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Amelunxen P.,Aminpro Chile | Runge K.,Metso Process Technology and Innovation
Mineral Processing and Extractive Metallurgy: 100 Years of Innovation | Year: 2014

This paper reviews the key events in the history of flotation modeling from 1935 through 2013. The focus is on first order kinetics models with an emphasis on the commonly used methods in the design and engineering sector of extractive metallurgy. Some ideas for future direction are also provided. Source


Jankovic A.,Metso Process Technology and Innovation | Dundar H.,Hacettepe University | Mehta R.,Deloitte
Journal of the Southern African Institute of Mining and Metallurgy | Year: 2010

An extensive laboratory grinding study was carried out on a magnetite ore in order to assess the grinding behaviour of magnetic concentrate and tail from low intensity magnetic separation (LIMS). The test work involved Bond ball mill testing, rod milling, low intensity magnetic separation (LIMS), and batch ball milling down to product sizes of around P80~25 microns. A total of 18 Bond tests and over 150 batch grinding tests and sieve sizing were carried out. Throughout the grinding tests, power draw was continuously monitored. The relationship between the grinding energy and product size was analysed using the conventional energy-size concepts. It was found that the Rittinger equation fits the experimental data well. However, Bond's equation does not fit the experimental data well, and therefore a modified Bond equation was developed. Differences in grinding properties between the magnetic and non-magnetic component were analysed and compared to the bulk ore. It was found that grinding properties differ significantly and therefore separate grinding test work may be required for each grinding step in the magnetite ore beneficiation flowsheet. © The Southern African Institute of Mining and Metallurgy, 2010. Source


Jankovic A.,Metso Process Technology and Innovation | Valery W.,Metso Process Technology and Innovation
Minerals Engineering | Year: 2013

Since the early days, there has been a general consensus within the industry and amongst grinding professionals that classification efficiency and circulating load both have a major effect on the efficiency of closed circuit ball mills. However, the effect of each is difficult to quantify in practice as these two parameters are usually interrelated. Based on experience acquired over the years and the investigative work conducted by F.C. Bond, it was established that the optimum circulating load for a closed ball mill-cyclone circuit is around 250%. This value is used as guideline for the design of new circuits as well as to assess the performance of existing circuits. The role of classification in milling appears to have been neglected in the current efforts to reduce the energy consumption of grinding. Two past approaches, experimental and modelling, for quantifying the effects of classification efficiency and circulating load on the capacity of closed ball mill circuits, are revisited and discussed in this paper. Application to the optimisation of existing circuits and design of new circuits is also discussed, with special attention to the development of more energy efficient circuits. © 2012 Elsevier Inc. All rights reserved. Source


Isokangas E.,Metso Process Technology and Innovation | Valery W.,Innovation Farm | Jankovic A.,Innovation Farm | Sonmez B.,Metso Process Technology and Innovation
26th International Mineral Processing Congress, IMPC 2012: Innovative Processing for Sustainable Growth - Conference Proceedings | Year: 2012

The production of minerals for economic use is a two-stage process, involving mining to extract the mineral from the ground, and processing to convert the mineral into a marketable product. Generally, mining and processing have been viewed as self-contained entities. Both have separate objectives, separate cost centres and key performance indicators (KPIs) that do not reflect the customer/supplier relationships that inherently exist. However, mining and processing operations are inter-connected and therefore intimately inter-related with the performance of one operation affecting the performance of another. Optimizing each stage separately without considering the whole system often misses potential economic benefits and energy savings. During the past fifteen years, the authors have been involved in implementing a holistic methodology "Mine to Mill Process Integration and Optimisation (Mine to Mill PIO)" to maximize the overall profitability of the operation rather than just optimizing any individual process in a mining operation. Metso Process Technology and Innovation (PTI), along with their project partners, have conducted several projects to significantly increase their production- generating typically 5% to 20% higher throughput and improve the overall mine and concentrator performance through PIO methodology. This proven methodology has applications ranging from greenfield projects to long-standing operations with AG/SAG, HPGR or conventional grinding circuits. This paper explains the Mine to Mill PIO methodology and discusses the benefits of such an approach on the energy consumption, the overall costs and benefits of mining operations. The paper also summarizes several case studies illustrating the use of PTI methodology in a variety of applications. Source


Meng J.,University of Queensland | Xie W.,University of Queensland | Brennan M.,University of Queensland | Tabosa E.,Metso Process Technology and Innovation | And 2 more authors.
IMPC 2014 - 27th International Mineral Processing Congress | Year: 2014

Turbulence and its distribution are of great importance in flotation cell design as they affect suspension of particles, air dispersion and particle-bubble collision rates, which in turn determine flotation performance. However, there is no mature technique to measure turbulence in three phase (liquid-solid-gas) systems such as in flotation cells. In this article, the authors present two new approaches that are suitable for measuring turbulence distribution in three phase systems and validate their applicability. The first technique uses a piezoelectric vibration sensor (PVS) to measure fluid kinetic energy standard deviation and the second technique applies electrical resistance tomography (ERT) to measure conductivity variation at a measurement position in a flotation cell. For the PVS technique, calibration of the sensor was performed to determine the values of parameters that were needed to calculate the force applied to the sensor. Then measurement was conducted in a 60L batch flotation cell and the results were compared with LDA measurement. This demonstrated that the piezoelectric sensor signal provides a good representation of fluid kinetic energy standard deviation at the position of measurement. For the ERT technique, conductivity distribution data was processed to give conductivity variations, which were then used to calculate fluid kinetic energy standard deviation at the measurement position. The spatial distribution of turbulence obtained by performing multiple measurements at different positions in the 60 litre batch flotation cell was found to agree with the PVS measurement results. These two techniques are potentially powerful tools for turbulence measurement in flotation environments, enabling a clearer understanding of turbulence's influence on flotation performance to be determined. Source

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