as process plant level. A high potential for energy savings resides in the introduction of certain crusher types that help to move the size distribution towards fine particles, the application of HPGR or choke-fed cone crushers. 　Also combining comminution and physical separation reduces the amount of ore to be ground, which actually increases capacity, but on the other hand usually leads to a higher process complexity in terms of additional processing steps and also process control demands. Promising design concepts refer to (i) improved classification methods within comminution circuits, (ii) the successive concentration and size reduction, for instance within staged grinding and flotation, or (iii) the pre-concentration by removing liberated gangue already at coarser particle sizes, e.g. by sensor-based sorting, gravity separation etc. Although the benefits of pre-concentration are obvious these technologies are presently implemented only at a few mining sites. 　Within ore concentration processes the recovery and selectivity of physical separations need to be further improved to become more resource efficient. For instance, the efficiency of froth flotation separation is depending on suitable particle size ranges. In the flotation of base metal ores, about 10% of the valuable minerals in the feed are lost in the very fine and in the coarse fractions. In the case of flotation of oxide and silicate minerals, the losses are generally higher. Coarse mineral particle recovery is limited due to an increased probability of detachment with increasing size and density, whereas the very fine and lighter particles do not manage to penetrate the fluid flow around the air bubbles thus decreasing the probability of collision. Some basic approaches exist to adjust the flotation process to fine particle flotation, involving high intensity dispersion and mixing, while low intensity flotation with larger sized air bubbles is generally intended for coarse particle flotation.

Figure 2　Energy savings potential U.S., based on [8]

Figure 3　Charge dynamics in tumbling mills [17]

19Sustainable Processing of Mineral Resources


　As stated above the characterization of mineral ores by its mineralogical and processing properties and their integration into process design and optimization are an important key to productivity improvements along the overall production chain from the ore to the metal product. Such a holistic approach is given by the quite young research field of geometallurgy.

3　THE GEOMETALLURGICAL APPROACH

　Geometallurgy combines geological and metallurgical/ processing information in order to create a spatially-based predictive model for mineral processing plants and is therefore widely regarded as an interdisciplinary approach that holds significant potential to utilize non-renewable mineral resources more efficiently and sustainably. 　Reliable information about the ore’s processing properties and its variations, based on representative sampling, quantitative mineralogy using advanced analysis methods and mineral processing tests, provide the basis for rigorous process modeling and simulation that can be used for optimizing the production scheduling and mineral beneficiation processes. 　To make use of this potential it is necessary to have a methodology at hand for ore characterization under uncertainty and variability, adequate data presentation and predictive mineral process modeling. Such a comprehensive methodology, applicable to the investigation of different ore types and various processing options, is subject to research and development today in order to : ・Define the ore boundaries based not only on metal grades but on

holistic economic assessment of the full production chain from mining through processing to final products.

・Define the production schedule to provide the most efficient utilization of the resource.

・At the feasibility stage of new plants design efficient processes that produce a product within given specifications considering the variability in the ore qualities,

・ Improve the recovery of valuable minerals and the final product quality along the entire production chain of an existing plant,

・ Identify valuable associated minerals and develop suitable and profitable process designs for their co-production, as well as detect and remove undesired minerals before metallurgical processing,

・ Predict and control the amount and composition of tailings and, by simulation, identify ways and means to recover valuables and/or reduce harmful components from waste streams. 　Ongoing research at Luleå University of Technology is aiming

on such an integrated approach to practicable geometallurgical modeling. This is done by combining state-of-the-art mineralogical analyses and improved technological testing with the 3D modeling of the ore body’s properties in order to model and simulate the processes along the production chain of mining, mineral processing and metallurgical processing. 　The conceptual design of the geometallurgical framework involves methods and tools that are utilizable also in conjunction with existing process modeling and simulation environments and commercial mine planning software. Within the geometallurgical approach at Lulea University of Technology, material analyses and data modeling are defined in a way that allows later connecting to the modeling and simulation of downstream metallurgical extraction and refining processes. 3.1　Ore characterization　Indications for the ore’s processing properties that describe its behavior during grinding and physical separation can already be obtained from mineralogical analyses, whereas additional technological tests are used to quantify the response of the ore to the mineral processing. Particular attention has to be paid to the behavior of the non-liberated, mixed particles as these are strongly affecting metal recovery and separation efficiency. 　At Luleå University of Technology mineral samples are commonly analyzed with respect to (i) the phase identification using optical microscopy, X-ray diffraction and SEM, (ii) the modal mineralogy, i.e. mass proportion of minerals in sample, by combining element-to-mineral conversion, XRD-Rietveld and automated mineralogy [18], and (iii) the mineral liberation and associations based on automated mineralogy, where polished sections of particle collectives are scanned by EDS spectroscopy detectors and combined with the image analysis of high resolution SEM images [19]. 　Figure 4 illustrates the particle’s mineral composition information for a mixed mineral particle as received from mineral liberation measurements with Oxford Instrument’s INCA Feature software. Results are used to define distributions of particles of different size and varying mineral composition that in the following serve as the input to process modeling and simulation. 　For the individual unit operations of mineral processing, like

froth flotation, magnetic separation, and density separation as well as for crushing and grinding, lab or bench scale tests are conducted. Besides that a variety of technological tests are used in parallel or as alternative methods, e.g. drop weight tests that give information about particle breakage behavior under impact or compressive strength tests. Batch grinding tests are complementarily used to

Figure 5　Particle liberation from batch grinding test

Figure 4　SEM-based particle image analysis



link the particle size reduction with energy for grinding and mineral liberation as shown in Figure 5.

3.2　3D property modeling　The ore’s properties are modeled in 3D based on spatial pattern information of the ore body including geometry and topology representation as for instance faults and horizons. Discretization methods (block models) are applied using different mesh definitions. For predicting unmeasured ore parameter values at innumerable locations statistical models are being developed for interpolation. In particular spatial property models for the different technological parameters are required that are most likely of non-linear character. Parts of the ore body that show similar processing properties are then defined as so-called geometallurgical domains in order to minimize the number of analyses as well as the numerical effort for process simulation necessary within a geometallurgical program. 　Figure 6 shows exemplarily the 3D representation of the

distribution of phosphorous minerals, mostly as apatite, within the ore body of the Kiruna iron ore mine in Northern Sweden. In order to meet the specifications of the blast furnace process parts of the ore requires an additional flotation step for reducing the phosphor content, i.e. within production planning the block-wise information on expected phosphor content is essential.

3.3　Process modeling and simulation　Within the geometallurgical approach a process model for mineral beneficiation is used in conjunction with the spatial model of the ore body for predicting the behavior of the ore during mineral processing - in both the design case as well as in the development of control strategies. For describing the processing properties within the geometallurgical model not only an extended data model is required that is capable of a combined presentation of geological and mineralogical information together with the technological parameters. The model has also to be populated with statistically sound data by applying concepts from geostatistics. 　The general challenge in mineral process modeling is still the limited number of data that is available for deriving the necessary process model parameters, which requires a careful evaluation of the results with respect to any extrapolation. Figure 7 summarizes exemplarily the information that needs to be provided to a process simulator. Besides grades and lithology data also processing properties like the Bond work index or flotation kinetics need to be given for each mine block. Results from process simulation are

primarily the material balances received from the process models for comminution and separation but also other derived quantities as particle size distributions, grades and recovery etc. 　Besides optimizing plant design, production scheduling and process control the geometallurgical model can also be used to develop new products and/or new applications for established products : ・Based on improved mineral and elemental analysis new products

(industrial minerals, metals, e.g. high tech materials as Te, Sb, Se in sulphide ores and rare earth elements in oxide ores) can be evaluated with respect to their economic potential and the risks in production by applying the geometallurgical model.

・New applications of known products will influence existing production by changed quality requirements and a different distribution of production capacity. This in turn results in the necessity of reconsidering the product program planning. Also this type of optimization can be conducted by adjusting parameters of the geometallurgical model.

3.4　The mineralogy-based approach at LTU　In order to reduce the model uncertainties remaining from geometallurgical testing of too few samples the objective of geometallurgical research and development should be to move the process modeling towards a more generic approach. This can be achieved by a differentiated view of a particle’s structure. As particles are comprised of minerals the key to advanced modeling is provided by linking the processing properties to the mineralogy, in particular to modal mineralogy and textural information. 　Such a mineralogy-based approach is pursued at Luleå University

Figure 6　Geological 3D model, Kiruna mine [20]Figure 7　Geometallurgical process simulation [21]

Figure 8　Modeling approach at LTU

21Sustainable Processing of Mineral Resources


of Technology. Figure 8 shows the different steps involved and the information needed when setting up the geometallurgical process simulation. The modal composition and the textural information from the geological model are used together with a model for initial breakage and mineral liberation to define the resulting particles of different mineral composition, i.e. the processing properties are described using mineralogical properties instead of conducting merely specific metallurgical testing. 　Particle-based modeling and simulation is then conducted by applying the principles of the so-called particle tracking method as developed by Lamberg and Vianna [22]. Particle tracking is a mass balancing technique of multiphase liberation data, which gives a quantitative description of how different particle types (representing different liberation classes) behave in the individual processing units and throughout the entire process.

3.5　Geometallurgy research and education at LTU 3.5.1　Rockliden Case Study : Boliden’s Rockliden complex Zn-Cu massive sulphide ore, located in North-Central Sweden, approximately 150km south of the Skellefte ore district, contains various antimony-bearing minerals. While antimony itself has been defined as a critical raw material by the Commission of the European Union, the presence of antimony lowers the quality of the copper concentrate from flotation. Within an ongoing case study the mineralogy of Rockliden is investigated in more detail. The analysis of the distribution of Sb-bearing minerals in the ore and in the process after lab-scale flotation tests is used to define different geometallurgical domains within the ore body and to identify means for future Sb control [23]. Figure 9 shows the corresponding flow sheet used for the laboratory tests together with the distribution of Sb-bearing minerals in the different concentrates. 3.5.2　Malmberget case study : The geology and process

mineralogy of LKAB’s Malmberget iron ore, located in Northern Sweden close to the city of Gallivare, has been studied. While establishing a geometallurgical program a technique to quantify minerals from routine chemical assays has been developed [24], involving electron microprobe (EPMA), X-ray fluorescence (XRF) and SATMAGAN analyses. In order to define a geological model of the deposit also an ore classification system based on the iron mineralogy, iron mineral grades and gangue mineralogy has been established. 3.5.3　Geometallurgical testing : The ore comminution behavior is investigated using drill cores as well as pre-crushed ore samples from different Swedish deposits. Based on rock mechanical strength tests like PLT and UCS, drop weight testing and lab

scale grinding tests the effects of mineralogical composition and different textural archetypes on the resulting particle size reduction and mineral liberation are systematically investigated in order to link particle properties to mineralogy [25]. Results are then used to further develop efficient test methods and enhance process modeling. 3.5.4　Geometallurgical Simulation Framework : The objective of another research project is the conceptual design and piloting of a simulation framework that integrates the geological model with the process modeling. This involves the development of suitable data models and corresponding data base management, the definition of interfaces to different ore characterization tools, and establishing the particle-based modeling and simulation as described above. The proof of concept will be done based on a case study for a Swedish iron ore involving sampling on plant level. 3.5.5　Researcher Network ProMinNet : In the field of process mineralogy and geometallurgy a researcher network has been established between Luleå University of Technology, the Norwegian University of Science and Technology in Trondheim, the University of Oulu, Finland, and the Technical University Bergakademie Freiberg in Germany, in order to provide advanced skills for participating researchers and transfer technologies between the partner institutions. The cooperation focuses on advanced techniques in automated mineralogy and comprises workshops, PhD courses and site visits as well as researcher exchange and a joint conference. The network is financed by the Nordic Council of Ministers (NordForsk). 3.5.6　Geometallurgy courses : An advanced-level course on geometallurgy has been developed and held for the Swedish mining company LKAB [26]. The course syllabus is tailor-made and comprises lectures on the company’s specific geology, process mineralogy and mineral and metallurgical processing as well as an exercise on process modeling and simulation. A project assignment is revised at closing workshop together with the R&D management. Geometallurgy and process mineralogy courses are also taught within the different master programs at Luleå University of Technology.

4　CONCLUDING REMARKS

　More sustainable processing of mineral resources is possible by improving single comminution and separation processes but also by the optimization of entire flow sheets. The key to this lies in a deeper knowledge and a sound understanding of the mineralogy. Developing geometallurgical programs that combine geological and metallurgical information in a spatially-based predictive model for mineral processing plants, is therefore regarded as a promising approach to improve resource efficiency within mineral processing.

Acknowledgements

　The financial support of the CAMM Centre of Advanced Mining and Metallurgy, established at Luleå University of Technology under the Swedish Strategic Research Initiative program, is gratefully acknowledged.

References

[1] Finland’s Mineral Strategy. Kirjapaino Keili Ltd, Vantaa, ISBN 978-952-217-134-4 (2010).

[2] Sweden’s Minerals Strategy : For sustainable use of Sweden’s mineral resources that creates growth throughout the country. Ministry of Enterprise Energy and Communications (2013).

Figure 9　Sb-bearing minerals in flotation products [23]



[3] The German Government’s Raw Materials Strategy - Safeguarding a sustainable supply of non-energy mineral resources for Germany. Federal Ministry of Economics and Technology (2010).

[4] Vidal, O., Weihed, P., Hagelüken, C., Bol, D., Christmann, P., Arndt, N. (eds.) ERA-MIN Research Agenda, ERA-MIN Network on the Industrial Handling of Raw Materials for European Industries (2013).

[5] Björkman, B., Bäckblom, G., Greberg, J., Weihed, P. (eds.) Strategic research and innovation agenda for the Swedish mining and metal producing industry, Report to Vinnova - Swedish Governmental Agency for Innovation Systems (2013).

[6] Dobbs, R., Oppenheim, Thompson, F. Brinkman, M. and Zornes, M. Meeting the world’s energy, materials, food and water needs, Report of the MGI McKinsey Global Institute (2011).

[7] Mudd, G.M. The Sustainability of Mining in Australia : Key Production Trends and Their Environmental Implications for the Future, Research Report No RR5, Dep. of Civil Engineering, Monash University & Mineral Policy Institute, April (2009).

[8] US Department of Energy, Industrial Technologies Program Mining Industry Energy Bandwidth Study, BCS Inc (2007).

[9] Rosenkranz, J. Better resource efficiency by improved comminution, SUSMP’12 International Conference on Sustainable Mineral Processing, Oulu, Finland (2012).

[10] Batterham, R. Trends in comminution driven by energy, Advanced Powder Technology 22, pp.138-140 (2011).

[11] Dhawan, N., Safarzadeh, M.S., Miller, J.D., Rajamani, R.K., Moats, S.M. Insights into heap leaching technology, Pre-prints SME Annual Meeting, Seattle, Feb. 19-22 (2012).

[12] Bluhm, H., Frey, W., Giese, H., Hoppe, P., Schultheiss, C., Strassner, R. Application of pulsed HV discharges to material fragmentation and recycling , IEEE Transactions on Dielectrics and Electrical Insulation, 7, 5, 625-636 (2000).

[13] Kingman, S.W. Recent developments in microwave processing of minerals, International Materials Reviews 51, 1, 1-12 (2006).

[14] L.F. Gaete-Garretón, L.F., Vargas-Hermández, Y.P., Velasquez-Lambert, C. Application of ultrasound in comminution, Ultrasonics 38, 345-352 (2000).

[15] El-Shall, H., Somasundaran, P. Physico-chemical aspects of grinding : a review of use of additives, Powder Technology, 38, 275-293 (1984).

[16] Powell, M.S. and Morrison, R.D. The future of comminution

modeling, International Journal of Mineral Processing 84, pp. 228-239 (2007).

[17] Alatalo, J. Charge dynamics in tumbling mills : simulation and measurements with an in-mill sensor, licentiate thesis Luleå University of Technology (2011).

[18] Amiri Parian, M., Lamberg, P. Combining chemical analysis (XRF) and quantitative X-ray diffraction (Rietveld) in modal analysis of iron ores for geometallurgical purposes in Northern Sweden, Proceedings 12th SGA Biennial Meeting 2013, Mineral Deposit Research for A High-Tech World Vol. 1, 356-359 (2013).

[19] P Lamberg, P., Rosenkranz, J., Wanhainen, C., Lund, C., Minz, F., Mwanga, A., Amiri Parian, M. Building a Geometallurgical Model in Iron Ores using a Mineralogical Approach with Liberation Data, Proceedings 2nd AUSIMM International Geometallurgy Conference, Brisbane, Australia, 30 September - 2 October 2013, 317-324 (2013).

[20] Niiranen, K. and Fredriksson, A. A systematic approach of geometallurgical mapping of the Kirunavaara iron ore, Proceedings Conference in Minerals Engineering, Luleå, Sweden (2012).

[21] Lamberg, P. Particles - The bridge between geology and metallurgy, Proceedings Conference in Minerals Engineering, Luleå, Sweden (2011).

[22] Lamberg, P., Vianna, S.M.S. A technique for tracking multiphase mineral particles in flotation circuits, Proceedings of VII Meeting of the Southern Hemisphere on Mineral Technology, Ouro Preto, Brazil, pp.195-202 (2007).

[23] Minz, F., Bolin, N.-J., Lamberg, P., Wanhainen, C. Detailed characterization of antimony mineralogy in a geometallurgical context at the Rockliden ore deposit, North- Central Sweden, Minerals Engineering, 52, pp.95-113 (2013).

[24] Lund, C., Lamberg. P., Lindberg, T. Practical way to quantify minerals from chemical assays at Malmberget iron ore operations - An important tool for the geometallurgical program, Minerals Engineering 49, pp.7-16 (2013).

[25] Mwanga, A., Rosenkranz, J., Lamberg, P., Koch. P.-H. Simplified Comminution Test Method for Studying Small Amounts of Ore Samples for Geometallurgical Purposes, Conference Exploration, Resource and Mining Geology, Cardiff, UK, 21-22 October (2013).

[26] Lindberg, T., Mattsby, C., Niiranen, K., Taavoniku, K., Hallberg, D., Fredriksson, A., Lamberg, P., Rosenkranz, J. Geometallurgy@LKAB, Proceedings Conference in Minerals Engineering, Luleå, Sweden (2013).

Sustainable Processing of Mineral Resources

Documents

Transcript of Sustainable Processing of Mineral Resources