Dynamic simulation of industrial grinding circuits : mineral liberation, advanced process control, and real-time optimisation

Étant donné que les minéraux apparaissent fréquemment dans des associations complexes dans la nature, la libération minérale est un aspect clé du traitement de minerais et celle-ci est accomplie par comminution. Cette opération est certainement l’une des plus importantes, mais aussi des plus coûteuses dans l’industrie. La réussite globale d’une usine dépend souvent de la performance du circuit de broyage car il existe un compromis pour atteindre la taille des particules libérant les minéraux ciblés afin d’obtenir des concentrés de haute pureté tout en ayant de faibles coûts d’opération, lesquels sont largement influencés par la consommation énergétique. Dans les années récentes, les entreprises ont été confrontées à des objectifs de performance plus exigeants, une concurrence accrue sur les marchés, et des réglementations environnementales et de sécurité plus strictes. D’autres défis supplémentaires sont inhérents aux circuits de broyage, par exemple les réponses non linéaires, le niveau élevé d’intercorrélation entre les variables et les recirculations de matière. Les problèmes ci-dessus soulignent la pertinence d’avoir des systèmes de contrôle et d’optimisation adéquats pour lesquels les praticiens profitent de plus en plus des approches basées sur des modèles pour y faire face de façon systématique. La modélisation et la simulation sont des outils puissants ayant des avantages significatifs tels que les faibles coûts, les temps requis pour réaliser des expériences relativement courts et la possibilité de tester des conditions opérationnelles extrêmes ainsi que différentes configurations des circuits sans interrompre la production. De toute évidence, la qualité des résultats sera aussi bonne que la capacité du modèle à représenter la réalité, ce qui souligne l’importance d’avoir des modèles précis et des procédures de calibrage appropriées, un sujet fréquemment omis dans la littérature. Un autre aspect essentiel qui n’a pas été rapporté est l’intégration efficace de la libération minérale aux systèmes de contrôle et d’optimisation de procédés. Bien qu’il s’agisse d’une information clé directement liée aux performances de l’étape de concentration, la plupart des stratégies se concentrent exclusivement sur la taille de particule du produit. Ceci est compréhensible étant donné qu’il est impossible de mesurer la distribution de libération présentement. Basée sur une librairie de simulation d’usines de traitement des minerais déjà existante, cette recherche aborde lesdits problèmes en (1) développant un modèle de libération minérale visant à coupler les étapes de broyage et de concentration ; (2) programmant et validant par calibrage un modèle phénoménologique de broyeur autogène/semi-autogène (BA/BSA), nécessaire pour compléter la librairie de simulation ; (3) couplant un simulateur de circuit de broyage à un procédé de concentration avec le modèle de libération, et (4) développant un système de contrôle et d’optimisation qui considère explicitement des données de libération minérale pour évaluer les avantages économiques. Les principaux résultats confirment que le modèle de libération est capable de reproduire avec précision des distributions de libération minérale couramment observées dans l’industrie. Cependant, si les données de calibrage correspondent à un point d’opération unique, la validité pourrait être limitée aux régions voisines proches. Le problème de caractériser l’évolution de la libération minérale aux diverses conditions d’opération ainsi qu’aux régimes transitoires reste à être abordé. Le modèle de libération s’est aussi révélé utile pour coupler des circuits de broyage avec des procédés de concentration, en particulier pour une unité de flottation. Quant au modèle de BA/BSA, celui-ci peut capturer le régime statique ainsi que la dynamique d’un broyeur réel et conjointement avec le reste des équipements dans la librairie de simulation, des circuits de broyage industriels. Ceci a été confirmé par le calibrage à partir des données d’opération d’une usine et des tests en laboratoire, tout en suivant une procédure systématique, contribuant aussi au sujet de l’établissement de méthodologies de calibrage standardisées. Pour terminer, les expériences concernant la stratégie de contrôle et d’optimisation basée sur la libération minérale suggèrent que l’utilisation de cette information peut améliorer la performance globale des circuits de broyage-séparation en réagissant aux variations des caractéristiques de libération, qui à leur tour influencent l’efficacité de séparation. L’étude de cas réalisé révèle que cela peut entraîner une augmentation du débit massique et de la teneur du concentré, de la récupération des métaux et des revenus de l’ordre de +0.5%, +1%, +1% et +5%, respectivement, par rapport au cas où ces informations sont omises.As minerals frequently appear in complex associations in nature, mineral liberation is one of the most relevant aspects in ore processing and is achieved through comminution. This operation is one of the most important, but also one of the most expensive ones in industry. The global efficiency of a plant often depends on the performance of the grinding circuit, since there is a compromise to achieve the particle size liberating the targetted minerals in order to obtain high purity concentrates while maintaining low operating costs, which are largely influenced by the energy consumption. In recent years, companies have been facing more demanding performance targets, stronger competition, and more stringent environmental and safety regulations. Additional challenges are inherent to the grinding circuits themselves, e.g. the nonlinear responses, high degree of intercorrelation of the different variables, and material recirculations. The abovementioned issues highlight the relevance of adequate process control and optimisation, and practitioners rely more often on model-based approaches in order to face them systematically. Modeling and simulation are powerful tools with significant advantages such as low costs, required times for conducting experiments are relatively short, and the possibility of testing extreme operational conditions as well as different circuit configurations without disrupting production. Evidently, the quality of the results will only be as good as the model capacity to represent the reality, which emphasises the relevance of having precise models and proper calibration procedures, the latter being a topic frequently omitted in the literature. Another crucial aspect that has not been reported yet is the effective integration of mineral liberation in control and optimisation schemes. Although it is a key piece of information directly related to the performance of the concentration stage, most strategies focus exclusively on the particle size. This is understandable given that it is currently impossible to measure the liberation distribution online. Based on an existing mineral processing plant simulation library, this research addresses these problems by (1) developing a mineral liberation model aiming at linking the grinding and concentration stages; (2) programming a phenomenological autogenous/semiautogenous (AG/SAG) mill model, required to complement the simulation toolbox, and validating it through calibration; (3) coupling a grinding circuit simulator to a concentration process by means of the liberation model, and (4) developing a plantwide control and optimisation scheme considering mineral liberation data explicitly to evaluate the economic benefits. The main results confirm that the liberation model is capable of reproducing accurately mineral distributions observed in industry. If calibration data correspond to a single operating point, its validity may however be limited to the close neighbourhood. Characterising the evolution of mineral liberation in different operating conditions and transient states remains to be addressed. The liberation model proved to be equally useful in coupling grinding circuits with concentration processes, specifically for flotation. As for the AG/SAG mill model, it can capture the steady state and dynamic behaviour of an actual device and, along with the rest of pieces of equipment in the simulation toolbox, of industrial grinding circuits. This was confirmed through calibration from plant data and laboratory testwork following a systematic procedure, contributing to the endeavour of establishing standard calibration methodologies. Lastly, the results of the designed control and optimisation scheme suggest that using liberation data for control and real-time optimisation can improve the overall performance of grinding-separation circuits by reacting to variations in the liberation characteristics, which in turn influence the concentration performance. The case study reveals that doing so can lead to increases in the concentrate mass flow rate and grade, metal recovery, and global profits in the order of +0.5%, +1%, +1%, and +5%, respectively, compared to the case omitting this information

Mining Technologies Innovative Development

The present book covers the main challenges, important for future prospects of subsoils extraction as a public effective and profitable business, as well as technologically advanced industry. In the near future, the mining industry must overcome the problems of structural changes in raw materials demand and raise the productivity up to the level of high-tech industries to maintain the profits. This means the formation of a comprehensive and integral response to such challenges as the need for innovative modernization of mining equipment and an increase in its reliability, the widespread introduction of Industry 4.0 technologies in the activities of mining enterprises, the transition to "green mining" and the improvement of labor safety and avoidance of man-made accidents. The answer to these challenges is impossible without involving a wide range of scientific community in the publication of research results and exchange of views and ideas. To solve the problem, this book combines the works of researchers from the world's leading centers of mining science on the development of mining machines and mechanical systems, surface and underground geotechnology, mineral processing, digital systems in mining, mine ventilation and labor protection, and geo-ecology. A special place among them is given to post-mining technologies research

Development of performance functions for economic performance assessment of process control systems

Economic performance assessment (EPA) of control systems is receiving increasing attention in both academia and industry. It addresses the estimation of the potential benefits resulting from control upgrade projects and monitoring and improvement of economic performance of the control system. Economic performance of control systems can often be related to crucial controlled variables dynamically and when controlled variables move away from an optimal operating point either more profit will be made or more cost will be incurred. This relation can be modelled by performance functions (PFs). When the multivariate nature of a process’s economic model is not considered, PFs of different controlled variables are referred to as individual performance functions. Otherwise, PFs of dependent controlled variables are referred to as joint performance functions. PFs play an important role in the latest techniques of EPA. There appears, however, to be no systematic method for developing PFs. The lack of such a method restrains further research into EPA, as without well-established PFs an EPA cannot be conducted smoothly and therefore cannot effectively support decision-making for management. The development of PFs is a bottleneck in the further research into EPA. Furthermore, the multivariate nature of processes has not been taken into account sufficiently as far as the relevant literature is concerned, which hampers the accuracy of PFs and accordingly the accuracy of economic assessment results. The contributions of this thesis lie in the following aspects: • A methodology for developing PFs is proposed, based on the PF development for an electric arc furnace, a grinding mill circuit and a stage of a bleach plant. • A comprehensive case study of an EPA of three controllers of a grinding mill circuit is conducted using a newly published framework to show the significance of PFs and how to perform an EPA systematically. • The current practice and guidelines on the control and functional/economic performance assessment of grinding mill circuits are captured using a survey study. The multivariate nature of an electric arc furnace’s economic model is investigated and joint performance functions are built based on individual performance functions. A multivariate economic assessment is conducted that shows how joint performance functions can help to provide a more accurate estimate of the economic performance of a controlled process. A web-based survey study on grinding mill circuits in mineral processing industries is conducted. One of its objectives is to obtain general PFs of grinding circuits. The survey results provide instructive insight into the PFs of grinding circuits. Furthermore, an in-depth literature review is conducted and the relationship between the product’s particle size distribution of grinding mill circuits and mineral recovery in downstream flotation circuits is revealed. The PFs of a grinding mill circuit being considered are formed, based on the survey results and literature study. An investigation into the PF development of a stage of a bleach plant is performed and crucial ideas used for their development are abstracted. A methodology for developing PFs for the EPA of control systems is then proposed by synthesising the methods used in the PF development described above. This methodology mainly includes the following stages: Stage 1: Determine information required for PF development. • Process operation and control understanding. • Process economics understanding. Stage 2: Gain required information on PF development. • PF-related information elicitation using survey research. • PF-related information available in the literature, including textbooks, journal papers, conference papers. • PF-related information from plant tests. Stage 3: Obtain suitable performance measures. Stage 4: Make suitable assumptions. Stage 5: Determine PFs. Stage 6: Develop Joint PFs. An economic assessment of three controllers (a nonlinear model predictive controller, a decentralized controller and three single-loop proportional-integral-derivative controllers) of the considered grinding mill circuit is conducted, using an EPA framework published recently to show the central role of PFs in the EPA and how to perform an EPA systematically. The circuit’s PFs, developed as described above, are used for the assessment. The EPA also shows that the improvement in the economic performance with the nonlinear model predictive controller mainly results from the improvement of the operating point and the controlled variables’ variation reduction only contributes a small part to the overall improvement, due to the characteristic of the PF of the circuit’s product particle size distribution. In addition, a web-based survey study is conducted and the current practice and guidelines on the control and functional/economic performance assessment of grinding mill circuits are captured. The questionnaire used for the study includes five segments. The first part identifies the respondents and the second part is intended to obtain background information on the milling circuits. The third part concerns the choice of key process variables and their economic impact. Part four involves the control of milling circuits and control loop performance and part five covers economic issues.Thesis (PhD)--University of Pretoria, 2010.Electrical, Electronic and Computer Engineeringunrestricte

Advances in Computational Intelligence Applications in the Mining Industry

This book captures advancements in the applications of computational intelligence (artificial intelligence, machine learning, etc.) to problems in the mineral and mining industries. The papers present the state of the art in four broad categories: mine operations, mine planning, mine safety, and advances in the sciences, primarily in image processing applications. Authors in the book include both researchers and industry practitioners